Vide Item No 659 N11072022 O6829 O6830 Regulations 9617 to 9620 and the syllabus of Honours Minor Degree Programs in Engg_1 Syllabus Mumbai University


Vide Item No 659 N11072022 O6829 O6830 Regulations 9617 to 9620 and the syllabus of Honours Minor Degree Programs in Engg_1 Syllabus Mumbai University by munotes

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Copy to : -
1. The Deputy Registrar, Academic Authorities Meetings and Services
(AAMS),
2. The Deputy Registrar, College Affiliations & Development
Department (CAD),
3. The Deputy Registrar, (Admissions, Enrolment, Eligibility and
Migration Department (AEM),
4. The Deputy Registrar, Research Administration & Promotion Cell
(RAPC),
5. The Deputy Registrar, Executive Authorities Section (EA),
6. The Deputy Registrar, PRO, Fort, (Publi cation Section),
7. The Deputy Registrar, (Special Cell),
8. The Deputy Registrar, Fort/ Vidyanagari Administration Department
(FAD) (VAD), Record Section,
9. The Director, Institute of Distance and Open Learni ng (IDOL Admin),
Vidyanagari,
They are requested to treat this as action taken report on the concerned
resolution adopted by the Academic Council referred to in the above circular
and that on separate Action Taken Report will be sent in this connection.

1. P.A to Hon’ble Vice -Chancellor,
2. P.A Pro -Vice-Chancellor,
3. P.A to Registrar,
4. All Deans of all Faculties,
5. P.A to Finance & Account Officers, (F.& A.O),
6. P.A to Director, Board of Examinations and Evaluation,
7. P.A to Director, Innovation, Incubation and Linkages,
8. P.A to Director, Board of Lifelong Learning and Extension (BLLE),
9. The Director, Dept. of Information and Communication Technology
(DICT) (CCF & UCC), Vidyanagari,
10. The Director of Board of Student Development,
11. The Director, Dep artment of Students Walfare (DSD),
12. All Deputy Registrar, Examination House,
13. The Deputy Registrars, Finance & Accounts Section,
14. The Assistant Registrar, Administrative sub -Campus Thane,
15. The Assistant Registrar, School of Engg. & Applied Sciences, Kalyan ,
16. The Assistant Registrar, Ratnagiri sub -centre, Ratnagiri,
17. The Assistant Registrar, Constituent Colleges Unit,
18. BUCTU,
19. The Receptionist,
20. The Telephone Operator,
21. The Secretary MUASA

for information.

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Syllabus for
Honours/Minor Degree Programs
in Engineering



(Introduced from the academic year 2022 -23)
AC – 11/07/2022
Item No. – 6.59 (N)





University of Mumbai























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Manuual for Honours and Minor Degree Programs in Engineering

1. Introduction:
As per the AICTE’s Approval Process Handbook -2020 -21: Chapter VII - clause 7.3.2 (Page 99 -101), all
branches of Engineering and Technology shall offer Elective Courses in the EMERGING AREAS viz.,
Artificial Intelligence (AI), Internet of Things (IoT), Blockchain, Robotics, Quantum Computing, Data
Sciences, C yber Security, 3D Printing and Design, Augmented Reality/ Virtual Reality (AR/VR), as
specified in Annexure 1 of the Approval Process Handbook.
a) Under Graduate Degree Courses in EMERGING AREAS shall be allowed as specialization from the
same Department. The minimum additional Credits for such Courses shall be in the range of 18 -
20 and the same shall be mentioned in the degree, as specialization in that particular area. For
example, doing extra credits for Robotics in Mechanical Engineering shall earn B.E./ B.Tech.
(Honours .) Mechanical Engineering with specialization in Robotics
b) Minor specialization in EMERGING AREAS in Under Graduate Degree Courses may be allowed
where a student of another Department shall take the minimum additional Cre dits in the range
of 18 -20 and get a degree with minor from another Department.
It is also made very clear by AICTE that areas in which Minor Degree/Honours may be offered are
numerous. It is up to the Universities with the help of their Academic Board/C ouncil to decide whether
Minor Degree/ Honours . is to be offered or not in any particular area, which is not mentioned above.
AICTE approval is not required for offering Minor Degree/ Honours . in any such area, however the
criteria that “Minor Degree or Hono urs. will cumulatively require additional 18 to 20 credits in the
specified area in addition to the credits essential for obtaining the Under Graduate Degree in Major
Discipline (i.e. 160 credits)”
2. Proposed Honours and Minor Degree:
Honours and Minor degree program is introduced in order to facilitate the students to choose
additionally the specialized courses in the emerging areas of their choice and build their competence in
such domains. Based on AICTE guidelines, the Faculty of Sc ience and Technology has proposed to offer
following Honours/ Minor degree program corresponding to each engineering program:
Table 1: Honours / Minor Degree Programs
Sr. No Honours/Minor degree programs
1 Infrastructure Engineering
2 Smart Cities
3 Waterways Transport Engineering
4 Professional Practices in Structural Engineering
5 Green Technology and Sustainability Engineering
6 Infrastructure Policies & Regulations
7 Artificial Intelligence and Machine Learning

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8 Blockchain
9 Cyber Security
10 Augmented Reality and Virtual Reality
11 Data Science
12 Internet of Things (IoT)
13 Waste Technology
14 Electric Vehicles
15 Microgrid Technologies
16 Robotics
17 3D Printing
18 Industrial Automation

The Honours and Minor degree programs selection for each of the engineering programs offered in
University of Mumbai is as given in next section.

3. Mapping with Engineering/Technology Programs in University of Mumbai
Honour’s/ Minors degree program is being introduced by the Faculty of Science and Technology of
University of Mumbai in order to facilitate the students to choose additionally the specialized
courses in the emerging areas of their choice and build their competence i n such domains. As per
AICTE guidelines, Honours/Minors degree program to be chosen by eligible students (based on
certain criteria given in manual) studying in third year of various Engineering program's are
elaborated in Table 2 to bring clarity to all s takeholders including students, faculty members and
institutions. Each eligible student can opt for maximum one Honour’s or one Minor Programs at
any time.















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Table 2: Honours and Minor Degree Program Mapping with Engineering Programs
Honours /
Minor
Degree
Programs Programs who can offer this as the
Honours Degree Program
Programs who can offer this as the Minor
Degree program
Row Column A Column B Column C
1 Infrastructure
Engineering Civil Engineering 1. Mechanical Engineering
2. Production Engineering
3. Automobile Engineering
4. Mechatronics Engineering
5. Printing and Packaging Technology
6. Electrical Engineering
7. Chemical Engineering
8. Electronics and Telecomm. Engineering
9. Electronics Engineering
10. Computer Engineering
11. Information Technology
12. Instrumentation Engineering
13. Electronics and Computer Science
14. Artificial Intelligence & Data Science
15. Cyber Security
16. Computer Science and Engineering
(Artificial Intelligence & Machine Learning)
17. Computer Science and Engineering (Internet
of Things & Cyber Security including
Blockchain)
18. Computer Science and Engineering (Data
Science)
19. Artificial Intelligence & Machine Learning
20. Data Engineering
21. Internet of Things
22. Computer Science and Design

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2 Smart Cities Civil Engineering 1. Civil and Infrastructure Engineering
2. Mechanical Engineering
3. Production Engineering
4. Automobile Engineering
5. Mechatronics Engineering
6. Printing and Packaging Technology
7. Electrical Engineering
8. Chemical Engineering
9. Electronics and Telecomm. Engineering
10. Electronics Engineering
11. Computer Engineering
12. Information Technology
13. Instrumentation Engineering
14. Electronics and Computer Science
15. Artificial Intelligence & Data Science
16. Cyber Security
17. Computer Science and Engineering
(Artificial Intelligence & Machine Learning)
18. Computer Science and Engineering (Internet
of Things & Cyber Security including
Blockchain)
19. Computer Science and Engineering (Data
Science)
20. Artificial Intelligence & Machine Learning
21. Data Engineering
22. Internet of Things
23. Computer Science and Design
3 Waterways
Transport
Engineering Civil Engineering 1. Civil and Infrastructure Engineering
2. Mechanical Engineering
3. Production Engineering
4. Automobile Engineering
5. Mechatronics Engineering
6. Printing and Packaging Technology
7. Electrical Engineering
8. Chemical Engineering
9. Electronics and Telecomm. Engineering
10. Electronics Engineering
11. Computer Engineering
12. Information Technology
13. Instrumentation Engineering
14. Electronics and Computer Science
15. Artificial Intelligence & Data Science
16. Cyber Security
17. Computer Science and Engineering
(Artificial Intelligence & Machine Learning)
18. Computer Science and Engineering (Internet
of Things & Cyber Security including
Blockchain)
19. Computer Science and Engineering
(Data Science)
20. Artificial Intelligence & Machine Learning
21. Data Engineering

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22. Internet of Things
23. Computer Science and Design
4 Professional
Practices in
Structural
Engineering Civil Engineering 1. Civil and Infrastructure Engineering
2. Mechanical Engineering
3. Production Engineering
4. Automobile Engineering
5. Mechatronics Engineering
6. Printing and Packaging Technology
7. Electrical Engineering
8. Chemical Engineering
9. Electronics and Telecomm. Engineering
10. Electronics Engineering
11. Computer Engineering
12. Information Technology
13. Instrumentation Engineering
14. Electronics and Computer Science
15. Artificial Intelligence & Data Science
16. Cyber Security
17. Computer Science and Engineering
(Artificial Intelligence & Machine Learning)
18. Computer Science and Engineering (Internet
of Things & Cyber Security including
Blockchain)
19. Computer Science and Engine ering (Data
Science)
20. Artificial Intelligence & Machine Learning
21. Data Engineering
22. Internet of Things
23. Computer Science and Design
5 Green
Technology
and
Sustainability
Engineering 1 Civil Engineering
2 Chemical Engineering
3 Printing and Packaging Technology
1. Civil and Infrastructure Engineering
2. Mechanical Engineering
3. Production Engineering
4. Automobile Engineering
5. Mechatronics Engineering
6. Electrical Engineering
7. Electronics and Telecomm. Engineering
8. Electronics Engineering
9. Computer Engineering
10. Information Technology
11. Instrumentation Engineering
12. Electronics and Computer Science
13. Artificial Intelligence & Data Science
14. Cyber Security
15. Computer Science and Engineering
(Artificial Intelligence & Machine Learning)
16. Computer Science and Engineering
(Internet of Things & Cyber Security
including Blockchain)
17. Computer Science and Engineering (Data
Science)
18. Artificial Intelligence & Machine Learning
19. Data Engineering

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20. Internet of Things
21. Computer Science and Design
6 Infrastructure
Policies &
Regulations Civil and Infrastructure Engineering 1. Civil Engineering
2. Mechanical Engineering
3. Production Engineering
4. Automobile Engineering
5. Mechatronics Engineering
6. Printing and Packaging Technology
7. Electrical Engineering
8. Chemical Engineering
9. Electronics and Telecomm. Engineering
10. Electronics Engineering
11. Computer Engineering
12. Information Technology
13. Instrumentation Engineering
14. Electronics and Computer Science
15. Artificial Intelligence & Data Science
16. Cyber Security
17. Computer Science and Engineering
(Artificial Intelligence & Machine Learning)
18. Computer Science and Engineering (Internet
of Things & Cyber Security including
Blockchain)
19. Computer Science and Engineering (Data
Science)
20. Artificial Intelligence & Machine Learning
21. Data Engineering
22. Internet of Things
23. Computer Science and Design
7 Artificial
Intelligence
and
Machine
Learning 1 Computer Engineering
2 Electronics and Telecomm.
Engineering
3 Electronics Engineering
4 Information Technology
5 Electronics and Computer Science
6 Mechatronics Engineering
7 Computer Science and Engineering
(Internet of Things & Cyber Security
including Blockchain)
8 Cyber Security
9 Computer Science and Engineering
(Data Science)
10 Internet of Things
11 Data Engineering
12 Computer Science and Design 1. Civil Engineering
2. Civil and Infrastructure Engineering
3. Mechanical Engineering
4. Production Engineering
5. Automobile Engineering
6. Printing and Packaging Technology
7. Electrical Engineering
8. Chemical Engineering
9. Instrumentation Engineering
10. Biomedical Engineering

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8 Blockchain 1 Computer Engineering
2 Electronics and Telecomm.
Engineering
3 Electronics Engineering
4 Information Technology
5 Electronics and Computer Science
6 Artificial Intelligence & Data Science
7 Cyber Security
8 Computer Science and Engineering
(Artificial Intelligence & Machine
Learning)
9 Computer Science and Engineering
(Data Science)
10 Internet of Things
11 Data Engineering
12 Computer Science and Design
13 Artificial Intelligence & Machine
Learning 1. Civil Engineering
2. Civil and Infrastructure Engineering
3. Mechanical Engineering
4. Production Engineering
5. Automobile Engineering
6. Mechatronics Engineering
7. Printing and Packaging Technology
8. Electrical Engineering
9. Chemical Engineering
10. Instrumentation Engineering
11. Biomedical Engineering


9 Cyber Security 1 Computer Engineering
2 Electronics and Telecomm.
Engineering
3 Electronics Engineering
4 Information Technology
5 Electronics and Computer Science
6 Artificial Intelligence & Data Science
7 Computer Science and Engineering
(Artificial Intelligence & Machine
Learning)
8 Computer Science and Engineering
(Data Science)
9 Internet of Things
10 Artificial Intelligence & Machine
Learning
11 Data Engineering
12 Computer Science and Design 1. Civil Engineering
2. Civil and Infrastructure Engineering
3. Mechanical Engineering
4. Production Engineering
5. Automobile Engineering
6. Mechatronics Engineering
7. Printing and Packaging Technology
8. Electrical Engineering
9. Chemical Engineering
10. Instrumentation Engineering
11. Biomedical Engineering


10 Augmented
Reality and
Virtual Reality 1 Computer Engineering
2 Electronics and Telecomm.
Engineering
3 Electronics Engineering
4 Information Technology
5 Electronics and Computer Science
6 Computer Science and Engineering
(Internet of Things & Cyber Security
including Blockchain)
7 Artificial Intelligence & Data Science
8 Cyber Security
9 Computer Science and Engineering
(Artificial Intelligence & Machine
Learning)
10 Computer Science and Engineering
(Data Science)
11 Internet of Things 1. Civil Engineering
2. Civil and Infrastructure Engineering
3. Mechanical Engineering
4. Production Engineering
5. Automobile Engineering
6. Mechatronics Engineering
7. Printing and Packaging Technology
8. Electrical Engineering
9. Chemical Engineering
10. Instrumentation Engineering
11. Biom edical Engineering

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12 Artificial Intelligence & Machine
Learning
13 Data Engineering
14 Computer Science and Design
11 Data Science 1 Computer Engineering
2 Electronics and Telecomm.
Engineering
3 Electronics Engineering
4 Information Technology
5 Electronics and Computer Science
6 Mechanical Engineering
7 Production Engineering
8 Automobile Engineering
9 Computer Science and Engineering
(Internet of Things & Cyber Security
including Blockchain)
10 Cyber Security
11 Computer Science and Engineering
(Artificial Intelligence & Machine
Learning)
12 Internet of Things
13 Artificial Intelligence & Machine
Learning
14 Electrical Engineering
15 Computer Science and Design 1. Civil Engineering
2. Civil and Infrastructure Engineering
3. Mechatronics Engineering
4. Printing and Packaging Technology
5. Chemical Engineering
6. Instrumentation Engineering
7. Biomedical Engineering


12
Internet of
Things
(IoT) 1. Computer Engineering
2. Electronics and Telecomm.
Engineering
3 Electronics Engineering
4 Information Technology
5 Electronics and Computer Science
6 Electrical Engineering
7 Mechanical Engineering
8 Production Engineering
9 Automobile Engineering
10 Mechatronics Engineering
11 Artificial Intelligence & Data Science
12 Cyber Security
13 Computer Science and Engineering
(Artificial Intelligence & Machine
Learning)
14 Computer Science and Engineering (Data
Science)
15 Artificial Intelligence & Machine
Learning
16 Data Engineering
17 Computer Science and Design 1. Civil Engineering
2. Civil and Infrastructure Engineering
3. Printing and Packaging Technology
4. Chemical Engineering
5. Instrumentation Engineering
6. Biomedical Engineering

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13 Waste
Technology Chemical Engineering 1. Civil Engineering
2. Civil and Infrastructure Engineering
3. Mechanical Engineering
4. Production Engineering
5. Automobile Engineering
6. Mechatronics Engineering
7. Printing and Packaging Technology
8. Electrical Engineering
9. Electronics and Telecomm. Engineering
10. Electronics Engineering
11. Computer Engineering
12. Information Technology
13. Instrumentation Engineering
14. Electronics and Computer Science
15. Artificial Intelligence & Data Science
16. Cyber Security
17. Computer Science and Engineering
(Artificial Intelligence & Machine Learning)
18. Computer Science and Engineering
(Internet of Things & Cyber Security
including Blockchain)
19. Computer Science and Engineering (Data
Science)
20. Artificial Intelligence & Machine Learning
21. Data Engineering
22. Internet of Things
23. Computer Science and Design
14 Electric
Vehicles 1 Electrical Engineering
2 Mechanical Engineering
3 Production Engineering
4 Automobile Engineering
1. Civil Engineering
2. Civil and Infrastructure Engineering
3. Mechatronics Engineering
4. Printing and Packaging Technology
5. Chemical Engineering
6. Electronics and Telecomm. Engineering
7. Electronics Engineering
8. Computer Engineering
9. Information Technology
10. Instrumentation Engineering
11. Electronics and Computer Science
12. Artificial Intelligence & Data Science
13. Cyber Secur ity
14. Computer Science and Engineering
(Artificial Intelligence & Machine Learning)
15. Computer Science and Engineering
(Internet of Things & Cyber Security
including Blockchain)
16. Computer Science and Engineering (Data
Science)
17. Artificial Intelligence & Machine Learning
18. Data Engineering
19. Internet of Things
20. Computer Science and Design

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15 Microgrid
Technologies Electrical Engineering 1. Civil Engineering
2. Civil and Infrastructure Engineering
3. Mechanical Engineering
4. Production Engineering
5. Automobile Engineering
6. Mechatronics Engineering
7. Printing and Packaging Technology
8. Chemical Engineering
9. Electronics and Telecomm. Engineering
10. Electronics Engineering
11. Computer Engineering
12. Information Technology
13. Instrume ntation Engineering
14. Electronics and Computer Science
15. Artificial Intelligence & Data Science
16. Cyber Security
17. Computer Science and Engineering
(Artificial Intelligence & Machine Learning)
18. Computer Science and Engineering
(Internet of Things & Cyber Security
including Blockchain)
19. Computer Science and Engineering (Data
Science)
20. Artificial Intelligence & Machine Learning
21. Data Engineering
22. Internet of Things
23. Computer Science and Design
16 Robotics 1. Mechanical Engineering
2. Production Engineering
3. Automobile Engineering
4. Printing and Packaging Technology
5. Mechatronics Engineering
6. Electrical Engineering 1. Civil Engineering
2. Civil and Infrastructure Engineering
3. Chemical Engineering
4. Electronics and Telecomm. Engineering
5. Electronics Engineering
6. Computer Engineering
7. Information Technology
8. Instrumentation Engineering
9. Electronics and Computer Science
10. Artificial Intelligence & Data Science
11. Cyber Security
12. Computer Science and Engineering
(Artificial Intelligence & Machine Learning)
13. Computer Science and Engineering (Internet
of Things & Cyber Security including
Blockchain)
14. Computer Science and Engineering (Data
Science)
15. Artificial Intelligence & Machine Learning
16. Data Engineering
17. Internet of Things
18. Computer Science and Design
19. Biomedical Engineering

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17 3D Printing 1. Mechanical Engineering
2. Production Engineering
3. Automobile Engineering
4. Printing and Packaging Technology
1. Civil Engineering
2. Civil and Infrastructure Engineering
3. Mechatronics Engineering
4. Electrical Engineering
5. Chemical Engineering
6. Electronics and Telecomm. Engineering
7. Electronics Engineering
8. Computer Engineering
9. Information Technology
10. Instrumentation Engineering
11. Electronics and Computer Science
12. Artificial Intelligence & Data Science
13. Cyber Security
14. Computer Science and Engineering
(Artificial Intelligence & Machine Learning)
15. Computer Science and Engineering (Internet
of Things & Cyber Security including
Blockchain)
16. Computer Science and Engineering (Data
Science)
17. Artificial Intelligence & Machine Learning
18. Data Engineering
19. Internet of Things
20. Computer Science and Design
18 Industrial
Automation Instrumentation Engineering 1. Civil Engineering
2. Civil and Infrastructure Engineering
3. Mechanical Engineering
4. Production Engineering
5. Automobile Engineering
6. Mechatronics Engineering
7. Printing and Packaging Technology
8. Electrical Engineering
9. Chemical Engineering
10. Electronics and Telecomm. Engineering
11. Electronics Engineering
12. Computer Engineering
13. Information Technology
14. Electronics and Computer Science
15. Artificial Intelligence & Data Science
16. Cyber Security
17. Computer Science and Engineering
(Artificial Intelligence & Machine Learning)
18. Computer Science and Engineering
(Internet of Things & Cyber Security
including Blockchain)
19. Computer Science and Engineering (Data
Science)
20. Artificial Intelligence & Machi ne Learning
21. Data Engineering
22. Internet of Things
23. Computer Science and Design

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4. Honours and Minor Degree Eligibility Criteria for Students:

In view of the above -mentioned guidelines issued by AICTE in APH 2020 -21 for offering Honours and
Minor degree in the various engineering programs, the following recommendations are proposed on
the eligibility criteria for students opting for same;
i) Eligibility criteria for opting the Honours/ Minor Degree program:
a. Students with no backlog in semester I, II, and III
b. The CGPI (based on semester I, II, and III) of the students must be 6.75 and above
c. For direct second year (DSE) admitted students - No backlog in semester III and CGPI must be
6.75 and above
ii) Each eligible student can opt for maximum one Honour’s or one Minor Programs at any time.
iii) However, it is optional for students to take Honour s/M inor degree program.
iv) The H onours/ M inor degree program can be opted only during regular engineering studies
v) The student shall complete the Honours/ M inor degree program in stipulated four semesters only.

5. Eligibility criteria for Department/Institut e to offer Honours/Minor degree:
As the intention of offering the Honours degree program is to facilitate the advanced learners to build
their competence in emerging areas with additional in -depth course work, it becomes very essential to
ensure availabi lity of such expert faculties and infrastructure with the departments and institutes. The
proposed modality of approval is self -assessment and declaration basis. Institute can assess on
following points before offering Honours/Minor degrees,
1. The Honours Degree program out of 18 programs listed in Table -1 can only be offered by
an institute having the regular degree program running as specified in Table 2 column B.

2. Availability of Faculty expertise in domains of Honours/Minor degree programs
a. Regular faculty on institute role who has completed PhD/Masters in same domain.
OR
b. Regular faculty on institute role who is doing research either sponsored by government
agencies or industries or trusts.
OR
c. Regular faculty on institute role who has successfully completed certificate course in
same domain and able to deliver the expectations of specialisation in emerging areas.

3. Availability of laboratory infrastructure/facilities in domains of Honours /Minor degree
a. Established centre of excellence in same domain.
OR
b. Built research facilities to facilitate research in emerging areas
OR
c. Minimum facility is already developed to conduct hands on experience in chosen
domains of Honours and Minor degrees.

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6. Procedure of Starting Honours/Minor Programs:
Departments offering Honours/Minor Programs shall be assessed by Institute as per eligib ility criteria
mentioned in manual. Once found to be eligible fill the template of self assessment and send to Deputy
Registrar Affiliation and Development Section, Fort Campus of University of Mumbai for information and
simultaneously copy to Director Boa rd of Examination and Evaluation, Examination House, Mahatma Phule
Bhavan, Kalina campus of University of Mumbai. Affiliation section shall handover copy of same to LIC
committee to verify correctness of self declaration, as and when appointed to visit for continuation of
affiliation. Template to be used for self assessment and decleration form is given in Table 3.

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Table 3. Self-assessment and D eclaration form for starting Honours/Minor
Programs under University of Mumbai
Name of Institute:
Honours / Minor Program:

Do you have regular program to offer Honours Program? Yes/No
If Yes,
Availability of Regular Engineering Programs (as specified in
Table 2 column B of Honours and Minor Degree Program
Manual Part -1) Following regular programs exists in
Institute to offer Honours Program
mentioned above,
1.
2.

Do you have availability of Faculty expertise as per criteria mentioned in
manual to offer Honours Program? Yes/No
If Yes, (Strike through whichever is not applicable)
1. Regular faculty on institute role who is doing research either
sponsored by government agencies or industries or trusts. Yes
No
2. Regular faculty on institute role who had completed either Phd or
Masters in same domain of Honours Program. Yes
No
3. Regular faculty on institute role who has successfully completed
certificate course in same domain of Honours Program Yes
No

Do you have availability of laboratory facilities as per criteria mentioned
in manual to offer Honours Program? Yes/No
If Yes, (Strike through whichever is not applicable)
1. Availability of Established Centre of Excellence (CoE) in same domain
of Honours Program Yes
No
2. Availability of Research Facilities built to facilitate research in same
domain of Honours Program. Yes
No
3. Availability of Minimum facility to conduct hands on experience in
same domain of Honours Program Yes
No
This is to certify that Departments offering honours programs is assessed an d found that at least
one of the eligibility norms in each of the three eligibility criteria has been found fulfilling. Hence
forwarded application for starting Honours program in “…………………..” to University of Mumbai.


Head of Institute sign and seal
(Enclosure: Supporting documents of fulfilling criteria’s )

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7. Examination Process and Result Declaration
In current scenario First Year and Final Year of engineering examinations, assessments and result
declaration are entirely done by University, while as in Second and Third Year question papers are
delivered by University, assessment and results preparation and declaration after approval from
university is done by Institute on behalf of University following all ordinances and regulations of
university. Honou rs/Minor degrees courses will be offered in Third and Final Year of engineering as
specialisation in emerging areas.
By keeping in mind availability of expertise of faculty with particular Institute only, proposed following
modalities of Examination and Evaluation,
Internal Assessment Examination:
1. Two Internal Assessment (IA) tests shall be carried out at institute level for each subject of Honours
/ Minor programs as per the directives given in the scheme and the syllabus.
End Semester Examination:
1. Question papers of End Semester Examination for each subject shall be prepared by the paper
setter panel appointed by University of Mumbai.
2. End Semester Examination answer -books evaluation (for sem. V, sem. VI, sem. VII and sem. VIII) of
subjects offered at each Honours / Minor programs shall be carried out by respective institute at
institute level by the examiners appointed by Principal from the panel provided by University.
3. Moderation -moderation of the answer books shall be carried out as per the existing rules
applicable as per ordinance O.5046 -A to the regular examination by the moderator appointed by
Principal from the panel provided by t he university.
4. Revaluation - Revaluation of the answer books shall be carried out as per the existing rules
applicable to the regular examination by the examiners appointed by Principal
5. Each institute shall process the result applying ordinance O.5042 -A and prepare the gazette copy
of the results for respective semester for each Honours / Minor programs offered. Institutes shall
submit results for moderation and approval to University similar to process of semester II to VI.
Institute shall maintain the rec ord of each student for each of the Honours / Minor programs
offered till the completion of the Sem VIII end sem. examination.
6. University shall create portal for getting all marks and status of students results of Honours/Minor
Programs. University shall issue common grade sheet of Honours/Minors Programs after the
successful completion of all semesters including 8th semester (final semester of their regular
program).
7. If the students compeletes the Honours / Minor program but fails in Sem VII / VIII, he/ s he will not
get any degree at that point of time, but both after passing regular degree program and Honours/
Minor program. However, the Honours/ Minor program should be completed in four semesters
only.
8. The following ordinances are not applicable to Hono urs/Minors programs as these are applicable
for entire examination and overall results of semesters .
i. O.5043 -A
ii. O.5044 -A
iii. O.5045 -A
iv. O.229

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8. Award of Degree Certificates:
University shall make provision of two types of degrees, one without and with honours/
Minors program;

1. Degree certificate without honours/minors programs shall be one, which is currently
issued.

2. The students successfully completing the Honours / Minor program Degree shall be
awarded with the degree designated as: “B. E. in ………(regular) Engineering with
Honours/Minor in …….. (specialization)”

Example 1: Students s successfully completing BE in Mechanical Engineering with
specialization (Honour s) in 3D Printing shall get a degree as “B.E. in Mechanical Engineering
with Honours in 3D Printing”

Example 2: Students successfully completing BE in Electrical Engineering with specialization
(Minor) in 3D Printing shall get a degree as “B.E. in Electrical Engineering with Minor in 3D
Printing”

9. Honours and Minor Degree Program Scheme and Structure:
Honours and Minor degree program be offered from academic year 2022 -23 onwards along with Rev
2019 ‘C’ scheme syllabus.
Honours and Minor credit courses will be offered from Semester V onwards to Semester VIII, scheme
structure of syllabus is given in Table 3


















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Table 3. Template for Honours/ Minor degree program syllabus scheme

University of Mumbai
Honours in ---------------
(With effect from 2022 -23)
Year
&
Sem
Course Code
and Course
Title Teaching Scheme
Hours / Week Examination Scheme and Marks Credit
Scheme
Theory Seminar
/Tutorial Pract. Internal
Assess
ment End
Sem.
Exam Term
Work Oral Total Credits

TE
Sem. V HXXC501:
Subject 1 04 -- -- 20 80 -- -- 100 04
Total 04 - -- 100 - - 100 04
Total Credits = 04

TE
Sem. VI HXXC601:
Subject 2 04 -- -- 20 80 -- -- 100 04
Total 04 - - 100 - - 100 04
Total Credits = 04


BE
Sem. VII HXXC701:
Subject 3 04 -- -- 20 80 -- -- 100 04
HXXSBL701:
Lab-1 -- -- 04 -- -- 50 50 100 02
Total 04 - 04 100 50 50 200 06
Total Credits = 06

BE
Sem.VIII
HXXC801:
Subject 4 04 - -- 20 80 -- -- 100 04
Total 04 - - 100 - - 100 04
Total Credits = 04

Total Credits for Semesters V,VI, VII &VIII = 04+04+06+04 = 18
Reference: https://www.aicte -india.org/sites/default/files/APH%202020_21.p df (page 99 -101)

Dr. Suresh K. Ukarande
Associate Dean,
Faculty of Science and Technology ,
University of Mumbai

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20









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21






University of Mumbai





Syllabus

Honours/Minor Degree Programs
(with effect from 2022 -2023)


Faculty of Science and Technology


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22

UNIVERSITY OF MUMBAI
Honours/Minor Degree Programs
(with effect from 2022 -2023)
Sr. No Honours/Minor degree programs Page N o.
1 Infrastructure Engineering 23
2 Smart Cities 39
3 Waterways Transport Engineering 57
4 Professional Practices in Structural Engineering 74
5 Green Technology and Sustainability Engineering 91
6 Infrastructure Policies & Regulations 108
7 Blockchain 124
8 Cyber Security 142
9 Augmented Reality and Virtual Reality 164
10 Artificial Intelligence and Machine Learning 180
11 Data Science 195
12 Internet of Things (IoT) 210
13 Waste Technology 229
14 Electric Vehicles 241
15 Microgrid Technologies 254
16 Robotics 266
17 3D Printing 278
18 Industrial Automation 292

Note: Course code format used in the document
1. Course Code: HXXC -Z01: (example - HEVC -501)
H stands for Honours/ Minor course
XX : Abbrevation of Program code: eg. For Electric Veh icles- it is ‘EV’
C- Theory Course
Z for semester. For sem 5 -> 501

2. Skill Based Lab Code: HXXSBL -Z01: (example - HEVSBL -701)
H stands for Honours/ Minor course
XX : Abbrevation of Program code: eg. For Electric Veh icles- it is ‘EV’
SBL- Theory Course
Z for semester. For sem 7 -> 701

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23



University of Mumbai





Syllabus

Honours /Minor Degree Program
in
Infrastructure Engineering



FACULTY OF SCIENCE & TECHNOLOGY

(As per AICTE guidelines with effect from the academic year 2022 -2023)

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University of Mumbai
Infrastructure Engineering
(With effect from 2022 -23)
Year
&Se
m
Course Code and
Course Title Teaching
Scheme Hours / Week Examination Scheme and Marks Credit
Scheme
Theory Seminar/
Tutorial Pract Internal
Assess
ment End
Sem
Exam Term
Work Oral Total Credits

TE
Sem
V HIEC501:
Transportation
Infrastructure 04 -- -- 20 80 -- -- 100 04
Total 04 - -- 100 - - 100 04
Total Credits = 04

TE
Sem.
VI HIEC601:
Energy and IT
Infrastructure 04 -- -- 20 80 -- -- 100 04
Total 04 - - 100 - - 100 04
Total Credits = 04


BE
Sem.
VII HIEC701:
Geographic
Information
System 04 -- -- 20 80 -- -- 100 04
HIESBL701:Lab1
Geographic
Information
System -- -- 04 -- -- 50 50 100 02
Total 04 - 04 100 -- 50 200 06
Total Credits = 06

BE
Sem.
VIII
HIEC801:
Infrastructural
Planning and
Management 04 - -- 20 80 -- -- 100 04
Total 04 - - 100 - - 100 04
Total Credits = 04

Total Credits for Semesters V,VI, VII &VIII = 04+04+06+04=18

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Infrastructure Engineering: Semester -V
Subject Code Subject Name Credits
HIEC501 Transport Infrastructure 4

Contact Hours Credits Assigned
Theory Practical Tutorial Theory Practical Tutorial Total
4 - - 4 - - 4

Theory Term Work/Practical/Oral
Total Internal Assessment End
Sem
Exam Duration of End
Sem Exam TW PR OR Test -I Test -II Average
20 20 20 80 3 hrs. - - - 100

Rationale
Urban sprawl worldwide is causing tremendous pressure on transport infrastructure. Transportation
infrastructure is one of the most important factors for a country's progress. The complex network of
connections between coastal ports, inland ports, rails a nd air routes is the 'lifeline' of a nation and it forms a
foundation of economic development. Transportation is an important sector of the economy in its own right
and that has been proven by so many instances how transport infrastructure has added speed and efficiency
to a country's progress. India has a large and diverse transport sector with its own share of challenges and
students will be conversant with transport infrastructure, diverse Transportation needs and equipments after
completion of this cour se.


1. To understand the fundamentals of infrastructure and different modes of transportation globally and
current state of affairs in India
2. To illustrate the types of modern highways, bridges and tunnels required for the transport infrastructure.
3. To identify the Mass Transit systems, for end to end transport and the structural systems required for the
same.
4. To design airport infrastructure mechanism
5. To classify water way infrastructure
6. To study all the important tools and equipments required for the efficient functioning of Transportation
infrastructure.

Module Contents Hours
1 Introduction to Infrastructure : Definition of infrastructure, Need of infrastructure,
different forms of infrastructure, physical and social infrastructure, role of
infrastructure in the development of a nation, Transportation scenario globally and in
India; Overview of various transport systems in India -rail, road, air, waterways . Major
organizations and players in the field of transport infr astructure 07
2 Modern Highways : Roads, Planning concepts, Uninterrupted traffic systems, Signal
free intersections, Freeway, Expressway, Service roads, bye pass, Turnpike. 10 Objectives

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Bridges and Tunnels: Classification based on Structural Materials like Steel, RCC, Pre -
stressed concrete or Composite. Bridge types based on structural behaviour such as
Beam bridge, Truss Bridge, Arch Bridge, Suspension& Cable stayed cantilever and
special purpose bridges.
Tunneling Methods: Types and purpose of tunnels; factor s affecting choice of
excavation technique; Methods – soft ground tunneling, hard rock tunneling, shallow
tunneling, deep tunneling; Supports in Tunnels: Different types of supports in
tunneling and their applicability.
3 Mass Transit system : trains, ferries, buses, trams, Rapid mass transit systems such as
subways and surface light rail systems, Cable cars, Various types of guided transport,
tube, U -Bahn, metropolitan or underground , Metro rails, Structural components and
their selection cri teria.
07
4 Airport Planning : Airport Master Plan, Airport Site Feature, Economic and Financial
feasibility, Zoning around airports, design considerations for Apron, Runway, Taxiway,
Hangar.
Air traffic control : radar, satellite navigation, One way, Two -way radio
communication. ATC assistance during Departure, En -Route, Descent, Approach and
Landing. 08
5 Waterways transportation : History of water transportation, policies related to water
transportation in India. Status of river, canals and ocean transpo rtation in India.
Modes of water transport - pontoons, amphibians, hovercrafts, boats, ships, water
taxi. Advantages and disadvantages of water transportation.
Ports harbours and docks : Historical development of Port, Docks and Harbour. Port
building facil ities, Classification of harbours, Requirement of Harbour, Jetty, Harbour
components, characteristics of good harbour and principles of harbour planning 09
6 Modern surveying tools - Drones, satellite survey, GIS software, GPS system, Total
station, Electronic Distance Measurement (EDM) Instruments
Modern Equipment - Dumper trucks, dozers, vibratory rollers, graders, tunneling
equipments, lifting equipments (Cranes), sand washing equ ipments, earth movers,
different excavators, wheel tracto r scraper, trenchers, loaders, pile boring and pile
driving machine, concrete mixers. concrete batching/mixing plant, concrete pumps,
slip forms, concrete vibrator, hot mix plant 11

Contribution to Outcomes

After completion of the course work, students will be able to,
1. Understand the fundamentals of infrastructure and different modes of transportation
2. Illustrate the types of modern highways, bridges and tunnels along with tunnelling methods required
for the transport infrastructure.
3. Identify the mass transit system in transport infrastructure
4. Design different components of airport infrastructure along with it’s economical and financial
feasibility
5. Classify different modes of water transportat ion and evaluate the principles of harbour planning
6. Study different modern surveying tools and modern equipment required for transport
infrastructure

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Theory Examination: -

1. The question paper will comprise six questions; each carrying 20 marks.
2. The first question will be compulsory that will have short questions having wei ghtage of 4 -5 marks
covering the entire syllabus.

3. The remaining five questions will be based on all the modules. For this, the module shall be divided
proportionately further, and the w eightage of the marks shall be judiciously awarded in proportion to
the importance of the sub -module and contents thereof.

4. There can be an internal choice in various sub -questions/ questions in order to accommodate the
questions on all the topics/ sub -topics.

5. The students will have to attempt any three questions out of remaining five questions.

6. A total of four questions need to be attempted.


Text Books: -

1. A Sustainable Vis ion for Urban India, Jain A K, Publisher: Kalpaz Publications
2. Highway Engineering, C. E. G. Justo and S. K. Khanna, Nem Chand & Bros; 10th Edition 2015 (1 January
2001)
3. Railway Engineering, M. M. Agarwal and Satish Chandra, Oxford University Press.
4. Design of Bridges, N. Krishna raju, Oxford and IBH Publishing
5. Airport Engineering: Planning And Design by Saxena S C , CBS Publication
6. Airport planning and design, S.K. Khanna, S. S Jain, M.G Arora , Nem Chand Brothers; 6th edition (January
1, 1999)
7. Inland Water Transport in India by R.P. Misra published by Prasaran ga, University of Mysore in 1972.
8. Docks and Harbour Engineering: Dr. S.P Bindra, Dhanpatrai Publications, India
9. Harbour, Dock and Tunnel Engineering: R. Srinivasan, Charotar Publication, India
10. Remote sensing and Geographical Information System, By A. M. Ch andra and S. K. Ghosh, Narosa
Publishing House.
11. Advanced Surveying -Total Station, GIS and Remote Sensing by Satheesh Gopi, R. Sathikumar and N.
Madhu, Pearson publication
12. Surveying Vol. 2 by S. K. Duggal, McGraw Hill Publication


Recommended Books: -

1. Introduction to Infrastructure: An Introduction to Civil and Environmental Engineering, Michael R Penn
2. Remote Sensing & GIS,2/E —Bhatta – Oxford University Press
3. Modern Construction Equipment and Methods by Frank Harris
4. Construction Planning, Equipment, and Methods (McGraw -Hill Series In Civil Engineering) by Robert L
Peurifoy ), Clifford J. Schexnayder , AviadShapira
5. Driving Horizontal Workings and Tunnel, by Pokorovski, Mir Publishers, 1980.
6. Harbour, Dock and Tunneling Engineering by R. Srinivasan Published by Charotar Publication


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Infrastructure Engineering: Semester -VI
Subject Code Subject Name Credits
HIEC601 Energy and IT Infrastructure 4

Contact Hours Credits Assigned
Theory Practical Tutorial Theory Practical Tutorial Total
4 - - 4 - - 4

Theory Term Work/Practical/Oral
Total Internal Assessment End
Sem
Exam Duration of End
Sem Exam TW PR OR Test -I Test -II Average
20 20 20 80 3 hrs. - - - 100

Rationale
The power infrastructure consists of generation, transmission, and distribution systems that are essential to all
other infrastructures and every aspect of the economy. In India , various sources of energy are used to
generate power . These include coal, natural gas, hydro, nuclear, and renewable (includes solar, wind, small hydro
and biomass). Telecommunications infrastructure is a physical medium through which all Internet traffic flows.
This includes telephone wires, cables and mobile technology such as fifth -generation (5G) mobile networks. The
IT infra structure consists of all elements that support the management and usability of data and information.
These include the physical hardware and facilities (including data centers), data storage and retrieval, network
systems, legacy interfaces, and software to support the business goals of an enterprise.

1. Evaluate energy infrastructure and hydroelectric power plant.
2. Classify the tidal, wind and solar energy and its operation
3. Explain nuclear energy infrastructure, policies and regulations for estab lishing nuclear power plant
and issues related to radioactive waste
4. Design criterions for telecommunication tower
5. Describe the fundamental elements of IT infrastructure
6. Design criterions for developme nt of smart grid networks

Module Contents Hours
1 Introduction to energy infrastructure : Types of electrical generation; generation
system architecture; power plant planning and design.
Hydroelectric infrastructure : Site selection; classification; hydrographs; storage and
pondage; essential elements; selection of turbines, environmental impact assessment. 04
2 Tidal energy infrastructure : Fundamentals of tide; wave theory, loading and energy;
operating principle - oscillating device; turbine characteristics; devices; moorings and
anchors; foundations.
Wind energy infrastructure : Offshore and onshore wind; properties of wind; wind
resource assessment; wind turbine blades; wind turbines in grid; wind projects. 06 Objectives

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Solar energy infrastructure : Basics of solar PV, fundamentals of the design of solar
energy fie lds; concentrated solar power plant; solar water heating systems
3 Nuclear energy infrastructure : Policy and regulations; economics and financing of
nuclear power plants; nuclear technology selection and project implementation; fuel
supply, radioactive waste and management; issues; environmental impact 10
4 Telecommunication – Definition, use, functions, and components, site surveys - raw
land tower site survey and boundary survey, classification of telecommunication
towers, Telecommunication signals, Des ign of towers – configuration, tower erection,
transmission lines constru ction, operation and maintenance of distribution systems. 13
5 IT infrastructure – components of IT infrastructure, Internet and world wide web,
design, planning, and implementation of networks and servers, storage management ,
Backup / Restore Methodolo gy, Remote Access, Control, Administration. 12
6 Smart grid, transmission and distribution : Grid resilience; environmental
performance; operational efficiencies; network architecture; transmission systems;
wide area monitoring, protection and control, transmission and distribution
architecture; micro grids; vulnerability; peak load shifting and grid storage. 07

Contribution to Outcomes

After completion of the course work, students will have ability to
1. Explain generation of hydroelectric power and its impact on environment
2. Classify and design infrastructure for non conventional energy sources
3. Describe the policies and regulations for nuclear power plant, infrastructural requirement and its
environmental impact assessment
4. Evaluate the components and functions of telecommunication
5. Summarize the fundamental elements of IT infrastructure such as networks and servers, storage
and remote access
6. Design and develop smart grid networks for transmission and distribution of the energy

Theory Examination: -

1. The question paper will comprise six questions; each carrying 20 marks.
2. The first question will be compulsory that will have short questions having weightage of 4 -5 marks
covering the entire syllabus.

3. The remaining five questions will be based on all the modules. For this, the module shall be divided
proportionately further, and the weightage of the marks shall be judiciously awarded in proportion to
the importance of the sub -module and contents thereof.

4. There can be an internal choice in various sub -questions/ questions in order to accommodate the
questions on all the topics/ sub -topics.

5. The students will have to attempt any three questions out of remaining five questions.

6. A total of four questions need to be attempted.

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Text Books: -

1. Textbook of Renewable Energy (Wood head Publishing India in Energy) ,by S.C. Bhatia , R.K. Gupta
2. P. Jain, Wind Energy Engineering, McGraw -Hill.
3. Nuclear Power in India by N. Sharma, B. Banerjee, Rupa Publication 2008
4. Environ mental Issues for 21st Century by S. P. Dasgupta, Mittal Publication.
5. Steve Morris, Up the Tower: The complete Guide to Tower Construction, Champion Radio Products Brian
W. Smith, Communication Structures, Thomas Telford publications
6. ICT in Urban services , Compendium of global good practices, National Institute of Urban affairs,
http://pearl.niua.org/sites/default/files/books/GPGL1_ICT.pdf
7. Fundamentals of telecommunication - https://www.net.t -labs.tuberlin.
de/teaching/computer_networking/documents/telecomm _fundamentals.pd f
Recommended Books: -

1. Hydroelectric Energy, Renewable Energy and the Environment By Bikash Pandey , Ajoy Karki , ISBN
9781439811672 CRC Press
2. Tidal Energy Systems, 1st Edition, Design, Optimization and Control, Vikas Khare Cheshta Khare Savita
Nema Prashant Bareda, Elsevier
3. E book on Energy Law in India by Mohammad Naseem, Saman Naseem, 2017, publisher Wolters Kluwer
4. Graham, S. and Marvin, S. Planning Cybercities Integrating Telecommunications into Urban Planning, The
town planning review, 70(1), Liverpool Universit y Press
5. S. Borlase (2013) Smart Grid Infrastructure, Technology, and Solutions, CRC Press. ISBN 9781439829103.
6. L.F. Drbal, P.G. Boston, K.L. Westra, R.B. Erickson (1996) Power Plant Engineering, Kluwer Academic
Publishers. ISBN 9781461380474.
7. D. Greaves, G . Iglesias (2018) Wave and Tidal Energy, John Wiley & Sons Ltd. ISBN 9781119014454.
8. S. A. Kalogirou (2009) Solar Energy Engineering Processes and Systems, Elsevier. ISBN 9780123745019.
9. Basic Infrastructure for a Nuclear Power Project (2006) Technical Repor t, CI#128 IAEA. ISBN 9201085060.
10. Kiessling, F., Nefzger,P., Nolasco,J.F., Kaintzyk,U., (2003), Overhead Power Lines Planning Design
Construction , 4th Edition, Springer
11. Ganguli, S.K., Kohli,V., (2016), Power Cable Technology , CRC Press

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Infrastructure Engineering : Semester -VII
Subject Code Subject Name Credits
HIEC701 Geographic Information Systems 4

Contact Hours Credits Assigned
Theory Practical Tutorial Theory Practical Tutorial Total
4 - - 4 - - 4

Theory Term Work/Practical/Oral
Total Internal Assessment End
Sem
Exam Duration of End
Sem Exam TW PR OR Test -I Test -II Average
20 20 20 80 3 hrs. - - - 100

Rationale
Geographic information system (GIS) is a computer system for capturing, storing, checking, and displaying data
related to positions on Earth's surface. By relating seemingly unrelated data, GIS can help individuals and
organizations better understand spatial patterns and relationships. IS technology is a crucial part of spatial
data infra -structure. Many different types of information can be compared and contrasted using GIS. The system
can include data about people, such as population , income , or education level. It can include information about
the landscape , such as the location of streams, different kinds of vegetation , and different kinds of soil. It can
include information about the sites of factories, farms, and schools, or storm drains, roads, and electric power
lines. Use of Geographic’s Information system in all infrastructures will enhance the social, economic,
development of India in all aspects.


1. To understand the fundamentals of GIS, basics tools, and its applications in all branches of Civil and
infrastructure Engineering .
2. To Illustrate the variousComponent of GIS, co -ordinate systems for creations of vector data and raster
dataset by using various GIS tools.
3. To understand Basic geodata base system for Creation of various types of maps.
4. To create various thematic maps by using the vector Dat a set as well as raster data set.
5. To analyze spatial Data for solving real word problems.
6. To apply GIS output data for solving real life problems.

Module Contents Hours
1 Introduction to Geographic Information System
GIS: History, Development of GIS, Objective of GIS, Advantages of GIS. 03
2 Introduction to Maps: Definition, Scale, Types of Maps, elements of Map, Projection
Coordinate Systems: Geographic, rectangular and Polar – Transformation, types and
application.
GIS: What is GIS, components of GIS, its applications, open source softwares. 09 Objectives

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3 DBMS: -Database Management system – function – types – advantages, Introduction to
Toposheet. Various open data sources.
GIS Data Model : Spatial Data Types - , Vector data, Raster data, TIN (Triangulated
reregulated network) data model, comparison of Vector &raster data, Non spatial data
(attributes) & its types. Preprocessing of spatial data set.
10
4 GIS input data:
Vector Data: -Source s for GIS Data Shape files, Vector Data Input – Georeferencing, Map
digitization and editing, and Topology – Topological Relationship.
Raster Data Input – Digital Elevation Mode (DEM) - Introduction to DEM, types of Dem,
Uses of Dem & different types of re solution, Introduction to satellite images, image
classification, Quality assessment of freely available Digital Elevation Model, Raster File
Formats, Vector File Formats – Raster to Vector an d Vector to Raster Conversion. 12
5 GIS Data Analysis : Introduction to GIS data Analysis – Data selection, reclassification,
overlaying analysis, Buffer Analysis, Spatial Analysis (Dem Analysis,) Surface Analysis ,
Network Analysis , proximity Analysis, Vector & Raster Analysis Methods. Error in GIS and
key elem ents of maps. 12
6 GIS Output Design a nd Presentation
Introduction - Spatial and non -spatial data presentation - Map layout – Charts, graphs
and multimedia output, elements of spatial data quality, Meta data and introduction to
web GIS. 06

Contribution to Outcomes

After completion of the course work, students will be able to,
1. Explain GIS applications in various fields
2. Illustrate the types of maps, their characteristics and different co -ordinate system, Components of
GIS& Familiar with new GIS software.
3. Com pare the basics of Data Base Management system for GIS - vector data set, raster data set &
Produce an error free GIS database for civil engineering applications.
4. Create & design basic database like creation of shape files, vector data set, raster data set & Produce
an error free GIS database for civil engineering applications
5. Analyze GIS Data which includes creating buffers, Clipping Features, raster data analysis, vector Data
Analysis and Dissolve Features.
6. Application of spatial data output along with quality assessment for applications in Civil & Infrastructure
Engg.


Internal Assessment (20 Marks):
Consisting Two Compulsory Class Tests - First test based on approximately 40% of contents and second test
based on remaining contents (approximately 40% but excluding contents covered in Test I)

End Semester Examination (80 Marks):
Weight age of each module in end semester examination will be proportional to number of respective
lecture hours mentioned in the curriculum.
1) Question p aper will comprise of total six questions , each carrying 20 marks.
2) Question 1 will be compulsory and should cover maximum contents of the curriculum.

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3) Remaining questions will be mixed in nature (for example if Q.2 has part (a) from module 3 then part (b)
will be from any module other than module 3) .
4) The students will have to attempt any three questions out of remaining five questions
5) Total Four questions need to be attempted.

Text Books: -
1. Remote Sensing and Geographic Information System, By A.M. Chandra and S.K. Ghosh, Narosa Publication
House.
2. Remote Sensing: Principles and Applications by B C Panda .
3. Geographic Information System by Jatin Pandey .
4. Remote Sensing and GIs by Basudeb Bhatta , Oxford University.

Recommended Books: -
1. Jonathan Campbell and Michael Shin, Essentials of Geographic Information Systems, 2011, Saylor
Foundation , ISBN: 9781453321966.
2. Michael N. DeMeres, Fundamentals of Geographic Information Systems, 4th Edition, 2009, Wiley, ISBN:
9780470129067
3. NPTEL GIS web course.

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Infrastructure Engineering : Semester -VII
Subject Code Subject Name Credits
HIESBL701 Geographic Information System – Lab 2

Contact Hours Credits Assigned
Theory Practical Tutorial Theory Practical Tutorial Total
- 4 - - 2 - 2

Theory Term Work/Practical/Oral
Total Internal Assessment End
Sem
Exam Duration of End
Sem Exam TW PR OR Test -I Test -II Average
- - - - - 50 - 50 100


1. To acquire basic knowledge of Geographic Information System Lab practices and applying it for solving
real life problem in Civil & Infrastructure Engineering.
2. To illustrate basic GIS-terms which are connected to data processing by means of exercises
3. To prepare basic geo data for Spatial and non spatial Analysis.
4. To apply Google earth in Geographic information system for preparation of various shapes files,
preparation of vector dat a set.
5. To analyze basic geodata base by using various tools.
6. To convert GIS output into various thematic maps for solving various real life problems in Civil –
infrastructure Engineering.

List of Experiments

Module Contents Hours
1 Getting started with GIS software (QGIS, ArcGIS) & data collection from various free
available sources. 4
2 Georeferenceing and projection of toposheet, Digitization of map/ Toposheet. 4
3 Creation of thematic maps, Base Map preparation, Data Conversion – Vector to Raster,
Raster to Vector. 4
4 Google earth integrations in GIS. 4
5 Vector analysis and Raster analysis, adding attribute data – quarries on attribute data,
Map composition. 4
6 Developing Digital Elevation Model, its application & analysis. 4
7 A case study of GIS applications. 4

Contribution to Outcomes

Learner will be able to…
1. Apply the installation of GIS software’s and various tools.
2. Explain various Database structure like vector data, raster data set.
3. Prepare and convert vector data set into raster data set. Objectives

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4. Interpret Google earth with GIS.
5. Perform various types of Analysis on raster data, vector data.
6. Transform GIS output by preparation of various thematic maps.

GIS Software’s: Arc GIS 10.3, QGis.
Assessment
Term Work Including
Laboratory work : 25 Marks
Case Study/Report/Tutorial : 20 Marks
Attendance : 05 Marks
End Semester Oral Examination
Oral examination will be based on the entire syllabus.

Text Books: -
1. Remote Sensing and Geographic Information System, By A.M. Chandra and S.K. Ghosh, Narosa
Publication House.
2. Remote Sensing: Principles and Applications by B C Panda .
3. Geographic Information System, by JatinPandey .
4. Remote Sensing and GIs by Basudeb Bhatta , Oxford University.
Recommended Books: -
1. Jonathan Campbell and Michael Shin, Essentials of Geographic Information Systems, 2011, Saylor
Foundation , ISBN: 9781453321966.
2. Michael N. DeMeres, Fundamentals of Geographic Information Systems, 4th Edition, 2009, Wiley, ISBN:
9780470129067
3. NPTEL GIS web course.

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Infrastructure Engineering : Semester -VIII
Subject Code Subject Name Credits
HIEC801 Infrastructural planning and management 4

Contact Hours Credits Assigned
Theory Practical Tutorial Theory Practical Tutorial Total
4 - - 4 - - 4

Theory Term Work/Practical/Oral
Total Internal Assessment End
Sem
Exam Duration of End
Sem Exam TW PR OR Test -I Test -II Average
20 20 20 80 3 hrs. - - - 100

Rationale
Infrastructure is the resources required for a society and its economy to function. Infrastructure
Planning primarily relates to new infrastructure creation but also phasing out of deficient and
outdated infrastructure when it is cost -effective.
Economic infrastructure is an internal facility of a country that make business activity poss ible, Such as
communication, transportation and distribution networks, financial institutions and markets, and energy supply
systems. Economic infrastructure definitely ensures the mobility of labour and capital within/from the economy.
It results in the o verall growth of towns and cities. Infrastructures provide for a lot of employment generation and
employment opportunities. They also play a crucial role in national defense activities.


1. To understand the infrastructural scenario in India and opportunities and challenges to be faced in road
development.
2. To understand the Infrastructure economics, finance and social environmental risk in infrastructure
3. To Realizing the real -world risks and challenges in managing infrastructure.
4. To identify the needs in urban infrastructure development and recycling technologies
5. To Understand the impact of infrastructural projects on environment
6. To analyse success and failure of measure infrastructural projects in India

Module Contents Hours
1 Introduction -
Infrastructure scenario in India, transportation, power and telecom sectors, urban and
rural infrastructure in India, road infrastructure development in India, rural roads
development in India -opportunities and challenges 06
2 Infrastructure economics and finance, project structuring and risk allocation in project
finance, Public -Private Partnership (PPP) for infrastructure - case studies, risk
management in infrastructure projects, term sheet development economic and social
e4nvironmental risk in infrastru cture, 08
3 Project Governance, public sector governance, strategies for governing against
infr6astructure project turbulence, the governance model, data –base management, 10 Objectives

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actor mapping and social network analysis, fair process and negotiations, design
thinking, life cycle and benefit cost analysis
4 Innovative infrastructure financing, urban infrastructure needs in India and funding
options, new and innovative materials for long lasting road infrastructure, green
highways –recycling technology, durable road infrastructure –options and recent
developments, polycentric governance and incomplete design, successful project
delivery strategies. 10
5 Environmental impact assessment: Tools, impact on air ,water, soil & Noise, Role of
Biodiversity impac t Assessment, Identification ,Prediction &Evaluation of Impacts on
Biodiversity, Techniques of Biodiversity impact assessment, E I A Report Preparation 10
6 Case Studies: Case studies for 1)BOT 2)Dams 3)Mass Transit System 4)Government
Funded Projects 08

Contribution to Outcomes

Students will have the ability to
1. Explain Indian Infrastructural framework and future challenges.
2. Analyze the infrastructure projects based on various risks.
3. Develop critical thinking on a variety of novel solutions or fixes which aids in execution infrastructure
projects better.
4. Design innovative methods for long lasting infrastructure and understand the successful project delivery
strategies.
5. Analyze the eff ect of infrastructural projects on environment.
6. Apply the design methodologies to the real world case studies


Theory Examination: -

1. The question paper will comprise six questions; each carrying 20 marks.
2. The first question will be compulsory that will have short questions having weightage of 4 -5 marks covering
the entire syllabus.
3. The remaining five questions will be based on all the modules. For this, the module shall be divided
proportionately further, and the weightage of the marks shall b e judiciously awarded in proportion to the
importance of the sub -module and contents thereof.
4. There can be an internal choice in various sub -questions/ questions in order to accommodate the questions
on all the topics/ sub -topics.
5. The students will have to attempt any three questions out of remaining five questions.
6. A total of four questions need to be attempted.


Text Books: -

1. Infrastructure Planning and Management (2018) by Prof. Ashwin Mahalingam NPTEL.
https://nptel.ac.in/courses/105/106/105106188/
2. Projects planning, Analysis Selection, Implementation and Review, Prasanna Chandra Tata McGraw Hill,
New Delhi, 2005
3. Vasant Desai, “Project M anagement”, Himalaya Publishing , 1st Edition, 2010
4. Arbitration”, Jubilee Publications, 2nd Edition., 1996 Engineering Contracts and B. J. Vasavada, “

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38
5. Construction Management & PWD Accounts --- D Lal, S. K. Kataria & Sons, 2012
6. Fundamentals of Engineering Economics —Pravin Kumar, Wiley, India

Recommended Books: -

1. Goodman AS, Hastak M (2006). Infrastructure planning handbook: planning, engineering, and economics.
New York: ASCE Press.
2. Miller R, Lessard DR (2001). The strategic management of large engineerin g projects: Shaping institutions,
risks, and governance. MIT press.
3. J. Parkin and D. Sharma, Infrastructure planning, Thomas Telford, London, 1999.
4. Construction project scheduling and control ----Mubarak, Wiley India
5. Construction Management: Planning and f inance -- Cormican D. Construction press, London, Feb 2002.

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39


University of Mumbai






Syllabus

Honours/Minor Degree Program
in
Smart Cities

FACULTY OF SCIENCE & TECHNOLOGY

(As per AICTE guidelines with effect from the academic year 2022 -2023)


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40

University of Mumbai
Smart Cities
(With effect from 2022 -23)
Year &
Sem
Course Code and
Course Title Teaching
Scheme Hours / Week Examination Scheme and Marks Credit
Scheme
Theory Seminar/
Tutorial Pract Internal
Assess -
ment End
Sem
Exam Term
Work Oral Total Credits

TE
Sem
V HSCC501:
Smart City Planning
and Development 04 -- -- 20 80 -- -- 100 04
Total 04 - -- 100 - - 100 04
Total Credits = 04

TE
Sem
VI HSCC601:
Smart City -Project
Management 04 -- -- 20 80 -- -- 100 04
Total 04 - - 100 - - 100 04
Total Credits = 04


BE
Sem VII HSCC701:
Smart Urban
Infrastructures 04 -- -- 20 80 -- -- 100 04
HSCSBL701: Lab -1:
Smart City -Project
Management -- -- 02 -- -- 50 50 100 02
Total 04 - 04 100 50 50 200 06
Total Credits = 06

BE
Sem
VIII HSCC801: Smart
Management of
Smart Urban
Infrastructures 04 - -- 20 80 -- -- 100 04
Total 04 - - 100 - - 100 04
Total Credits = 04

Total Credits for Semesters V,VI, VII &VIII = 04+04+06+04=18

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41
Smart Cities : Semester V
Course Code Course Name Credits
HSCC501 Smart City Planning and Development 04

Contact Hours Credits Assigned
Theory Practical Tutorial Theory Practical Tutorial Total
4 - - 4 - - 4

Theory Term Work/Practical/Oral
Total Internal Assessment End Sem
Exam Duration of End
Sem Exam Term
Work Pract. Oral
Test -I Test -II Average
20 20 20 80 03 Hrs. - - - 100

Rationale
Today, more than 54% of the world’s total population lives in urban areas. It is projected that urbanization
will continue in the coming years, raising the urban population to 6.0 billion people by 2045. The significant
increase in urban population will put awesome load on urban infrastructure which results in increasing the
demand for energy, mobility, water, and other urban services in cities. So, cities have to become smarter in
provision of urban services. Also due to the global awareness about negative environmental impacts of
pollution, cities are feeling more pressure to improve their environmental performance, while imp roving
their level of services. Increasing demand for sustainable, inclusive, reliable and efficient urban service puts
our urban infrastructures under a huge pressure. But digitalization provides a powerful tool to address these
issues and create a paradi gm shift in our concept of cities. Due to this novel nature of smart cities, it is
important that policymakers, urban managers and other relevant actors be prepared to understand and
address the challenges that the transition will bring about. This course will provide the basic principles that
to consider for a successful transition into a smart city.
Objectives
1. Enable students in understanding the concepts, discourses and practices of “Smart Cities”
across the Globe.
2. To develop competence in planning projects at the city level to ensure sustainability of
environment and human beings.
3. Apply smart technologies across the spectrum of infrastructure and governance.
4. Develop overall city strategy to become contemporary and competitive.
5. Enable students to understand city centric capital formation and finance, risk and feasibility to
ensure the economic health of the city.
6. Develop overall smart cities and villages.

Detailed Syllabus
Module Course Module / Contents Hours
1 Introduction to Smart Cities - 09

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42
1.1 Definition and concept of smart city, Introduction to City planning,
Introduction to Development Control Rules, Building Bye Laws
1.2 Conventional Vs. Smart city, Understanding Smart City
1.3 Various approaches to smart city, Pan city concept
1.4 Challenges of Urbanization, Smart City Characteristics
2 Smart City Standards -
09 2.1 Smart City Planning and Development, Dimensions of Smart Cities
2.2 Government of India initiatives “100 Smart Cities” Policy and Mission
2.3 Global experience of smart cities
2.4 Smart cities –Global standards
2.5 Smart cities -Performance benchmarks
2.6 Smart cities -Practice codes
3 Important sectors of smart city
09 3.1 Various sectors in smart city, Smart building and home device
3.2 Smart water, Smart Transportation, Smart Health, Smart Energy, smart
public service
3.3 Cyber security, Safety and privacy, Concept of smart community
3.4 Concept of Digitalization, brief information about the various tools used
for digitalization such as - ICT, IoT, Sensors, Artificial Intelligence
4 Governance of Smart Cities -E-Governance
09 4.1 Introduction to smart E -Governance, Smart E -Governance for Citizen
services
4.2 Smart E -Governance for Industries and Commerce
4.3 Smart E -Governance within Government
4.4 Envisaging Future Smart E -Governance
4.5 Models for smart Governance
4.6 Regulatory Guidelines and Standards for E -Governance
5 Smart Citizen Services
08 5.1 Smart leadership and strategy; Stakeholder’s engagement
5.2 Smart healthcare
5.3 Smart education, skill development centers, incubation/ Trade
facilitation centers
5.4 Safety and security of citizens particularly women, children and the
elderly people
6 Green Building in Smart Cities and Smart Villages -
08 6.1 Sustainability, smart housing, Green buildings, Rating system of Green
Building
6.2 Energy efficient buildings, Energy Saving System in buildings
6.3 Introduction to Rural Planning and Development, Understanding
Concept of Smart Village, Issues of Smart Village
6.4 Smart Village Performance Benchmark, Smart Village Policy and Mission,
Planning and Management of Smart Village, Financing Smart Village

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43
Contribution to Outcome
On completion of this course, the students will be able to:

1. Conceptualize cities as socio -technical systems
2. Evaluate the main impacts of information and communication technologies on urban
infrastructures and services.
3. Describe the main steps and considerations of the smart city transition.
4. Compare the main managerial and governance challenges of developing and managing a
smart city.
5. Apply such concepts and tools in the case of smart water and smart housing systems.
Internal Assessment 20 Marks
Consisting Two Compulsory Class Tests - First test based on approximately 40% of contents and second test
based on remaining contents (approximately 40% but excluding contents covered in Test I)

End Semester Examination 80 Marks
Weightage of each module in end semester examination will be proportional to number of respective
lecture hours mentioned in the curriculum.
1. Question paper will comprise of total six questions, each carrying 20 marks.
2. Question 1 will be compulsory and should cover maximum contents of the curriculum.
3. Remaining questions will be mixed in nature (for example if Q.2 has part (a) from module
3 then part (b) will be from any module other than module 3).
4. Only Four questions need to be solved.

Reference Books:
1. “Smart Cities Unbundled” by, Sameer Sharma, Bloomsbury Publishing India Pvt. Ltd.
2. “Introduction to Smart Cities” by P.P. Anil Kumar, Pearson Publications
3. “Smart Cities & Urban Development in India “by N. Mani, New Century Publications
4. “Smart City” by Ar un Firodia, Vishwakarma Publications.
5. “The Smart City Transformations: The Revolution of the 21st Century” by Amitabh Satyam & Igor
Calzada, Bloomsbury Publishing India Pvt. Ltd.
6. “Financing Cities in India: Municipal Reforms, Fiscal Accountability and Urb an Infrastructure” by,
Prasanna K. Mohanty, SAGE publications India pvt. Ltd.
7. “Transforming Our Cities: Facing Up To India's Growing Challenge: Postcards of Change”, by Isher
Judge Ahluwalia, Harper Collins publications
8. "Urban Systems Design Creating Sust ainable Smart Cities in the Internet of Things Era”, by Yoshiki
Yamagata, Perry P. J. Yang, Elsevier publications
9. “Internet of Things in Smart Technologies for Sustainable Urban Development” by G. R. Kanaga
chidambaresan, R. Maheswar V. Manikandan, K. Rama krishnan by Springer Publications
10. “Smart Cities: Introducing Digital Innovation to Cities” by Oliver Gassmann, Jonas Böhm, Maximilian
Palmié, Emerald Publications.



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Honours in Smart Cities : Semester V I
Course Code Course Name Credits
HSCC601 Smart City-Project Management 4

Contact Hours Credits Assigned
Theory Practical Tutorial Theory Practical Tutorial Total
4 - - 4 - - 4

Theory Term Work/Practical/Oral
Total Internal Assessment End Sem
Exam Duration of End
Sem Exam Term
Work Pract. Oral
Test -I Test -II Average
20 20 20 80 03 Hrs. - - - 100

Rationale
Smart City projects involve great technical complexity, and require a wide diversity of skills to control and
monitor them. Project Management would be an integral part for smart infrastructure and cities. Like other
complex infrastructure projects; smart city projects are subjected to risk and uncertainties leading to huge time
and cost overrun. Managers are faced with the problem of putting together and directing large temporary
organizations subjected to constrained resources, limited time, and environme ntal uncertainty. Project
management plays an important role in developing the Smart Cities. It has grown in response to the need for a
managerial approach that deals with the problems and opportunities of modern society. It provides the technical
and mana gerial competency, communication and decision making necessary to meet the challenges of complex
activities. Application of modern project management tools would ensure more collaboration, communication
flow and much flawless implementation of Smart City p rojects. Modern project management concepts of
application of Integrated Project Delivery (IPD) and Building Information Modeling (BIM) would reduce the co -
ordination problems and ensure much higher probability of successful completion of the projects with in
stipulated time and cost frame

Objectives

1. This course is designed to give exposure to project management tools and techniques applicable for
planning, controlling and monitoring of Smart Infrastructure and Cities.
2. This course would also enable to develop insight for managing project risks, uncertainties and
complexities of smart city projects.
3. To provide overview on sound disaster risk management practices for preparing towards “Safe Cities”.
To educate and sensitize students, government officers, planners, policy makers, academician,
researchers and others on process of disaster management in smart cities.
4. To educate participants on various tools and methods that can be adopted for hazard identification,
vulnerability analysis and disaster risk re duction measures.
5. To stimulate thought process to address hazard risks and vulnerabilities of distinct groups within the
city to make more resilient communities.
6. To stimulate process of critically analyzing risks to various urban sectors like Health, Tra nsport,
Communication, Housing, Services, Infrastructure etc to come up with strategy to reduce risks
Researchers and Academicians.

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45

Detailed Syllabus
Module Course Module / Contents Hours
1 Name of Module 1: Philosophy and Concepts of Project Management in smart cities -
08 1.1 Philosophy and Concepts of Project Management -Phases
1.2 Philosophy and Concepts of Project Management - Stages of Project -
1.3 Philosophy and Concepts of Project Management -Approval Status
1.4 Philosophy and Concepts of Project Management -Work Break down Structure
2 Name of Module 2: Project Organization Structure -
08 2.1 Project Organization Structure - Planning
2.2 Project Organization Structure - Scheduling
2.3 Project Organization Structure -Controlling
2.4 Project Organization Structure -CPM
2.5 Project Organization Structure -The PERT Model
2.6 Project Management using BIM
3 Name of Module 3: Project Cost Analysis
09 3.1 Project Cost Analysis
3.2 Updating a Project
3.3 Resource Allocation and Leveling
3.4 Line of Balance Technique
4 Name of Module 4: Smart City Project Management with Case Studies -
09 4.1 Smart Project Planning
4.2 Smart Project Scheduling
4.3 Smart Project Monitoring
4.4 Smart Project Controlling
4.5 Project Risk Management
4.6 Case Studies on Smart Cities
5 Name of Module 5: Safety, Security and Disaster Management for Smart Citizen -
09 5.1 Safety, Security and Disaster Management for Smart Citizen
5.2 Disaster Risk Reduction (DRR) Overview
5.3 Smart Cities and Disaster Management
5.4 DRR Framework for Smart Cities
6 Name of Module 6: Thematic Analysis and Resilience Strategy for Smart Cities -
09
6.1 Thematic Analysis, Infrastructure Data/Digital Services

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6.2 Data Management and Analytics
6.3 Resilience Strategy for Smart Cities
6.4 Stakeholder Capacity Building, Self -Assessment at project and city level

On completion of this course, the students will be able to:

1. Explain role of project management in developing the Smart Cities.
2. Evaluate the risk and uncertainties throughout all the phases of Smart City projects.
3. Compare application of modern project management tools for flawless implementation of smart
city projects.
4. Evaluate the managerial approach that deals with the problems and opportunities challenges of
modern society of developing and managing a smart city.
5. Apply such concepts and tools for smart infrastructure and cities.

Internal Assessment 20 Marks
Consisting Two Compulsory Class Tests - First test based on approximately 40% of contents and second test
based on remaining contents (approximately 40% but excluding contents covered in Test I)

End Semester Examination 80 Marks
Weightage of each module in end semester examination will be proportional to number of respective lecture
hours mentioned in the curriculum.
1 Question paper will comprise of total six questions, each carrying 20 marks.
2 Question 1 will be compulsory and should cover maximum contents of the curriculum.
3 Remaining questions will be mixed in nature (for example if Q.2 has part (a) from module 3 then part
(b) will be from any module other than module 3).
4 Only four questions need to be solved.

Reference Books:
1. Principles of Sustainable Project Management” by Mohamed Salama, Goodfellow Publishers
2. “Smart Cit ies Unbundled” by Sameer Sharma , Bloomsbury Publishing India Pvt. Ltd.
3. “Introduction to Smart Cities” by P.P. Anilkumar, Pearson Publications
4. “Smart Cities & Urban Develop ment in India” by N. Mani, New Century Publications
5. “Smart City” by Arun Firodia, Vishwakarma Publications
6. “The Smart City Transformations: The Revolution of the 21st Century” by Amitabh Satyam & Igor Calzada,
Bloomsbury Publishing India Pvt. Ltd.
7. “Financing Cities in India: Municipal Reforms, Fiscal Accountability and Urban Infrastructure” by,
Prasanna K. Mohanty, SAGE publications India pvt. Ltd.
8. “Transforming Our Cities: Facing Up To India's Growing Challenge: Postcards of Change”, by Isher Jud ge
Ahluwalia, Harper Collins publications
9. Smart City Tech Planning Handbook by Wade Sarver
10. https://www.projectsmart.co.uk/project -management -ebooks.php

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Smart Cities : Semester VII
Course Code Course Name Credits
HSCC701 Smart Urban Infrastructures 04

Contact Hours Credits Assigned
Theory Practical Tutorial Theory Practical Tutorial Total
4 - 4 - 4

Theory Term Work/Practical/Oral
Total Internal Assessment End Sem
Exam Duration of End
Sem Exam Term
Work Pract. Oral
Test -I Test -II Average
20 20 20 80 03 Hrs. - 100

Rationale
The smart city infrastructure is the introductory step for establishing the overall smart city framework and
architecture. The scope of these cities is mainly limited to construct a technology park converting the industrial
real estate to state -of-the-art information technology using the evolution in the telecom and IP networks including
insignificant asset management automation system. Urbanization is not only associated with economic
development but over the time it started aspiring people to better quali ty of life. Cities are seen as solutions for
boosting economy, generating employment, creating skills, providing better health services and many more
things. However, the state of urban service delivery in India’s cities and towns is far poorer than is des irable for
India’s current income levels. Considering that the Indian economy has been one of the fastest growing economies
in the world for some time, and aspirations and standards are raising, the current state of service delivery is simply
unacceptable. Moreover, a successful city cannot operate efficiently in isolation from its environment. It must
balance social, economic and environmental needs. Smart Cities focus on their most pressing needs and on the
greatest opportunities to improve lives. They ta p a range of approaches – digital and information technologies,
urban planning best practices, public private partnerships, and policy change to make a difference.
Objectives
1. To study application of Solar Energy for Smart Cities -Conventional vs. Smart City
2. To prepare the qualified resource persons for the upcoming specialization in solid waste management
practices after the mission period of SBM i.e., after 2020.
3. To learn from the challenges and limitations faced in e -governance projects in Citizen Services delivery,
industries and commerce and intra -government systems for efficiency and transparency.
4. To develop ability to conceptualize, design, implement and mana ge the new era smart e -governance
projects.
5. An understanding of the urban water supply and sanitation systems and linkages with urban forms.
6. Understanding the fundamentals of large project financing -Financial markets for smart city project finance
such as syndicated bank loans, capital markets, private equity fund, multilateral institutions, joint ventures,
public -private -partnership (PPP)
7. Understanding the projects and their business risks.
8. Understanding the documentation used to structure individual la rge project financings.

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Detailed Syllabus
Module Course Module / Contents Hours
1 Conceptualization of Smart Energy System for Smart city:
08 1.1 Application of Solar Energy for Smart Cities, Conventional vs. Smart City, Green
approach to meet Energy demand, Energy scenarios of conventional cities,
Energy Efficient Building
1.2 Meeting energy demand through direct and indirect solar resources, Efficiency of
indirect solar resources and its utility, Structure of Smart Grid, Indian Perspective,
Advantage and limitation
1.3 Renewable in Smart grid Structural concept, Specific applications, Perspective in
Smart Cities
1.4 Application of Solar in mobility, Matching demand and supply of energy in typical
Smart city through Green mobility
2 Smart Water Management in Smart Cities -
10 2.1 Introduction to water Bye -Laws
2.2 Details of Water Supply system, various stages in implementing the system
2.3 Planning Stage: Conversion of existing maps to GIS
2.4 Assessing earlier population forecast, Demand estimation
2.5 Validation of ground elevations
2.6 Design Stage: Hydraulic model of distribution system
3 Solid Waste Management in Smart Cities
09 3.1 Introduction to an effective urban Solid Waste Management (SWM) with 5Rs,
MSW Characteristics and Quantities, MSW Rules 2016, Swachh Bharat Mission
and Smart Cities Program
3.2 Disposal of Municipal Solid Waste: Landfill, Biochemical Processes and
Composting, Energy Recovery from Municipal Solid Waste, case study of any
Smart Cities in the Country
3.3 Construction and Demolition (C&D) Waste Management - Overview, Regulation,
Beneficial Reuse of C&D Waste Materials, E -Waste Management Issues &
Challenges and Status in India, E -Waste Management Rules 2016 and
Management

3.4 Critical examinations of SBM endeavor with special emphasis on clean city
rankings along with case study on solid waste management
4 Smart Transportation in Smart Cities -
08 4.1 Introduction of “Smart Transport”
4.2 Application of traffic engineering to smart cities: Level of service, Traffic system
management, reduction of conflicts, signal design
4.3 Smart pavement materials: plastic pavement, porous pavement, electric
generating roads (Piezo electric roads) etc.
4.4 Introduction to Urban Transportation system planning: Trip Generation,
distribution
4.5 Modal split and traffic assignment

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4.6 Highway economics
5 Smart sanitation and storm water drainage system for Smart city -
09 5.1 Crisis of Sanitation - India, Key Sanitation policy issues and goals, Benchmarks for
Smart Sewerage and Sanitation, steps required to achieve these benchmarks
5.2 Need of sewer model, Assessment of sewerage system at Planning and Design
stage for transforming into smart sanitation
5.3 Sludge Management, Wastewater Reuse and Recycling. Need of Storm water
drainage system, Storm water Planning, Challenges in Sustainable Storm water
Planning
5.4 Trends and issues in storm water system Storm water management to for
sustainable water management in Indian smart cities
6 Smart Funding for Smart Cities -
08 6.1 Financing Smart Cities Development -Types of sources for sustainable smart city
funding: GOI seed capital grant of Rs 500 crore to each smart city, Leveraging this
grant for funding from open sources, Business Risk Assessment, Public Private
Partnership PPP concept and Modes of Smart City funding -BOOT, BOT, BOO,
DBFOT etc.
6.2 PPP Request for Qualification (RFQ) and Criteria as per Planning Commission
guidelines (Case Study), PPP request for Proposal (RFP) along with Concession
agreement terms and conditions as per Planning Commission Guidelines
6.3 Debt funding, Consortium of financiers, Guarantees and mortgage, Joint venture ,
Municipal Bonds, Documentation of debt funding, Equity Funding through Initial
Public Offer
6.4 Private equity funding and risk factors in IPO, Procedure of IPO funding, Other
funding sources like Viability gap funding, Special subsidy for the project, Merger
and Acquisition, Long term Lease, Financing etc.

Contribution to Outco me
Conceptualize on completion of this course, the students will be able to:
1. Smart Energy System required for Smart city.
2. Explain the effective urban Solid Waste Management practices, MSW rules.
3. Evaluate the importance of best sanitation practices, storm water management and its linkage for the smart
city transition.
4. Describe the evolution of e -governance and smart public services to be provided for developing and managing
a smart city.
5. Evaluate application of traffic engineering to smart cities
Internal Assessment 20 Marks
Consisting Two Compulsory Class Tests - First test based on approximately 40% of contents and second test
based on remaining contents (approximately 40% but excluding contents covered in Test I)
End Semester Examination 80 Marks
Weightage of each module in end semester examination will be proportional to number of respective lecture
hours mentioned in the curriculum.
1. Question paper will comprise of total six questions, each carrying 20 marks.

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2. Question 1 will be compulsory and should cover maximum contents of the curriculum.
3. Remaining questions will be mixed in nature (for example if Q.2 has part (a) from module 3 then part (b)
will be from any module other than module 3).
4. Only Four questions need to be solved.

Recommended Books:
1. “Water, Wastewater, and Stormwater Infrastructure Management”, by Neil S. Grigg, CRC Press Taylor
and Francis Group
2. “Smart Cities Unbundled” by Sameer Sharma, Bloomsbury Publishing India Pvt. Ltd.
3. “Introduction to Smart Cities” by P.P. Anilkumar, Pearson Publications
4. “Smart Cities & Urban Development in India” by N. Mani, New Century Publications
5. “Smart City” by Arun Firodia, Vishwakarma Publications
6. “Municipal Stormwater Management” by Debo, Thomas, Reese, Andrew, Lewis Publishers
7. “State of the Capital: Creating a Truly Smart City”, by K.S. Mehra, Rupa Publications India
8. Security in Smart Cities: Models, Applications, and Challenges”, by Aboul Ella Hassanien Mohamed
Elhoseny , Syed Hassan Ahmed, Amit Kumar Singh Published by Springer
9. “Transportation and Power Grid in Smart Cities: Communication Networks and Services” by Me like Erol -
Kantarci, Huss ein T. Mouftah , Mubashir Husain Rehmani , Wiley Publications
10. Cities and Mobility & Transportation: Towards the next generation of Urban Mobility by Pascual Berrone,
Joan EnricRicart Costa , Ana Duch T -Figueras, IESE CITIES IN MOTION: International.





























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Smart Cities : Semester V II
Course Code Course Name Credits
Lab 1: HSCSBL701 Smart City -Project Management 02

Contact Hours Credits Assigned
Theory Practical Tutorial Theory Practical Tutorial Total
- 04 - - 02 02

Theory Term Work/Practical/Oral
Total Internal Assessment End Sem
Exam Duration
of End Sem
Exam Term
Work Pract. Oral
Test -I Test -II Average
- - - - - 50 - 50 100

Rationale
Smart City projects involve great technical complexity. It requires a widespread diversity of skills to control and
monitor them. For any smart infrastructure project management would be an integral part. Like other complex
infrastructure projects; smart city projects are subjected to risk and unce rtainties leading to huge time and
cost overrun. Project managers are faced with many problems that are putting together subjected to
constrained resources, finance, time, and environmental uncertainty. Therefore, project management plays an
important role in the development of the Smart Cities. It provides the technical and managerial competency,
communication and decision making necessary to meet the challenges of complex activities. It has grown in
response to the need for a managerial approach that deal s with the problems and opportunities of modern
society. A successful city operates efficiently only when it balances social, economic and environmental needs.
Smart Cities focus on their most demanding needs to improve lives. They tap various approaches like digital
and information technologies, urban planning best practices, public private partnerships, capacity building,
policy change to achieve the success.

Course Objective:


1. To acquire knowledge on various components of Smart Cities.
2. To study ongoing projects and their business risks
3. To understand documentation, financings, capacity building used to structure individual large project
4. To study urban water supply, sanitation, solid waste management, transportation & application of
Solar Energy for Smart Cities
List of Experiments (Conduct three practi cal out of six practical’s mentioned below)
Module Detailed Content Lab
Session /
Hours . Rationale

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1 Preparing a report on Project Management -Phases -Stages of project -Work
Break down Structure of Smart city in India (Ongoing Smart City Project -Case
study). 08
2 Preparing a report of Project Cost Analysis -Resource Allocation and Leveling,
Line of Balance Technique (Ongoing Smart City Case Study). 08
3 Preparing a report on Smart Energy System for Smart city (Ongoing Smart City -
Case Study). 08
4 Preparing a report on Smart Water Management in Smart Cities (Ongoing
Smart City -Case Study). 08
5 Preparing a report on Solid Waste Management in Smart Cities (Ongoing Smart
City-Case Study). 08
6 Preparing a report on Smart Transportation in Smart Cities (Ongoing Smart
City-Case Study).
08


Course Outcomes:

At the end of the course, learner will be able to:
1. Compare various stages of project of smart city.
2. Evaluate the effective urban Solid Waste Management practices, MSW rules.
3. Compare the importance smart water management, best sanitation practices, storm water
management and its linkage for the smart city transition.
4. Prepare application of traffic engineering to smart cities
Assessment:
• Term Work Including Laboratory Work and neatly written project report of the work done.
Laboratory Work: 50 Marks
• End Semester Oral Examination: 50 Marks

Recommended Books:
1. Manual on Water Supply and Treatment, (latest Ed.): Ministry of Urban Development, New Delhi
2. Manual on Wastewater Treatment 3rd Ed. Pub: CPHEEO, Ministry of Urban Development, Govt. of
India, New Delhi,
3. Municipal Solid Waste Management Manual, (Part1,2,3) Ministry of Urban Development, CPHEEO,
2016
4. Refer various websites of municipal corporations of the cities selected under the smart city mission to
study success story,
5. Refer following official government websites
 http ://cpheeo.gov.in
 https://moef.gov.in/en/


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Smart Cities : Semester V III
Course Code Course Name Credits
HSCC801 Smart Management of Smart Urban Infrastructures 04

Contact Hours Credits Assigned
Theory Practical Tutorial Theory Practical Tutorial Total
4 - - 4 - - 4

Theory Term Work/Practical/Oral
Total Internal Assessment End Sem
Exam Duration of End
Sem Exam Term
Work Pract. Oral
Test -I Test -II Average
20 20 20 80 03 Hours - - - 100

Rationale
The introduction of Smart urban technologies into legacy infrastructures has resulted in numerous challenges
and opportunities for contemporary cities and will continue to do so. Over the past few years, advances in the
Information and Communica tion Technologies (ICTs) have significantly challenged the traditionally stable
landscape of urban infrastructure service provision. This has resulted in increasing interest from both
technology vendors and public authorities in the transition of cities to wards so -called “Smart Cities”. Although
such “Smart technologies” can provide immense opportunities for citizens and service providers alike, the ICTs
often act as disruptive innovators of urban infrastructure service provision.
Objectives

1. Enable students to develop competence in planning of projects at the city level to ensure sustainability
of environment and humans
2. Enable students to apply smart technologies across the spectrum of infrastructure and governance
3. Enable students to develop overall city strategy to become contemporary and competitive
4. Enable students to understand city centric capital formation and finance, risk and feasibility to ensure
the economic health of the city

Detailed Syllabus
Module Course Module / Contents Hours
1 Management of Smart Urban Infrastructures
08
1.1 Issues and Challenges in Construction and Maintenance of Infrastructure,
Information Technology and Systems for Successful Infrastructure
Management

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1.2 Innovative Design and Maintenance of Infrastructure Facilities, Infrastructure
Modeling and Life Cycle Analysis Techniques
1.3 Capacity Building and Improving the Governments Role in Infrastructure
Implementation
1.4 An Integrated Framework for Successful Infrastructure Planning and
Management, Infrastructure Management Systems and Future Directions
2 Management of Smart water, Wastewater System -
10 2.1 Overview of Urban Water Supply, Rainwater Harvesting, Dual water supply
system, water recycling
2.2 Building blocks of 24x7 water supply system,
2.3 Performance indicator and Benchmark for water supply services
2.4 Smart metering, Leakage management & NRW reduction for achieving 24x7
water supply
2.5 Smart monitoring through SCADA system for various components of water
and sewerage system
2.6 Redressal of complaints on real time basis, Current Practices in Wastewater
Recycling
3 Management of Smart Urban Energy Systems
08 3.1 Meaning of ‘Smart Energy Management
3.2 Smart Energy Management – Water, Transport
3.3 Smart Energy Management -Waste Management and Public Services etc
3.4 Challenges and Implementation Barriers for Smart Energy Management, Way
forward for achieving integrated Smart Energy Management
4 Management of Smart Solid Waste System -
10 4.1 The environmental impact of waste management and its relationship on the
sustainable development and smart city development
4.2 Management of Solid Waste using IoT
4.3 management issues in source reduction, recycling, material recovery and
transformation of waste through composting
4.4 Implementation of solid waste management options -collection system,
energy recovery and landfill disposal.
4.5 Biomedical waste management, Economy and financial aspects of solid waste
management.
4.6 Case Studies of Smart cities having successful solid waste Management
program
5 Name of Module 5: Management of Smart Urban Transportation Systems
08 5.1 Introduction of “Smart Transport”, Smart Automobile and Sustainable fuels
5.2 Smart infrastructure -Intelligent Transport systems (ITS), GIS, RS, GPS,
Navigation and Identification Systems
5.3 Electronic fee payment technology (E -ticketing), Traffic Safety Management

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5.4 Human and Environmental Impacts, Safety and Sustainability, Case Study:
BRTS or Smart Parking with economics and costing, Mobility Services, Smart
Mobility
6 Case Study Towards Smart Cities: Part I & II
08 6.1 Towards Smart Cities: Part I: (0 4 hours)
The transition of legacy cities to Smart Cities is not a spontaneous process. To
get the transition process right, and to the benefit of citizens, cities have to
adopt effective management and governance approaches to successfully deal
with numerous complexities of this process. This Mod ule will help to
understand the most important factors in the transition phase of legacy cities
to smart cities an d their managerial implications
6.2

Towards Smart Cities: Part II: ( 04 hours)
Management of Smart Cities calls for different approaches from conventional
urban management approaches, Role of city government in the network of
actors who play an important role in management of clean, safe, healthy living
conditions. Modern, efficient infrastructure that enables and promotes high -
quality work opportunities and high -quality living, Efficient and sustainable
use of resources, The city challenges such as city master plans, long term
urban plans, city mobility plans, city strategic plans for renewable energy,
water sources, waste management, prici ng on water, power, tax assessment
and frequent revisions, appropriation of resources, water harvesting and
recycling, public participatory approach, citizen participation, citizen audit,
capacity building in key disciplines, effective urban governance, ad option of
ICT facilities, in due respect to local and regional culture, social aspects, safety
and security based on economical vibrancy -Smart Cities -Internet of Things
(IoT) and Artificial Intelligence (AI).


Contribution to Outcome
On completion of this course, the students will be able to:
1. Explain how to make the best of these smart technologies in your cities’ legacy infrastructures.
2. Learn about state -of-the-art strategies for effectively managing the transition from legacy infrastructures
to smar t urban systems.
3. Evaluate Life Cycle Analysis Techniques and sustainable development of Infrastructure.
4. Describe principles for the management of Smart urban infrastructures as well as the applications of
these principles in the various sectors.
Internal Assessment 20 Marks
Consisting Two Compulsory Class Tests - First test based on approximately 40% of contents and second test
based on remaining contents (approximately 40% but excluding contents covered in Test I)

End Semester Examination 80 Marks
Weightage of each module in end semester examination will be proportional to number of respective lecture
hours mentioned in the curriculum.

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56
1. Question paper will comprise of total six questions, each carrying 20 marks.
2. Question 1 will be compulsory and should cover maximum contents of the curriculum.
3. Remaining questions will be mixed in nature (for example if Q.2 has part (a) from module 3 then part
(b) will be from any module other than module 3).
4. Only Four questions need to be solved.

Recommended Bo oks:
1. Integrated Solid Waste management, George Tchobanoglous, Hilary Theisen and Samuel A Vigil Tata
McGraw Hill
2. “Smart Cities Unbundled” by Sameer Sharma, Bloomsbury Publishing India Pvt. Ltd.
3. “Introduction to Smart Cities” by P.P. Anilkumar , Pearson Publications
4. “Smart Cities & Urban Development in India”by N. Mani, New Century Publications
5. “Smart City” by Arun Firodia, Vishwakarma Publications
6. “The Smart City Transformations: The Revolution of the 21st Century” by Amitabh Satyam & Igor
Calzada, Bloomsbury Publishing India Pvt. Ltd.
7. “Financing Cities in India: Municipal Reforms, Fiscal Accountability and Urban Infrastructure” by,
Prasanna K. Mohanty, SAGE publications India pvt. Ltd.
8. “Transforming Our Cities: Facing Up To India's Growing C hallenge: Postcards of Change”, by Isher
Judge Ahluwalia, Harper Collins publications
9. “Urban Systems Design Creating Sustainable Smart Cities in the Internet of Things Era”, by Yoshiki
Yamagata, Perry P. J. Yang, Elsevier publications
10. “Internet of Things in Smart Technologies for Sustainable Urban Development” by G. R. Kanaga
chidambaresan, R. Maheswar V. Manikandan, K. Ramakrishnan by Springer Publications
11. “Smart Cities: Introducing Digital Innovation to Cities” by Oliver Gassmann, Jonas Bohm, Maximilian
Palmie, emerald Publications


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University of Mumbai





Syllabus

Honours /Minor Degree Program
In
Waterways Transportation Engineering


FACULTY OF SCIENCE & TECHNOLOGY

(As per AICTE guidelines with effect from the academic year 2022 -2023)

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58




BE
Sem.
VIII
HWTC801:
Construction and
Management of
Port and Harbour 04 - -- 20 80 -- -- 100 04
Total 04 - - 100 - - 100 04
Total Credits = 04

TE
Sem.
VI HWTC601:
Design of Ports and
Harbour structures 04 -- -- 20 80 -- -- 100 04
Total 04 - - 100 - - 100 04
Total Credits = 04


BE
Sem.
VII HWTC701:
Port and Harbour
Operations and
Services 04 -- -- 20 80 -- -- 100 04
HWTSBL701: Lab -1
-- -- 04 -- -- 50 50 100 02
Total 04 - 04 100 50 50 200 06
Total Credits = 06 University of Mumbai
Waterways Transportation Engineering
(With effect from 2022 -23)
Year
&
Sem
Course Code
and Course
Title Teaching
Scheme Hours / Week Examination Scheme and Marks Credit
Scheme
Theory Seminar/Tutorial Pract Internal
Assess
ment End
Sem
Exam Term
Work Oral Total Credits

TE
Sem
V HWTC501:
Waterways and
Ports 04 -- -- 20 80 -- -- 100 04
Total 04 - -- 100 - - 100 04
Total Credits = 04

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59
Waterways Transportation Engineering : Semest er V
Course Code Course Name Credits
HWTC501 Waterways and Ports 04

Contact Hours Credits Assigned
Theory Practical Tutorial Theory Practical Tutorial Total
4 - - 4 - - 4

Theory Term Work/Practical/Oral
Total Internal Assessment End
Sem
Exam Duration of
End Sem Exam Term
Work Pract. Oral
Test -I Test -II Average
20 20 20 80 03 Hrs. - - - 100
Rationale
Waterways are critically important to the transportation of people and goods throughout the world.
The complex network of connections between coastal ports, inland ports, rail, air, and truck routes
forms a foundation of material economic wealth worldwide. This subject introduces the basic
elements related to waterway engineering.

Objectives

 To understand the historical development of waterways at a national and global level and also the
significance of ports and harbours as a mode of transport.
 To understand the present status and different surveys required for the planning of Ports and
Harbours.
 To understand the policies related to water transportation in India.
 To understand the natural phenomenon affecting waterways and its elements.
 To unde rstand the coastal protection works and coastal Regulations to be adopted
 To study and understand all the important facilities required at the p ort for the efficient planning of
port.

Detailed Syllabus
Module Contents Hours
1 General: Comparison of different modes of transportation. Types, Characteristics, advantages
and disadvantages of water transportation. History of water transportation at world level and
at national level. Case studies of countries with excellent water transportation facilities. 04
2 Historical development and Harbour planning: Development and policies related to water
transportation in India. Status of river, canal and ocean transportation in India. Classification
of harbours, Requirement of Harbour. Harbour components, ship ch aracteristics, 12

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characteristics of good harbour and principles of harbour planning, size of harbour, site
selection criteria and layout of harbours. Surveys to be carried out for harbour planning
Marine surveys, Topographic survey of marine area. Hydro grap hic surveys, Tide Surveys.
3 Port development and planning : Port building facilities. Differences between Port, Docks and
Harbour. Requirement of a good port, Port development in India, Major ports in India.
Maritime policies, Port authorities, bodies and associations. Port modernization and new port
development (Sagarmala project). Connectivity enhancement Port -linked
industrialization and Coastal community development and development of river information
services. Environment Impact Statement (EIS). A pprovals and mitigation .Case studies of
various available Ports in India and abroad. 10
4 Natural Phenomena: Wind, waves, tide formation and currents phenomena, their generation
characteristics and effects on marine structures. Wind strength, water waves , origin of water
waves, effect of wind duration, and bottom friction and water depth on water waves. Wave
form and generation. Velocity, height and length of waves. Diffraction, breaking and reflection
of waves, wave action on vertical walls, piles. Beach protection, literal drift, silting, erosion
and littoral drift. 12
5 Coastal Structures : Piers, Break waters, Wharves, Jetties, Quays, Spring Fenders, Dolphins and
Floating Landing Stage Types, Objective, principal function and suitability. 06
6 Harbour Terminal facilities and Navigational Aids :
Port building facilities, Transit sheds, Warehouses, Cargo handling facility, Services for
shipping terminals , Inland port facilities planning, purpose and general description. Necessity
of navigation aids and t heir types, Requirement of signals, Fixed and floating navigation aid. 08

Contribution to Outcomes

After completion of the course work, the students are expected to
1. Develop a strong fundamental s related to waterways transportation Engineering.
2. Understand the present status and different surveys required for the planning of Ports
and Harbours.
3. The students shall be in a commanding position to plan and execute hydrographic surveys
required at various stages of planning, construction and execution of Port and harbours.
Also understand the policies related to water transportation in India.
4. The student will also be able to understand the role and effect of natural phenomenon
such as wind and waves on the waterways.
5. Understand the coastal protection works and coastal Regulations to be adopted.
6. The student is expected to get full knowledge related to all the modern techniques and
various important methods for effective management of port facilities.

Internal Assessment (20 Marks)

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61
Consisting Two Compulsory Class Tests - First test based on approximately 40% of contents and
second test based on remaining contents (approximately 40% but excluding contents covered in
Test I)

End Semester Examination (80 Marks)
Weightage of each module in end semester examination will be proportional to number of
respective lecture hours mentioned in the curriculum.
1 Question paper will comprise of total six questions, each carrying 20 marks.
2 Question 1 will be compulsory and should cover maximum contents of the curriculum.
3 Remaining questions will be mixed in nature (for example if Q.2 has part (a) from module
3 then part (b) will be from any module other than module 3).
4 Only Four questions need to be solved.

Recommended Books: -
1. Docks and Harbour Engineering: Dr. S.P Bindra , Dhanpatrai Publications, India
2. Docks and Harbour Engineering: Hasmukh P. Oza, Gautam H. Oza, Charotar Publication, India
3. Harbour, Dock and Tunnel Engineering: R. Srinivasan , Charotar Publication, India
4. Alonzo Def. Quinn, Design and Construction of Ports and Marine Structure, McGraw – Hill Book
Company, New York.
5. PeraBrunn, “Port Engineering”, 1 st Edition, Gulf Publishing Company, 2000.
6. Leslie A.Bryan , “Principles of Water Transportation”, University of Chicago Press










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Waterways Transportation Engineering : Semester VI
Course Code Course Name Credits
HWTC601 Design of Ports and Harbour structures 04

Contact Hours Credits Assigned
Theory Practical Tutorial Theory Practical Tutorial Total
4 - - 4 - - 4

Theory Term Work/Practical/Oral
Total Internal Assessment End Sem
Exam Duration of End
Sem Exam Term
Work Pract. Oral
Test -I Test -II Average
20 20 20 80 03 Hrs. - - - 100


In the subject of Transportation Engineering, study of Harbour, Dock and Port Engineering is essential. This course
is designed to give the basic understanding of ports and harbour structures. The course will also cover wide areas
such as vessel types, t ypes of harbours, design of entrance channel, turning circle, breakwaters, berthing
structures etc. A key feature of this course is to introduce the international practice and technologies in fields of
coastal, ports and harbour including the codal require ments for designing the various components of port and
harbour structures.
Objectives

1. To make the students understand the basic principles of design of port and harbour structures.
2. To cover the design aspects of areas such as vessel types, types of ha rbours, design of entrance channel,
turning circle, breakwaters, berthing structures etc.
3. To understand the importance of load consideration and will enable the students to calculate the different
loads in designing the various components.
4. To introduce the international practices and construction technologies in order to design the foundation
and fenders of ports and harbour.
5. To appreciate the design principles and codal requirements for designing a breakwater with the help of
model studies.
6. To enable the s tudents in understanding the concept, types and differences of docks and locks in order to
navigate safely.

Detailed Syllabus
Module Content Hours
1 Introduction: Ports and harbours – an infrastructure layer between two transport
media. Introduction to navigation channel, entrance channel and turning circle. 08 Rationale

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Design issues: Sea port layout with regards to - wave action - siltation - navigability,
berthing facilities. -Vessel type and si ze
2 Wind rose and wave rose as per IS 4651, Operational and design wave as per return
period, seismic, sidescan and bathymetry charts 08
3 Load consideration and calculations: Environmental Loads : Wind, Currents, Waves.
Mooring Loads: Mooring Lines Arrangement, Mooring Line Materials, Mooring
Forces.
Loads From Cargo Handling and Hauling Equipment and Uniform Distributed Loads.
Design Load Assumptions, Uniform Distributed Cargo Loads and Miscellaneous Live
Loads, Rubber Tire and Crawler Track Mounted Equipment, Rail -Mounted Cargo,
Fixed -Base Equipment, Ship Impact. 12
4 Foundation Design: Vertical Loads on Piles or Piers Due to Changes in Water Level
Ice Load of Thermal Origin, Other Ice -Induced Loads
design methodology for pier , girder, slab, foundations and fenders - codes and
standards 10
5 Design of breakwater and physical model studies on stability. Introduction to effect
of breakwater on shoreline, dredging and disposal 06
6 Docks and Locks: Tidal basin, wet docks -purpose, design consideration, operation of
lock gates and passage, repair docks - graving docks, floating docks 08
Total 52



After successful completion of the course the students shall be able to
1. Understand the different terminologies and components of port and harbour and will enable the
students to understand the design issues.
2. Embrace the concept and principle behind load consideration and will eable the students to
determine the different loads as well.
3. Desi gn the foundation of different structures of ports and harbour and explore the codal
requirements while designing.
4. Understand the concept of breakwater and will enable the students to design a breakwater.
5. Discuss the various international practices and mo dern construction technologies introduced in
ports and harbour in order to design the foundation and fenders.
6. Understand the purpose of docks and locks with the major differences between them.

Internal Assessment (20 Marks)
Consisting Two Compulsory Class Tests - First test based on approximately 40% of contents and second
test based on remaining contents (approximately 40% but excluding contents covered in Test I)

End Semester Examination (80 Marks)
Weightage of each module in end semester examination will be proportional to number of respective
lecture hours mentioned in the curriculum.
1 Question paper will comprise of total six questions, each carrying 20 marks. Contribution to Outcomes

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2 Question 1 will be compulsory and should cover maximum contents of the curriculum.
3 Remaining questions will be mixed in nature (for example if Q.2 has part (a) from module 3 then
part (b) will be from any module other than module 3).
4 Only Four questions need to be solved.
References:

1. Port Design - Guidelines and recommendations by C. A. Thoresen, Tapir Publications.
2. Design of Marine Facilities for the Berthing, Mooring and Repair of Vessels by J. W. Gaythwaite, Van
Nostrand.
3. Handbook of Offshore Engineering by S.K. Chakrabarti, Elsevi ers, 2005.
4. Agerschou, H., Lundgren, H., Sorensen, T., Ernst, T., Korsgaard, J., Schmidt, L.R. and Chi, W.K., (1983).
“Planning and Design of Ports and Marine Terminals”, A Wiley -Interscience Publication.
5. Per brun (1983). “Port Engineering” Gulf Publishing Co.
6. Docks and Harbour Engineering: Bindra, S. P.; Dhanpat Rai and Sons, New Delhi.
7. Harbour, Dock and Tunnel Engineering: Shrinivas, R.; Charotar Publishing House, Anand
8. Design and Construction of Ports and Marine Structures: Quinn, A. D., Tata Mc -Graw Hil l India Publishing
House

Additional Reading
IS-4651 Indian standard Code of practice for planning and design of ports and harbour, Bureau of Indian
Standards, New Delhi.











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Waterways Transportation Engineering : Semester VII
Course Code Course Name Credits
HWTC701 Port and Harbour Operations and Services 04

Contact Hours Credits Assigned
Theory Practical Tutorial Theory Practical Tutorial Total
4 - - 4 - - 4

Theory Term Work/Practical/Oral
Total Internal Assessment End Sem
Exam Duration of End
Sem Exam Term
Work Pract. Oral
Test -I Test -II Average
20 20 20 80 03 Hrs. - - - 100

Rationale
Today 80% of the world's cargo is being transported by waterways. The boom in e -commerce has led to the
thinning of borders between countries and goods being exchanged seamlessly. Thus, ports have become the
bedrock of todays' global economy and India is no exception. Thus it’s imperative for students to understand
how seaport operates and apply the best practices along with the latest industrial developments. This course
is designed in line with the contemporary developments. The syllabus covers global port management
practices at the regulatory, commercial, technological, operational and financial levels. The shipping industry
has myr iad complexities and the syllabus provides students wide -ranging and up -to-date understanding
required to thrive in today’s highly competitive and evolving environment.
Objectives
1. To study History of Ports, its evolution, Governance and Ownership structure.
2. To Understand different types of logistic integration, Port operations and services.
3. To study planning of vessel movements and improvement of Port capacity.
4. To study the different types of International agreements which are the tools for growth in Indian ports.
5. To study and analyze traffic forecasting in order to plan the port operations effectively.
6. To study port authorities and regulatory framework

Detailed Syllabus
Module Course Module / Contents Hours
1 Introduction
08 1.1 The History of Ports: Ports history, Planning, and Development.
1.2 Port Ownership, Structure, and Organization. Port Governance and Structural Type.
1.3 Port Workforce: Productivity, Growth, and Empowerment Strategies. Measuring
Productivity, Throughput, and Growth.
Connecting Hub port Gateways to the Inland Infrastructure

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2 2.1 Logistics Integration of Port Activities: The Five Stages of Integration for the
Maritime Industry.
08 2.2 Strategic Location and Market Accessibility for Existing and Emerging Seaports.
2.3 Ports’ Success Factors. Supply Chain Opportunities, Competition, and Conflict
Prevention
3 Port Operations
14 3.1 Terminal Operators; Property Leasing Opportunities. Port Management Services
and Operations. The Harbourmaster’s Department and Functions, Terminal
Manager, Vessels’ Planning.
3.2 The Four Stages of Port Management and Operations: Leasing Opportunities,
Marine Terminal Operator (MTO) Agreements and Leasing Opportunities and MTO
case studies
3.3 Charter Party Types, Charter Party Clauses and Areas of Dispute, The Port and
Charter Party Terms
3.4 The Components of Shipbuilding, Intellectual Property Rights, The History of
Shipbuilding , Reasons for Shipyards Losing Market Share, Contemporary
Shipbuilding Trends, Shipbuilding and Oil Market Analysis, Global Market Analysis.
3.5 Liner Services, Tramp Trade, and Offshore Support Agents. Agency Select ion and
Practices, Port Agency Responsibilities. General Agency Duties, for Tramp, Liner, and
Logistics Services.
4 International Trade and Port capacity
06 4.1 The General Agreement on Tariffs and Trade. The World Trade Organization. Ports’
Growth and the Global Trade Agreements Matrix.
4.2 Traffic Forecasting, Ports and the Principles of Derived Demand, Shipping, Ports, and
the Ripple Effect. Optimum Size and Economies of Scale
4.3 Port Capacity Utilization, Capacity Management, Capacity Planning and Ports’
Technology and Innovation.
5 Strategic Planning
08 5.1 Strategic Planning, Development, and Management: Corporate Objectives and
factors considered in planning, developing and management
5.2 Port Pricing Strategies: Tariff Changing and Competitiveness. Port Pricing. Pricing
Systems and Price -Setting Consi derations.
5.3 KPIs: Measuring Financial and Operational Performance.
5.4 Port Equipment and Berth Facilities: Operations and Maintenance, Port Cargo
Handling Equipment (CHE). Performance Management and the Human Factor
6 Port Regulations and Future of Ports
08 6.1 ISM: International Safety Management
ISPS: International Ship and Port Facility Security Code
OHSAS and OSHA: Occupational Safety and Health Administration
VGP: Vessel General Permit by the US Environmental Protection Agency
6.2 ISO 14001: Environmental Management System
HAZMAT: Hazardous Materials;
HAZWOPER: Hazardous Waste Operations and Emergency Response
BWM: Ballast Water Management
6.3 Incident Investigation and Root Cause Analysis ; Inspections, Surveys, and Audits ;
Global and National Regulatory Compliance for Ships

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6.4 Port Development Strategy: Elements of Long -Term Strategic Planning, Strategic
Port Planning and Tactical Port Planning, Port Planning and the Factors of Production
6.5 Forecasting the Market: Port Management and Forecasting Areas. The Risk Element
in Forecasting, Forecasting Methods and Tools

Contribution to Outcome
On completion of this course, the students will be able to:
1. Port operations and planning
2. Port capacity Planning and Forecasting
3. Understand the Key Performance Indicators (KPIs) for strategic planning and
management in port operations
4. Understand the different types of International agreements which are the
tools for growth in Indian ports
5. Understand the regulatory fr amework involved in running a port.
6. Understand the traffic forecasting in order to plan the port operations
effectively

Internal Assessment 20 Marks
Consisting Two Compulsory Class Tests - First test based on approximately 40% of contents and second
test based on remaining contents (approximately 40% but excluding contents covered in Test I)

End Semester Examination 80 Marks
Weightage of each module in end semester examination will be proportional to number of respective
lecture hours mentioned in the curriculum.
1 Question paper will comprise of total six questions, each carrying 20 marks.
2 Question 1 will be compulsory and should cover maximum contents of the curriculum.
3 Remaining questions will be mixed in nature (for example if Q.2 has part (a) from module 3 then
part (b) will be from any module other than module 3).
4 Only Four questions need to be solved.
Recommended Books:
1 Maria G. Burns , “Port Management and Operations ”1st Edition,2015
2 Muir Wood, A.M., and Fleming. C.A., “Coastal Hydraulics Sea and Inland Port Structures”, 1st
Edition, Hallstead Press, 2002.
3 Ozha&Ozha, “Dock and Harbour Engineering”, 1 st Edition, Charotar Books, Anand., 1990
Reference Books:
1 S. Seetharaman, “Construction Engineering and Management”, 4 thEdition ,Umesh
publications, New Delhi, 1999.
2 Richand L. Silister, “Coastal Engineering Volume I & II, Elsevier Publishers, 2000.
3 PeraBrunn, “Port Engineering”, 1 st Edition, Gulf Publish ing Company

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Waterways Transportation Engineering : Semester VII
Course Code Course Name Credits
Lab 1: HWTSBL701 Port and Harbour Operations and Services 02

Contact Hours Credits Assigned
Theory Practical Tutorial Theory Practical Tutorial Total
- 04 Per Week - - 02 02

Theory Term Work/Practical/Oral
Total Internal Assessment End Sem
Exam Duration of
End Sem
Exam Term Work Pract. Oral
Test -I Test -II Average
- - - - - 50 - 50 100

Rationale
This subject is designed to give the basic understanding of ports and harbour structures. The course will also
cover wide areas such as design of entrance channel, turning circle, breakwaters, berthing structures etc.
Thus it’s imperative for students to understand how seaport planned, designed, operates and apply the best
practices along with the latest industrial developments. The course equips students with necessary field
exposure and makes them aware of complex administration and structural reforms a nd acquaints them with
necessary precautions and precision of this profession .

 To study and understand all the important facilities required at the port for the efficient
planning.
 To make the students to understand design and analysis of port and harbour structures using
conventional approach as well as software.
 To understand the importance of load consideration and will enable the students to calculate
the different loads in designing the various components.
 To study and analyse traffic forecasting in order to plan the port operations effectively
 To understand organizational behavior and management techniques for management of port.
 To study human resource management skills required at port.

List of Experiments( Any Six)
Exp.No. Detailed Content Lab Session / Hr.
1 The visit of any harbour and port to understand the various structures, its
construction and operations -Report 02
2 Effect of earth quake and Tsunami on port structures - Case studies 02
3 IT System and Port Planning 02 Course Objectives

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4 Design of Jetties using STAAD Pro and Midas 02
5 Design of Jetties using Sacs 02
6 Design of breakwater using STAAD Pro and Midas 02
7 Design of breakwater using Sacs 02
8 Planning and Designing of Storage, warehouse using STAAD Pro or any other
designing software’s. 02
9 Planning of placing the components of Port and estimating its capacity. 02
10 Current Issues in Port Management: Report on Case Study 02
11 Marine Structure, Navigation Aids 02
12 Docks and Repair Facilities, Port Facilities 02
13 Dredging, Coastal Protection 02

Contribution to Outcomes

 Develop a strong fundamental related to waterways transportation Engineering. Understand
the different terminologies and components of port and harbour and will enable the students
to understand the design issues.
 Understand the concept and principle behind load consideration and will enable the students to
determine the different loads as well.
 Understand the concept of design the foundation and breakwater of different str uctures of ports and
harbour and explore the codal and software requirements while designing.
 Understand the Port operations, planning and process of Dredging
 Understand skill required for effective organizational behavior, project management and port
mana gement skills.

Term work

Shall consist of Assignment, design report, ca se study and Site visit report related to this course. Distribution
of marks for Term Work shall be as follows:
Assignment : 15 marks
Case study and design report: 15 marks
Site visit : 15 marks
Attendance: 05 Marks
Further, while giving weightage of marks on the attendance, following guidelines shall be resorted to: 75% -
80%: 03 Marks; 81% - 90%: 04 Marks; 91% onwards: 05 Marks.
End Semester Oral Examination
The oral examination shall be based upon the entire theory and laboratory syllabus.
Reference Books:
1. Docks and Harbour Engineering: Dr. S.P Bindra, Dhanpatrai Publications, India
2. Docks and Harbour Engineering: Hasmukh P. Oza, Gautam H. Oza, Charotar Publication, India.

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3. Port Design - Guidelines and recommendations by C. A. Thoresen, Tapir Publications.
4. Design of Marine Facilities for the Berthing, Mooring and Repair of Vessels by J. W. Gaythwaite, Van
Nostrand.
5. Handbook of Offshore Engineering by S.K. Chakrabarti, Elseviers , 2005.
6. Maria G. Burns, “Port Management and Operations ”1st Edition,2015
7. Detnorskeveritas, Rules for the Design, Construction and Inspection of Fixed Offshore Structures
8. R. Srinivasan and S. C. Rangwala, Harbour, Dock and Tunnel Engineering, 1995, Charot ar Pub.House,
Anand
9. SCI/SCOPUS Indexed Refereed International Journals (For Case Studies) 2 Relevant Indian Standard
Specifications Codes, BIS Publications, New Delhi. 3 Departmental Laboratory Manual
10. Standard Geotechnical Engineering Handbook
11. NPTEL Vid eo lectures on Practical.





















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Waterways Transportation Engineering : Semester VIII
Course Code Course Name Credits
HWTC801 Construction and Management of Port and Harbour 04

Contact Hours Credits Assigned
Theory Practical Tutorial Theory Practical Tutorial Total
04 -- -- 04 -- -- 04

Theory Term Work/Practical/Oral
Total Internal Assessment End Sem
Exam Duration of End
Sem Exam Term
Work Pract. Oral
Test -I Test -II Average
20 20 20 80 3 Hrs. -- -- -- 100

Rationale
This is a course which deals with various construction equipment and processes of various structures involved
in the port and shipping business as well as teaching capable administration strategies for the same. The course
equips students with necessary fi eld exposure and makes them aware of complex administration and structural
reforms and acquaints them with necessary precautions and precision of this profession.
Objectives
1. To study the various construction equipment and process of Port and harbor
structures.
2. To study the construction and maintenances of Fishing Harbor.
3. To understand the process of Dredging
4. To understand organizational behavior and management techniques for management
of port.
5. To study human resource management skills requi red at port.
6. To understand health, safety, security and environment concerns related to port
activities.

Detailed Syllabus
Module Course Module / Contents Hours
1 Marine and offshore constructi on equipment: Basic motions of Barges, crane
barges, Offshore derrick barges, semisubmersible barges, Jack -up construction
barges, launch barges, pipe laying barges, floating concrete plant. Pile driving
equipment. 10
2. Fishing Harbour Construction 12

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Fishing Harbour and Fish landing centres – Types, Various components of fishing
Harbour and landing centre . Land side and water side facilities and structures of
fishing Harbour. Small and medium fishing Har bour, Deep sea fishing Harbour ,
Environmental auditing for fishing Harbour. Dredging and breakwater
construction. Layout and construction of Jetties, quays and slipways. Use of
different construction materials for shore based and seaside structures . Fishing
Harbour maintenance and waste disposal , Water treatment plant in fishing
Harbour. Statu s of fishing Harbours in India.
3 Dredging General ,Classification of dredging works, Types of dredgers, Uses of
dredged material ,Execution of dredging work 06
4 Introduction to Port management: Organizational behavior: Definition, diversity
in workplace, Ethics and ethical behavior in organizations.
Project Management: Principles of management, Project definition, Project
manager skills, Stages of project, Scheduling, Contract Strategy, selection and
appointment of contractors, project implement ation and execution, closure of
project.
Port and terminal operations, types of ports and terminals, terminal ownership,
port and cargo movements, competition and other challenges facing the industry 08
5 Port Labour, People Management and Port master pla nning:
Historic and current port labour environment, effective management of staff on
ports, Labour reforms and social issues, employment framework and employee
relations.
Introduction to post master planning, land parcelisation, development phasing
strategy, developing 30 year masterplan.
Terminal Ownership: Impact of port ownership, Privatization benefits and
concerns, BOT, BOOT and BOO, Concession agreement, Tariff setting, role of port
regulators. 08
6 Health, Safety, Security and the Environment (HSSE) in Ports:
Importance of HSSE culture, HSSE concepts, HSS on Ports, safety and security
indicators, regulations related to HSSE.
Risk awareness and risk management, system approach to port safety and
security.
Environment management: Introduction, E nvironment impact, Environment
regulations and governance. 08

Contribution to Outco me
On completion of this course, the students will be able to:
1 Understand the various methods and equipment for the construction of Port and harbor
structures
2 Understand the construction and maintenances of Fishing Harbor.
3 Understand the process of Dredging.

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4 Understand skill required for effective organizational behavior, project management and port
management skills.
5 Carry out human resource management in accordance to labour laws and to develop master plan
for port.
6 Understand the importance of health, safety, security and environment concerns at port and to
suggest measure.

Internal Assessment 20 Marks
Consisting Two Compulsory Class Tests - First test based on approximately 40% of contents and second
test based on remaining contents (approximately 40% but excluding contents covered in Test I)

End Semester Examination 80 Marks
Weightage of each modu le in end semester examination will be proportional to number of respective
lecture hours mentioned in the curriculum.
1 Question paper will comprise of total six questions, each carrying 20 marks.
2 Question 1 will be compulsory and should cover maximum contents of the curriculum.
3 Remaining questions will be mixed in nature (for example if Q.2 has part (a) from module 3 then
part (b) will be from any module other than module 3).
4 Only Four questions need to be solved.

Recommended Books:
1 S. Seetharaman, “Construction Engineering and Management”, 4th Edition , Umesh publications,
New Delhi, 1999.
2 Detnorskeveritas, Rules for the Design, Construction and Inspection of Fixed Offshore
Structures.
3 R. Srinivasan and S. C. Rangwala, Harbour , Dock and Tunnel Engineering, 1995,
Charotar Pub.House, Anand
4 Alonzo Def. Quinn, Design and Construction of Ports and Marine Structure, McGraw – Hill Book
Company, New York
5 Construction project management by KK Chitkara, Tata McGraw Hill (2010)


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University of Mumbai





Syllabus

Honours /Minor Degree Program
In
Professional Practices in Structural Engineering



FACULTY OF SCIENCE & TECHNOLOGY

(As per AICTE guidelines with effect from the academic year 2022 -2023)



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University of Mumbai
Professional Practices in Structural Engineering
(With effect from 2022 -23)
Year
&Sem
Course Code
and Course Title Teaching
Scheme Hours / Week Examination Scheme and Marks Credit
Scheme
Theory Seminar/Tutorial Pract Internal
Assess
ment End
Sem
Exam Term
Work Oral Total Credits

TE
Sem
V HPSC501:
Concrete
Consultant
Practices 04 -- -- 20 80 -- -- 100 04
Total 04 - -- 100 - - 100 04
Total Credits = 04

TE
Sem
VI HPSC601:
Formwork
Design Practices 04 -- -- 20 80 -- -- 100 04
Total 04 - - 100 - - 100 04
Total Credits = 04


BE
Sem
VII HPSC701:
Structural
Consultant
practices – I 04 -- -- 20 80 -- -- 100 04
HPSSBL701:
Structural
Consultant
Practices (SBL) 04 -- 50 50 100 02
Total 04 04 100 50 50 200 06
Total Credits = 04+02=06

BE
Sem
VIII
HPSC801:
Structural
Consultant
practices – II 04 - -- 20 80 -- -- 100 04
04 -- 100 -- -- 100 04
Total Credits = 04


Total Credits for Semesters V,VI, VII & VIII = 04+04+06+04=18

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Professional Practices in Structural Engineering : Semester V
Course Code Course Name Credits
HPSC501 Concrete Consultant Practices 04

Contact Hours Credits Assigned
Theory Practical Tutorial Theory Practical Tutorial Total
04 -- -- 04 -- -- 04

Theory Term Work/Practical/Oral
Total Internal Assessment End Sem
Exam Duration of End
Sem Exam Term
Work Pract. Oral
Test -I Test -II Average
20 20 20 80 3 Hrs. -- -- -- 100

Rationale
Basic concept of concrete technology is essential for civil engineering students to execute the civil engineering
projects as per the standard laid down time to time. The concrete technology is the backbone of infrastructure
of civil engineering field. The students must know various concreting operations and testing operations during
and after construction. It is expected to know the properties of materials, especially concrete and to maintain
quality in construction projects. The civil engineeri ng students ought to know the selection of materials, its
mix proportioning, mixing, placing, compacting, curing and finishing.
Objectives
1 To study the properties of fresh and hardened concrete.
2 To study the properties such as workability and durability.
3 To acquaint the practical knowledge by experimental processes of various materials required for
concrete.
4 To understand the Mix design by different methods.
5 To understand ordering and handling of RMC.


Detailed Syllabus
Module Course Module / Contents Hours
1 Introduction to concrete making materials
09 1.1 Cement
Physical properties of cement as per IS Codes, types of cements and their uses.
1.2 Aggregates
Properties of coarse and fine aggregates and their influence on properties of
concrete, properties of crushed aggregates.
2 Special cementitious materials 07

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2.1 GGBS: properties, advantages and disadvantages, uses
2.2 Silica fume: properties, advantages and disadvantages, uses
2.3 Admixture
Plasticizers, Super -plasticizers, Retarders, Accelerators, Mineral admixtures
and
other admixtures, test on admixtures, chemistry and compatibility with
concrete.
3 Concrete and its properties
13 3.1 Grades of concrete, Manufacturing of concrete, importance of w/c ratio.
3.2 Properties of fresh concrete - workability and factors affecting it, consistency,
cohesiveness, bleeding, segregation.
3.3 Properties of hardened concrete - Compressive, Tensile and Flexural strength,
Modulus of Elasticity, Shrinkage and Creep.
3.4 Durability - Factors affecting durability, Relation between durability and
permeability
4 Concrete Mix Design
10 4.1 Design of concrete mixes by IS code method
4.2 Design of concrete mixes by ACI method
4.3 Design of concrete mixes by Road Note 4 method
4.4 Design of high strength concrete mixes, design of light weight aggregate
concrete mixes, design of fly -ash cement concrete mixes, design of high -
density concrete mixes.
5 Testing of Concrete
07 5.1 Non -Destructive testing of concrete
Rebound Hammer test, ultrasonic pulse velocity test, load test, carbonation
test, 1⁄2 cell potentiometer test, core test and relevant provisions of I.S. codes.
5.2 Durability
Permeability test, Rapid chloride penetration test.
6 Ready mix concrete
06 6.1 Advantages of RMC, components of RMC plant, distribution and transport,
handling and placing, mix design of RMC.
6.2 Distribution and transport, handling and placing, mix design of RMC.
6.3 Handling Quality Complaints

Contribution to Ou tcome
On completion of this course, the students will be able to:
1 Identify the properties of ingredients of concrete.
2 Know the properties of wet concrete, hardened concrete.
3 Understand the Mix design by different methods for different grades of concrete.
4 Perform various test on concrete.
5 Understand the concept of durability and cracking in concrete.

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Internal Assessment 20 Marks
Consisting Two Compulsory Class Tests - First test based on approximately 40% of contents and second test
based on remaining contents (approximately 40% but excluding contents covered in Test I)

End Semester Examination 80 Marks
Weightage of each module in end semester examination will be proportional to number of respective lecture
hours mentioned in the curriculum.
1 Question paper will comprise of total six questions, each carrying 20 marks.
2 Question 1 will be compulsory and should cover maximum contents of the curriculum.
3 Remaining questions will be mixed in nature (for example if Q.2 has part (a) from module 3 then part (b)
will be from any module other than module 3).
4 Only Four questions need to be solved.

Recommended Books:
1 Concrete Technology: A. R. Shanthakumar, Oxford University Press.
2 Concrete mix proportioning -guidelines (IS 10262:2009).
3 Method making, curing and determining compressive strength of accelerated -cured concrete test
specimens as per IS: 9013 -2004.
4 Tentative Guidelines for cement concrete mix design for pavements (IRC: 44 -1976): Indian Road Congress,
New Delhi.
5 Properties of concrete: Neville, Isaac Pitman, London.

Reference Books:
1 Concrete Technology Theory and Practice: Shetty M.S., S. Chand.
2 Relevant I.S. codes: Bureau of Indian standard.
3 Concrete Technology: D.F. Orchardi, Wiley, 1962.
4 Chemistry of Cement and Concrete: F.M. Lue, Edward Arnold, 3rd Edition, 1970.
5 Concrete Technology: Neville A.M. & Brooks. J. J., ELBS -Longman.
6 Concrete Technology: Gambhir M.L., Tata McGraw Hill, New Delhi.











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Professional Practices in Structural Engineering : Semester VI
Course Code Course Name Credits
HPSC601 Formwork Design Practices 04

Contact Hours Credits Assigned
Theory Practical Tutorial Theory Practical Tutorial Total
04 -- -- 04 -- -- 04

Theory Term Work/Practical/Oral
Total Internal Assessment End Sem
Exam Duration of End
Sem Exam Term
Work Practi. Oral
Test -I Test -II Average
20 20 20 80 3 Hrs. -- -- -- 100


Rationale
Course focuses on importance of Formwork design in RCC construction apart from concreting and bar bending
work. It deals with the changing scenario towards formwork designing as a career option in Construction
Industry. The course helps the students to know the market outlook as well as the requirements of formwork
design by knowing all the technical as well as field considerations while designing formwork for various
components of building. It gives the exposer to students regarding cost benefits and time saving along with
advanced techn ologies and new formwork mate rial in construction industry.
Objectives
1 To know the different types of formwork and importance of formwork in RCC Construction
2 To study the market outlook and requirements of system formwork in construction industry.
3 To design a formwork for walls, columns, beams and slabs considering all the live loads, concrete
pressures, wind loads, concreting methods and do the necessary checks.
4 To understand the formwork selection criteria for various tunnel construction methods, bridge
construction methods and high -rise construction.
5 To plan and estimate the material and man power required for Formwork.
6 To know the various advancements in formwork design in construction market.


Detailed Syllabus
Module Course Module / Contents Hours
1 Introduction to Formwork
08
1.1 Various Activities and Equipment involved in concrete construction -
Concrete, Reinforcement, Batching Plant, Boom Placer, Concrete Pumps,
Buckets, Crane, Formwork (Shuttering/Centering), Scaffolding, etc.

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1.2 Introduction of Formwork, Types of Formwork, Importance of Formwork in
RCC Structure
1.3 Conventional Formwork and Scaffolding - Advantages and Disadvantages in
view of ongoing approach and site requirements
1.4 System Formwork and Scaffolding, Time -Cost Distribution in RCC
Constructio n with respect to Formwork, Reinforcement and Concreting.
2 System Formwork
09 2.1 Importance of System Formwork - Construction Market Outlook, Market
Growth Drivers (Increasing Urbanization, Housing Shortage, Economic
Development),
2.2 Factors driving demand for System Formwork and Scaffolding, Key
Challenges at construction sites, Requirements and Solutions against
Challenges - Design and Planning, Equipment usage time, etc.
2.3 Design and Planning - Project Planning Sequence - Current and Corr ect
Practice, Any TWO Case Studies.
2.4 Equipment usage time - Crane Availability, Boom Placer, labour, etc.
2.5 Parameters considered in High Rise Buildings - Comparison between System
Formwork and Conventional Formwork
3 Formwork Design - Walls, Columns & Slabs
14 3.1 Introduction to Formwork Design - Factors related to Concreting, Concrete
Placing method influence pressure of Concrete - Crane Bucket Concreting,
Boom Placer Concreting
3.2 Loads on formwork and lateral pressure of concrete, Calculation of design
pressure based on type of concrete, method of concreting, grade of
concrete, type of structure and rate of concreting
3.3 Concrete Pressure Calculation - Column and Wall Formwork
3.4 Design of formwork for slab (less than 4 m hei ght)- Design Loads for slabs
and beams formwork
3.5 Design of formwork Material for walls & Columns (Vertical application) -
Sheathing Member (Plywood), Secondary Member, Primary Member, Tie
System; Check against various forces and bending.
3.6 Design of Slab Formwork Material - Primary, Secondary and Prop Members;
Checks against failures.
3.7 Planning & Estimation of Formwork for Residential & Commercial Buildings,
Column Formwork Sets, Cycle time - Slabs and Beams
4 Formwork for High Rise Constructions, Tunnels and Bridges
12 4.1 Design Concept for Climbing system - Define, Types, CB 240 and SCS 250
system, Anchoring System
4.2 Study of IS: 875(Part3): Wind Loads on Buildings and Structures, Wind Force
for Formwork design - High Rise Construction and Slab height more than 4 m
4.3 Design of Formwork system for any typical floor plan with self -climbing
system for walls, columns, beams and slabs
4.4 Overview of Tunnel Construction Methods & Formwork selection
4.5 Overview Bridge Construction Methods & Formwork Selection
4.6 Overview of High -Rise Construction & Formwork Selection

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5 Economics and Maintenance of Formwork
05 5.1 Factors affecting supply and demand of Formwork
5.2 Manpower Management required for formwork
5.3 Maintenance of Formwork & its Stacking.
6 Advancement & Scope of Formwork Design
04 6.1 Advance formwork technology Available in the market
6.2 Advanced Material used as a Formwork
6.3 Formwork field as career option


Contribution to Out come
On completion of this course, the students will be able to:
1 Understand the different types of formwork and its importance in various RCC construction activities.
2 Understand various aspects of system formwork over conventional formwork. Also, understand the
market outlook and various parameters need to be considered in design of formwork
3 Design a formwork for walls, columns, beams and slabs considering all the live loads, concrete pressures,
wind loads in a view of different concreting metho ds and do the necessary checks
4 Understand the formwork selection criteria for various tunnel construction methods, bridge construction
methods and high -rise construction .
5 Plan and estimate the material and man power required for Formwork .
6 Know the advance formwork technologies and advanced material available in the market.

Internal Assessment 20 Marks
Consisting Two Compulsory Class Tests - First test based on approximately 40% of contents and second test
based on remaining contents (approximately 40% but excluding contents covered in Test I)

End Semester Examination 80 Marks
Weightage of each module in end semester examination will be proportional to number of respective lecture
hours mentioned in the curriculum.
1 Question paper will comprise of total six questions, each carrying 20 marks.
2 Question 1 will be compulsory and should cover maximum contents of the curriculum.
3 Remaining questions will be mixed in nature (for example if Q.2 has part (a) from module 3 then par t (b)
will be from any module other than module 3).
4 Only Four questions need to be solved.

Recommended Books:
1 Formwork for concrete structures: Robert L. Peurifoy and Garold D. Oberlender, The McGraw hill
publishing company.
2 Concrete Formwork Systems: Awad S. Hanna, Marcel Dekker.

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3 Design and Construction of Formwork for Concrete Structures: Albert Edward Wynn, Cement and
Concrete Assn.
4 Concrete Formwork: Leonard Koel, Amer Technical Pub.
Reference Books:
1 IS: 875(Part3): Wind Loads on Buildings and Structures
2 Formwork for concrete structures: Dr. Kumar Neeraj Jha, The McGraw Hill Education India
3 Modern Practices in Formwork for Civil Engineering Construction Work: Dr. Janardan Jha, Prof. S. K. Sinha.








































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Professional Practices in Structural Engineering : Semester VII
Course Code Course Name Credits
HPSC701 Structural Consultant Practice -1 04

Contact Hours Credits Assigned
Theory Practical Tutorial Theory Practical Tutorial Total
04 -- -- 04 -- -- 04

Theory Term Work/Practical/Oral
Total Internal Assessment End Sem
Exam Duration of End
Sem Exam Term
Work Pract. Oral
Test -I Test -II Average
20 20 20 80 3 Hrs. -- -- -- 100

Rationale
Course is equipped with the basic knowledge about structural designs and various other consultants and venders
related with the structural consultant which combines together to carry out the design of any structural project.
This will make students to unde rstand the hierarchy of the work which has to carry out the structural consultant
and structural engineer with other agencies and consultants and also it will highlight the brief information
regarding structural quantity estimation and tenders.
Objectives
1 To understand types of various structures, importance of structural consultant and role of structural
engineer
2 To understand the scope, responsivities and activities of structural engineer
3 To study the schematic designs, documentation and certification in structural design.
4 To understand the roles of client, architect, another consultant with structural consultant.
5 To understand relation of structural consultant with different agencies and vendors.
6 To study structural quantity estimation and tender preparation and also documentation.


Detailed Syllabus
Module Course Module / Contents Hours
1 Introduction
09 1.1 Types of Structures, functionality, various forms of structures, usage driven
requirements, notable structures in the world, country, state, city.
1.2 Information on team of consultants required for the comprehensive design of
structures. Responsibilities of various consultants’ team members – legal,
professional, ethical and moral

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1.3 Place of a structural engineer in the matrix of the overall project, Set up of a
structural designer’s office, Various personnel working in a structural designer’s
office
2 Role of Structural Consultant
07 2.1 Scope of a structural consultant, Tasks and deliverables for a structural
consultant
2.2 Activities that a structural engineer has to carry out
2.3 Legal responsibilities of a structural engineer
3
09 3.1 Introduction to: Concept, Schematic, Tender, Design Development, Detail Design
of various structural designs
3.2 Construction Stage Documentation, Construction Administration, Completion
Stage Documentation, Certification
3.3 Bye laws pertaining to structural engineers in MCGM rule book, HRC, liaison,
NBC, DCR etc.
3.4 Licensing requirements for a structural engineer
4 Teaming up with other consultants, contractors and vendors – Nature of
communication transactions – Part 1
11 4.1 Client – Brief and scope defined by Client’s representative
Architects – Design and Liaison,
Surveyor, Geotechnical Engineer, Wind Engineer
4.2 Façade Engineer, Interior Architect, Landscape architect, Steel Fabrication
contractor’s detailers
4.3 Water proofing Consultant/vendor, Fire proofing Consultant/Vendor, Concrete
technologists, concrete manufacturers
5 Teaming up with other consultants, contractors and vendors – Nature of
communication transactions – Part 2
08 5.1 Agencies: Material Testing Agency, Rebaring Agency, Anchoring Agency, Post
Tensioning Agency, Ground Anchoring Agency, Piling Agency.
5.2 Vendors: Steel suppliers/manufacturers, Alternate material suppliers/
manufacturers/ vendors, Bearings/isolators suppliers/manufacturers / vendors,
Electrical Engineers, Mechanical Engineers
5.3 Other vendor and agencies: Plumbing/Drainage Engineers, Traffic Consultants /
Parking system vendor / parking requirements, Vertical Transportation
Consultants, Pre -Engine ered Building Agencies Contractors in general
6 Structural Quantity Estimation and Tender
08 6.1 Structural Quantity Estimation: Structural Specifications, Structural Bill of
Quantities, General material consumption ratios, Actual sample workout
problem.
6.2 Tender Stage: Preparation of Tender Drawings, Bill of Quantities, Specifications,
Special Notes, Consultant’s estimate, Disclaimers
6.3 Construction Documentation and Construction Administration
Delivery of drawings and other documents to site for execution.

Contribution to Outco me
On completion of this course, the students will be able to:

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1 Understand types of various structures, importance of structural consultant and role of structural
engineer .
2 Understand the various scope, responsivities and activities of structural engineer has in structural
consultant .
3 Study and understand the schematic designs, documentation and certification in structural design
4 Understand the roles and nature of client, architect, other consultant with structural consultant
and also safety measures at site.
5 Understand the n ature of communication transactions of structural consultant with different
agencies and vendors .
6 Study the structural quantity estimation and tender preparation and also documentation works
required to the structural consultant .

Internal Assessment 20 Marks
Consisting Two Compulsory Class Tests - First test based on approximately 40% of contents and second test
based on remaining contents (approximately 40% but excluding contents covered in Test I)

End Semester Examination 80 Marks
Weightage of each module in end semester examination will be proportional to number of respective lecture
hours mentioned in the curriculum.
1 Question paper will comprise of total six questions, each carrying 20 marks.
2 Question 1 will be compulsory and should cover maximum contents of the curriculum.
3 Remaining questions will be mixed in nature (for example if Q.2 has part (a) from module 3 then
part (b) will be from any module other than module 3).
4 Only Four questions need to be solved.

Recommended Books:
1. Fundamentals of Reinforced Concrete: Sinha& Roy, S. Chand and Co. Ltd.
2. Estimating, Costing, Specifications and Valuation: Chakraborty, M., Kolkata.
3. Relevant Indian Standard Specifications, BIS Publications
4. Professional Construction Management: Barrie D.S. & Paulson B C, McGraw Hill
5. The cost management toolbox; A Managers guide to controlling costs and boosting profits - Oliver, Lianabel
(Tata McGraw Hill).









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Professional Practices in Structural Engineering : Semester VII
Course Code Course Name Credits
HPSSBL701 Structural Consultant Practice -Lab 02

Contact Hours Credits Assigned
Theory Practical Tutorial Theory Practical Tutorial Total
-- 04 - -- 02 -- 02

Theory Term Work/Practical/Oral
Total Internal Assessment End Sem
Exam Duration of
End Sem Exam Term
Work Pract. Oral
Test-I Test-II Average
-- -- -- -- -- 50 -- 50 100

Course Objectives
1
To understand types of various structures, importance of structural consultant and role of structural
engineer
2 To understand the scope, responsibilities and activities of structural engineer
3 To study the schematic designs, documentation and certification in structural design.
4 To understand the roles of client, architect, another consultant with structural consultant.
5 To understand relation of structural consultant with different agencies and vendors.
6 To study structural quantity estimation and tender preparation and also documentation.

Contribution to Outco me
On completion of this course, the students will be able to:
1. Understand types of various structures, importance of structural consultant and role of
structural engineer .
2. Understand the various scope, responsibilities and activities of structural engineer has in
structural consultant .
3. Study and understand the schematic designs, documentation and certification in structural
design
4. Understand the roles and nature of client, architect, and other consultant with structural
consultant and also safety measures at site.
5. Understand the n ature of communication transactions of structural consultant with
different agencies and vendors .
6. Study the struc tural quantity estimation and tender preparation and also documentation
works required to the structural consultant .


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List of Tutorials and Assignments
Week
(Activity) Detailed Content Lab
Session
/ Hr.
1 Study of different types of structures based on its utility, roles and responsibilities
of various consultants. 02/04
2 Study of Legal responsibilities, scope and activities for structural consultant 02/04
3 Preparation of tender, documentations and detailed design of various structural
components of any one structure 02/04
4 Design of single bay double storey building structure using softwares like
ETAB/STAAD and SAFE 03/06
5 Application of different IS codes for the selection of parameters (like loading,
design, materials, etc) for different types of structural systems 02/04
6 Structural quantity estimation which includes bill of quantities, general material
consumption ratios, consultant’s estimate 02/04

Assessment:
 End Semester Oral Examination
Oral examination will be based on entire syllabus

Reference Books:
1. Design of Reinforced Concrete Structures: Dayaratnam, P; Oxford and IBH.
2. Illustrated Reinforced Concrete Design: Dr. V. L. Shah and Dr. S. R. Karve, Structure
Publications, Pune
3. Relevant IS codes, BIS Pub lication, New Delhi
4. Project Preparation, Appraisal, Budgeting, and Implementation: Prasanna Chandra (Tata
McGraw Hill).
5. Construction Engineering and Management: S. Seetharaman, Umesh Publications, Delhi.













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Professional Practices in Structural Engineering : Semester VIII
Course Code Course Name Credits
HPSC801 Structural Consultant Practice -II 04

Contact Hours Credits Assigned
Theory Practical Tutorial Theory Practical Tutorial Total
04 -- -- 04 -- -- 04

Theory Term Work/Practical/Oral
Total Internal Assessment End Sem
Exam Duration of End
Sem Exam Term
Work Pract. Oral
Test -I Test -II Average
20 20 20 80 3 Hrs. -- -- -- 100

Rationale
This course is capable of different parameters with the designs and drawing of various structures and the roles
of different structural consultant. The course will give ideas regarding the software applications in the structural
engineering works which eas e the design and drawing stage difficulties. It also provides students the brief
knowledge about different tests required from various agencies, consultants and venders.
Objectives
1
To understand different structures, material required for construction and various interpretations
2 To study the various IS codes, loadings and framing structure systems.
3 To understand and prepare the cost comparison report and hand calculation techniques.
4 To study and run different software used in structural consultant.
5 To understand reinforcement details, drawings and various design audit
6 To conduct different tests and to form stagewise and final certifications for the designs.

Detailed Syllabus
Module Course Module / Contents Hours
1 Introduction
09 1.1 Concept and Schematic Stages
Definition of a given structure – identifying the structural system
1.2 Material of construction – Appropriate selection based on functional
requirement, space constraints, aesthetics, special demands from
client/architect/function
1.3 Data and drawing reading and its interpretation as received from all
collaborating agencies
2 Introduction to IS codes 07

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2.1 Introduction to IS 456, IS 800, IS 1786,
Loading parameters – as per architectural drawings and usage requirements
2.2 Introduction to IS 875, IS 875 -Part 3, IS 1893
2.3 Various types of framing, structural systems – gravity and lateral, codal
inter pretations, parameter selection – comparative studies
3 Cost Comparison and Report
12 3.1 Comparative costing of components: Flooring, Column grids, Types of columns,
Lateral Systems, Foundation systems and Soil retention structures – retaining
walls, shoring systems etc
3.2 Formation of Design Basis Report, Preliminary Analysis Tools – Introduction
3.3 Preparation of Concept and Schematic Drawings. Contents of these drawings.
3.4 Hand Calculation techniques, Sofwares available, tips for usage of software
Introduction to Etabs/ Staad
4 Softwares to carry out structural designs
10 4.1 Hands on ETABS / STAAD / SAFE modelling for sample simple structures for
understanding of the working of the software only, its various facilities, capacity
and limitations. Meaning of various parameter definitions
4.2 Design Development / Working Stage, Incorporation of other consultants’
requirements, Preparation of DD stage drawings
4.3 Running final ETABS model, Running final SAFE mode
5 Reinforcement details
06 5.1 Reinforcement calculations, Feeding data to structural draughtsman
Preparation of GFC / working reinforcement drawings – contents
5.2 Notes on reinforcement drawings, Typical details, Standard formats of
reinforcement drawings
5.3 Special requirements of detailing – Introduction to SP34 and IS 13920
Drawing and design audit
6 Tests and Certifications
08 6.1 List of submittals expected from contractors/vendors/agencies for structural
engineer’s approval
6.2 Site visit records / reports / approvals / comments / suggestions,
Changes in design / drawings / details as per site situations,
Monitoring safety / stability on the site during construction,
Retrofitting / repairs / modifications etc. if necessary
6.3 Stage wise Certification, Monitoring quantities as construction progresses as in
built drawings, Final certification


Contribution to Outc ome
On completion of this course, the students will be able to:
1 Explain different concepts and schematic stages of structures, material required for construction and
various interpretations .
2 Demonstrate use of the various IS codes, loadings parameters and different framing structure
systems.

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3 Prepare the cost comparison report and hand calculation techniques.
4 Prepare and run sample models in different software such as ETABS, STAAD, SAFE used in structural
consultant .
5 Explain reinforcement details from samples, preparation of drawings and various design audit.
6 Conduct diff erent tests according to list wise submittals and to form stage wise and final
certifications for the designs .

Internal Assessment 20 Marks
Consisting Two Compulsory Class Tests - First test based on approximately 40% of contents and second test
based on remaining contents (approximately 40% but excluding contents covered in Test I)

End Semester Examination 80 Marks
Weightage of each module in end semester examination will be proportional to number of respective lecture
hours mentioned in the curriculum.
1 Question paper will comprise of total six questions, each carrying 20 marks.
2 Question 1 will be compulsory and should cover maximum contents of the curriculum.
3 Remaining questions will be mixed in nature (for example if Q.2 has part (a ) from module 3 then part
(b) will be from any module other than module 3).
4 Only Four questions need to be solved.

Recommended Books:
1. Design of Reinforced Concrete Structures : Dayaratnam, P; Oxford and IBH.
2. Illustrated Reinforced Concrete Design: Dr. V. L. Shah and Dr. S. R. Karve , Structure Publications, Pune
3. Relevant IS codes, BIS Publication, New Delhi
4. Project Preparation, Appraisal, Budgeting, and Implementation: Prasanna Chandra (Tata McGraw Hill).
5. Construction Engineering and Management: S. Seet haraman, Umesh Publications, Delhi.











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University of Mumbai





Syllabus

Honours /Minor Degree Program
In
Green Technology and Sustainable Engineering


FACULTY OF SCIENCE & TECHNOLOGY

(As per AICTE guidelines with effect from the academic year 2022 -2023)

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University of Mumbai
Green Technology and Sustainable Engineering
(With effect from 2022 -23)
Year
&
Sem
Course Code
and Course
Title Teaching
Scheme Hours / Week Examination Scheme and Marks Credit
Scheme
Theory Seminar/Tutorial Pract Internal
Assess
ment End
Sem
Exam Term
Work Oral Total Credits

TE
Sem
V HGSC501:
Green
Technologies
and Practices 04 -- -- 20 80 -- -- 100 04
Total 04 - -- 100 - - 100 04
Total Credits = 04

TE
Sem.
VI HGSC601:
Green Building
and
Infrastructure
Engineering 04 -- -- 20 80 -- -- 100 04
Total 04 - - 100 - - 100 04
Total Credits = 04


BE
Sem.
VII HGSC701:
Fundamentals
of Sustainable
Engineering 04 -- -- 20 80 -- -- 100 04
HGSSBL7 01:
Lab-1
Green Building
and
Infrastructure
Engineering -- -- 04 -- -- 50 50 100 02
Total 04 - 04 100 50 50 200 06
Total Credits = 06

BE
Sem.
VIII
HGSC801:
Sustainable Built
Environment
Engineering 04 - -- 20 80 -- -- 100 04
Total 04 - - 100 - - 100 04
Total Credits = 04

Total Credits for Semesters V,VI, VII &VIII = 04+04+06+04 = 18

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Green Technology and Sustainable Engineering: Semester V
Course Code Course Name Credits
HGSC501 Green Technologies and Practices 04

Contact Hours Credits Assigned
Theory Practical Tutorial Theory Practical Tutorial Total
4 - - 4 - - 4

Theory Term Work/Practical/Oral
Total Internal Assessment End Sem
Exam Duration of End
Sem Exam Term
Work Pract. Oral
Test -I Test -II Average
20 20 20 80 03 Hours - - - 100

Rationale
Technology is application of knowledge to practical requirements. Green technologies encompass various
aspects of technology which help us reduce the human impact on the environment and create ways of
sustainable development. Social equitability, economic feasibility and sustainability are the key parameters for
green technology. Today, the environment is racing towards the tipping point at which we would have done
permanent irreversible damages to the planet earth. Our current actions are pulling the world towards an
ecological landslide which if happens would make destruction simply inevitable. Green technologies are an
approach towards savings earth and are necessary. Green technologies are our way out of destruction.
Objectives
1. To acquire knowledge on the concept of green technologies
2. To understand the principles of Green Chemistry in the Energy efficient technologies.
3. To analyze the methods of reducin g CO2 levels in atmosphere for Cleaner Production Project
Development and Impl ementation
4. To evaluate the methods of Pollution Prevention and Cleaner Production Awareness Plan.
5. To analyze the application of Energy Efficacy.
6. To apply the knowledge of Green Fuels during implementation.

Detailed Syllabus
Module Course Module / Contents Hours
1 Introduction to Green Technology
07 1.1 Definition - Importance – Historical evolution – advantages and
disadvantages of green technologies.
1.2 Factors affecting green technologies.
1.3 Role of Industry, Government and Institutions -Industrial Ecology.
1.4 Role of industrial ecology in green technology.
2 Green Chemistry 08

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2.1 Principles of Green Chemistry, Green chemistry metrics -atom economy.
2.2 E factor, reaction mass efficiency.
2.3 Waste: Sources of waste, different types of waste.
2.4 Chemical, physical and biochemical methods of waste minimization.
2.5 Clean development mechanism: reuse, recovery & recycle.
2.6 Raw material substitution: Wealth from waste, case studies.
3 Cleaner Production Project Development and Implementation
09 3.1 Overview of CP Assessment Steps and Skills, Process Flow Diagram.
3.2 Material Balance, CP Option Generation: Technical and Environmental
Feasibility analysis.
3.3 Economic valuation of alternatives: Total Cost Analysis – CP Financing.
3.4 Preparing a Program Plan: Measuring Progress -ISO 14000.
4 Pollution Prevention and Cleaner Production Awareness Plan
10 4.1 Waste audit: Environmental Statement.
4.2 Carbon credit, Carbon trading, Carbon footprint.
4.3 Carbon sequestration.
4.4 Life Cycle Assessment - Elements of LCA.
4.5 Life Cycle Costing.
4.6 Eco Labeling.
5 Energy Efficacy
08 5.1 Availability and need of conventional energy resources: major
environmental problems related to the conventional energy resources.
5.2 Future possibilities of energy need and availability.
5.3 Non -conventional energy sources: Solar Energy -solar energy conversion
technologies and devices.
5.4 Solar Energy: principles, working and application.
6 Green Fuels
10 6.1 Definition -benefits and challenges: comparison of green fuels with
conventional fossil fuels with reference to environmental, economical and
social impacts - public policies and market driven initiatives.
6.2 Biomass energy: Concept of biomass energy utilization, types of biomass
energy, conversion processes.
6.3 Wind Energy, energy conversion technologies, their principles, equipment
and suitability in Indian context.
6.4 Tidal and geothermal energy.

Contribution to Outco me
On completion of this course, the students will be able to:

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95

1. Enlist different concepts of green technologies in a project.
2. Describe the principles of Green Chemistry in the Energy efficient technologies.
3. Select the best method for the carbon credits of various activities for Cleaner
Production Project Development and Implementation.
4. Evaluate the importance of life cycle assessment for Pollution Prevent ion and
Cleaner Production Awareness Plan.
5. To apply the problems related to Pollution Prevention and Cleaner Production
Awareness Plan.
6. To choose the green fuels based on their benefits for sustainable development.


Internal Assessment

20 Marks
Consisting Two Compulsory Class Tests - First test based on approximately 40% of contents and second test based
on remaining contents (approximately 40% but excluding contents covered in Test I)

End Semester Examination
80 Marks

Weightage of each module in end semester examination will be proportional to number of respective lecture
hours mentioned in the curriculum.
1. Question paper will comprise of total six questions, each carrying 20 marks.
2. Question 1 will be compulsory and should cover maximum contents of the curriculum.
3. Remaining questions will be mixed in nature (for example if Q.2 has part (a) from module 3 then part (b) will
be from any module other than module 3).
4. Only Four questions need to be solved.

Recommended Books:
1. Pollution Prevention: Fundamentals and Practice’ by Paul L Bishop (2000), McGraw Hill International.
2. ‘Pollution Prevention and Abatement Handbook –Towards Cleaner Production’ by World Bank Group
(1998), World Bank and UNEP, Washington D.C.
3. ‘Cleaner Product ion Audit’ by Prasad Modak, C. Visvanathan and Mandar Parasnis (1995), Environmental
System Reviews, No.38, Asian Institute of Technology, Bangkok
4. ‘Handbook of Organic Waste Conversion’ by Bewik M.W.M.
5. ‘Solar Energy’ by Sukhatme S.P.

Reference Books:
1. ‘Energy, The Solar Hydrogen Alternative’ by Bokris J.O.
2. ‘Non -conventional Energy Sources’ by Rai G.D.
3. ‘Waste Energy Utilization Technology’ by Kiang Y. H.
4. Wind, Tidal , Geothermal, Biomass and Non –conventional energy Green fuel by G.D.Rai.

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Green Technology and Sustainable Engineering : Semester VI
Course Code Course Name Credits
HGSC601 Green Building and Infrastructure Engineering 04

Contact Hours Credits Assigned
Theory Practical Tutorial Theory Practical Tutorial Total
4 - - 4 - - 4

Theory Term Work/Practical/Oral
Total Internal Assessment End Sem
Exam Duration of End
Sem Exam Term
Work Pract. Oral
Test -I Test -II Average
20 20 20 80 03 Hours - - - 100

Rationale
This course incorporating sustainable design/thinking as a new civil engineering course and experiences from the
pilot offering. Important areas are outlined to aid all engineers in understanding sustainability in context with
traditional engineering principles. Green -building rating systems are used to introduce the concepts of sustainability
in buildings and infrastructure, highlighted by presentations from green -building professionals. By providing a better
understanding of sustainability through education, civil engineers can provide proactive solutions to a g rowing global
infrastructure.

Objectives

1. To acquire knowledge on various aspects of green building concepts.
2. To acquire knowledge on Indian Green Building Council.
3. To understand to green building design.
4. To apply knowledge on material conservation handling of non -process waste.
5. To analyze green building assessment systems national as well international.
6. To evaluate various terminologies Embodied Energy, Life Cycle Assessment, Environmental Impact
Assessment, Energy Audit and Energy Management.
Detailed Syllabus
Module Course Module / Contents Hours
1 Green Building Concepts
07 1.1 What is Green Building, Why to go for Green Building, Benefits of Green Buildings -
1.2 Green Building Materials and Equipment in India, What are key Requisites for
Constructing a Green Building?

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1.3 Principles of green building – Selection of site and Orientation of the building –
usage of low energy materials – effective cooling and heating systems -
1.4 Effective electrical systems – effective water conservat ion systems -
2 Green Building Practices in India
09 2.1 Practices Indian Green Building Council, Green Building Moment in India, Benefits
Experienced in Green Buildings -
2.2 Launch of Green Building Rating Systems, Residential Sector, Market
Transformation -
2.3 Green Building Opportunities And Benefits: Opportunities of Green Building -
2.4 Green Building Features, Material and Resources, Water Efficiency
2.5 Optimum Energy Efficiency -
2.6 Typical Energy Saving Approach in Buildings -
3 Introduction to Green Building Design
09 3.1 Green Building Design Introduction, Reduction in Energy Demand -
3.2 Onsite Sources and Sinks, Maximize System Efficiency -
3.3 Steps to Reduce Energy Demand and Use Onsite Sources and Sinks, Use of
Renewable Energy Sources.
3.4 Eco-friendly captive power generation for factory, Building requirement -
4 Material Conservation and Occupational Health
09 4.1 Material Conservation Handling of non -process waste, waste reduction during
construction -
4.2 Materials with recycled content, local materials, material reuse, certified wood,
Rapidly renewable building materials and furniture -
4.3 Indoor Environment Quality And Occupational Health: Air conditioning, Indoor air
quality, Sick building s yndrome, Tobacco smoke control -
4.4 Minimum fresh air requirements avoid use of asbestos in the building -
4.5 Improved fresh air ventilation, Measure of IAQ -
4.6 Reasons for poor IAQ, Measures to achieve Acceptable IAQ levels -
5 Green building Rating Systems
09 5.1 Green building assessments system studying e.g. LEED US (Leadership in Energy and
Environmental Design) -
5.2 Living Building Challenge, Green Globes ( Green Building Initiative) (US), Green
Globes (ECD -Canada; LEED -Canada, Built Green CANADA
5.3 BREEAM (Building Research Establishment Environmental Assessment Method)
(UK) -
5.4 LEED India ( Indian GBC ); IGBC Green modules; TERI -GRIHA (Green Rating for
Integrated Habitat Assessment) (India) Rating modules -
6 Embodied Energy, Life Cycle Assessment, Environmental Impact Assessment, Energy
Audit and Energy Management 09
6.1 Introduction to the Concept: “Life Cycle assessment of materials” -

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6.2 EIA: Introduction to EIA. Process of EIA and its application through a case study,
EIA as a strategic tool for sustainable development -Social Impact Assessment of
Infrastructure projects -
6.3 Embodied energy of various construction materials -Energy Management with
respect to buildings -
6.4 Clean Development Mechanism, Kyoto Protocol, Energy Conservation Building
Code -

Contribution to Outc ome

On completion of this course, the students will be able to:
1. Explain the concepts of green building.
2. Learn practices Indian Green Building Council and GRIHA.
3. Use the green building design in the projects.
4. Learn material conservation handling of non -process waste.
5. Learn green building assessment systems national as well international.
6. Study various terminologies Embodied Energy, Life Cycle As sessment,
Environmental Impact Assessment, Energy Audit and Energy Management.
Internal Assessment
20 Marks
Consisting Two Compulsory Class Tests - First test based on approximately 40% of contents and second test
based on remaining contents (approximately 40% but excluding contents covered in Test I)

End Semester Examination 80 Marks
Weightage of each module in end semester examination will be proportional to number of respective lecture
hours mentioned in the curriculum.
1 Question paper will comprise of total six questions, each carrying 20 marks.
2 Question 1 will be compulsory and should cover maximum contents of the curriculum.
3 Remaining questions will be mixed in nature (for example if Q.2 has part (a) from module 3 then part (b)
will be from any module other than module 3).
4 Only Four questions need to be solved.
Recommended Books:
1. Manual of Tropical housing and climate by Koenisberger
2. Climate responsive architecture by Arvind Krishnan
3. Manual of solar passive architecture - by Nayak J.K. R. Hazra J. Prajapati.
4. Energy Efficient Buildings in India by Milli Mujumdar
5. Solar Energy in Architecture and Urban Planning by Herzog Thomas
6. Sustainable Building Design Manual -Volume I and II –TERI Publ ication
7. Green building codes and standards
8. International Green Construction Code
9. Complete Guide to Green Buildings by Trish riley
10. Standard for the design for High Performance Green Buildings by Kent Peterson, 2009

Reference Books:

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99
1. Green Building Hand Book by Tom woolley and Sam kimings, 2009.
2. Green Building Materials by Ross Spiegel and Dru Meadows
3. Publications from - CBRI , SERC, BMTPC
4. Shahane, V. S, “Planning and Designing Building”, Poona, Allies Book Stall, 2004.
5. Michael Bauer, Peter Mösle and Michael Schwarz “Green Building – Guidebook for Sustainable
Architecture” Springer, 2010.
6. Tom Woolley, Sam Kimmins, Paul Harrison and Rob Harrison “Green Building Handbook” Volume I, Spon
Press, 2001.







































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Green Technology and Sustainable Engineering : Semester VII
Course Code Course Name Credits
HGSC701 Fundamentals of Sustainable Engineering 04

Contact Hours Credits Assigned
Theory Practical Tutorial Theory Practical Tutorial Total
4 - - 4 - - 4

Theory Term Work/Practical/Oral
Total Internal Assessment End Sem
Exam Duration of End
Sem Exam Term
Work Pract. Oral
Test -I Test -II Average
20 20 20 80 03 Hours - - - 100

Rationale
This course contains content that address sustainability issues and innovations of relevance to the discipline area.
Sustainability content (principles and theory) is well integrated into the course. The course outline specifically
addresses the sustainabi lity content.
Objectives

1. To acquire knowledge and awareness among students on issues in areas of sustainability.
2. To understand the role of engineering Environmental Pollution and Environmental legislations in India.
3. To understand the International Environmental Management Standards.
4. To apply a clear understanding of the role and impact of various aspects of engineering and engineering
decisions on environmental, societal, and economic problems.
5. To analyze the Sustainable Engineering.
6. To evaluate the Sustainable Assessment Systems.

Detailed Syllabus
Module Course Module / Contents Hours
1 Introduction to Sustainability
08 1.1 Sustainability -Introduction, Historical Evolution -Goals of Sustainable Development -
Principles of Sustainability -Sustainability -need and concept, challenges.
1.2 Social, Environmental and Economic sustainability concepts
1.3 Sustainable development, Nexus between Technology and Sustainable development,
Challenges for Sus tainable Development.
1.4 Multilateral environmental agreements and Protocols -Clean Development Mechanism
(CDM)
2 Environmental Pollution and Environmental legislations in India 09

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2.1 Regional and Local Environmental Issues -Air Pollution, Sources - Effects -Preventative
Measures of Air Pollution; Water pollution - Land Pollution
2.2 Sustainable wastewater treatment, Solid waste - sources, impacts of solid waste, Zero
waste concepts, 3 R concept -
2.3 Environmental legislations in India -Water Act, Air (Pollution & Prevention) Act
2.4 Environmental Protection Act and Climate Change Act
2.5 Forest Act, Animal Protection Act, Factory Act, Labour Act
2.6 SEZ Notifications, CRZ Notifications etc
3 International Environmental Management Standards
09 3.1 International Environment Acts and Protocols, Global, Regional and Local environmental
issues, Natural resources and their pollution, Carbon credits, Carbon Trading, Carbon Foot
Print
3.2 ISO 14000, ISO 14001, Life Cycle Analysis, Environmental Impact Assessment studies,
Sustainable habitat
3.3 Global environmental issues -Resource degradation, Climate change, Global warming,
Ozone layer depletion

3.4 Sustainable materials -Conventional and renewable material sources, sustainab le
development, Sustainable u rbanization, Industrial Ecology
4 Basic concepts of sustainable habitat and Energy sources
09 4.1 Basic concepts of sustainable habitat, Sustainable materials for building construction
4.2 Material selection for sustainable design
4.3 Conventional and non -conventional energy sources -Solar energy, Fuel cells, Wind energy,
Small hydro plants, bio -fuels, Energy derived from oceans, Geothermal energy -Methods for
increasing energy efficiency of buildings
4.4 Embodied energy of various construction materials -Energy Management with respect to
buildings
4.5 Clean Development Mechanism
4.6 Kyoto Protocol, and Energy Conservation Building Code
5 Sustainable Engineering -
08 5.1 Sustainable Urbanization - Sustainable cities -
5.2 Sustainable transport -Industrialization and poverty reduction -Social and technological
change -
5.3 Industrial Processes: Material selection, Pollution Prevention, Industrial Ecology, Industrial
symbiosis
5.4 Bio-mimicking
6 Sustainable Assessment Systems
09 6.1 Studying few Green/Sustainable building assessments systems
e.g. Living Building Challenge, Green Globes ( Green Building Initiative) (US)
6.2 LEED India and GRIHA Sustainability Assessment Techniques -
6.3 Green Globes (ECD –Canada, International Initiative for a Sustainable Built Environment:
iiSBTool

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6.4 SBModel 15
Contribution to Outc ome

On completion of this course, the students will be able to:
1. To explain issues in areas of sustainability.
2. To summarize the role of engineering Environmental Pollution and Environmental legislations in India .
3. To interpret the International Environmental Management Standards.
4. To relate a clear understanding of the role and impact of va rious aspects of engineering and engineering decisions
on environmental, s ocietal, and economic problems.
5. To connect the Sustainable Engineering
6. To develop the Sustainable Assessment Systems.

Internal Assessment 20 Mark s
Consisting Two Compulsory Class Tests - First test based on approximately 40% of contents and second test based on
remaining contents (approximately 40% but excluding contents covered in Test I)

End Semester Examination 80 Marks
Weightage of each module in end semester examination will be proportional to number of respective lecture hours
mentioned in the curriculum.
1 Question paper will comprise of total six questions, each carrying 20 marks.
2 Question 1 will be compulsory and should cover maximum contents of the curriculum.
3 Remaining questions will be mixed in nature (for example if Q.2 has part (a) from module 3 then part (b) will be
from any module other than module 3).
4 Only Four questions need to be solved.

Recommended Books:
1. Allen, D. T. and Shonnard, D. R., Sustainability Engineering: Concepts, Design and Case Studies, Prentice Hall.
2. Bradley. A.S; Adebayo, A.O., Maria, P. Engineering applications in sustainable design and development, Cengage
learning
3. Mackenthun, K.M., Basic Concepts in Envir onmental Management, Lewis Publication, London, 1998
4. Twidell, J. W. and Weir, A. D., Renewable Energy Resources, English Lang.
5. Prohit, S. S., Green Technology - An approach for sustainable environment, Agrobios publication uage Book Society
(ELBS).
Reference Books:
1. Environment Impact Assessment Guidelines, Notification of Government of India, 2006
2. ECBC Code 2016, Bureau of Energy Efficiency, New Delhi Bureau of Energy Efficiency Publications -Rating System,
TERI Publications - GRIHA Rating System
3. Ni bi n Chang, Systems Analysis for Sustainable Engineering: Theory and Applications, McGraw -Hill Professional.

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Green Technology and Sustainable Engineering : Semester -VII
Course Code Course Name Credits
Lab 1: HGSSBL601 Green Building and Infrastructure Engineering 02

Contact Hours Credits Assigned
Theory Practical Tutorial Theory Practical Tutorial Total
- 04 Per Week - - 02 02

Theory Term Work/Practical/Oral
Total Internal Assessment End Sem
Exam Duration of
End Sem
Exam Term Work Pract. Oral
Test -I Test -II Average
- - - - - 50 - 50 100

Course Objective:
1. To acquire knowledge on various aspects of green building concepts.
2. To acquire knowledge on Indian Green Building Council.
3. To understand green building design.
4. To analyze green building assessment systems national as well international.
5. To apply knowledge on material conservation handling of non -process waste.
6. To evaluate various terminologies of Embodied Energy, Life Cycle Assessment, Environmental Impact Assessment,
Energy Audit and Energy Management

List of Experiments (Conduct six practicals out of nine mentioned below)
Module Detailed Content Lab Session
/ Hr.
1 To study sustainable planning aspects for urban housing (Literature based). 04
2 To study the benefits given by Municipal Corporations to Green Buildings (Literature based). 04
3 To prepare detailed plan for a hypothetical site indicating utility of solar path, wind direction,
rainfall intensity etc., to make it sustainable (Literature based) 04
4 To pre pare a report on energy efficient buildings in India (Case Study based). 04
5 To compare the benefits under different green building rating systems (Literature based) 04
6 To study: Innovative Materials Developed by CBRI, SERC (Literature based). 04
7 To study, analyze present scenario of organic waste collection and management of any of the
premise; preferably hotels (Case Study based) 04
8 To prepare a report on carbon credit, carbon Trading and Carbon footprint (Literature based). 04
9 To study: Environmental Audit of any existing building and prepare a report (Case Study
based). 04

Course Outcomes

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At the end of the course, learner will be able to:
1. Understand the concepts of green building.
2. Learn practices of Indian Green Building Council and GRIHA
3. Design a sustainable green building
4. Assessed green building systems nationally as well internationally.
5. Learn material conservation handling of non -process waste.
6. Study various terminologies of Embodied Energy, Life Cycle A ssessment, Environmental Impact Assessment, Energy
Audit and Energy Management.
Assessment:

Term work :
Shall consist of Assignment, design report, case study and Site visit report related to this course. Distribution of marks fo r
Term Work shall be as follows:
Assignment: 15 marks
Case study/Literature report: 15 marks
Site visit: 15 marks
Attendance: 05 marks
Further, while giving weightage of marks on the attendance, following guidelines shall be resorted to: 75% - 80%: 03
Marks; 81% - 90%: 04 Marks; 91 % onwards: 05 Marks.
End Semester Oral Examination :
Oral examination shall be based upon the entire theory, site visit and laboratory syllabus.
Recommended Books:
1. ‘Handbook of Organic Waste Conversion’ by Bewik M.W.M.
2. Green Building Hand Book by Tom woolley and Sam kimings, 2009.
3. Energy Efficient Buildings in India by Milli Mujumdar
4. Allen, D. T. and Shonnard, D. R., ‘Sustainability Engineering: Concepts, Design and Case Studies’, Prentice Hall.
5. ‘Solar Energy’ by Sukhatme S.P.
6. ‘Waste Energy Utilization Technology’ by Kiang Y. H.
Reference Books:
1. Handbook on Green Practices published by Indian Society o f Heating Refrigerating and Air -conditioning Engineers,
2009.
2. Manual of Tropical housing and climate by Koenisberger
3. Climate responsive architecture by Arvind Krishnan
4. Manual of solar passive architecture - by Nayak J.K. R. Hazra J. Prajapati.
5. Green Building Materials by Ross Spiegel and Dru Meadows Publications from - CBRI , SERC, BMTPC
6. Solar Energy in Architecture and Urban Planning by Herzog Thomas
7. Sustainable Building Design Manual -Volume I and II –TERI Publication
8. Green building codes and standards
9. International Green Construction Code
10. Complete Guide to Green Buildings by Trish riley
11. Standard for the design for High Performance Green Buildings by Kent Peterson, 2009
12. Shahane, V. S, “Planning and Designing Building”, Poona, Allies Book Stall, 2004.
13. Michael Bauer, Peter Mösle and Michael Schwarz “Green Building – Guidebook for Sustainable Architecture”
Springer, 2010.
14. Tom Woolley, Sam K immins, P. Harrison and R. Harrison “Green Building Handbook” Volume -I, Spon Press, 2001.

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Green Technology and Sustainable Engineering : Semester VIII
Course Code Course Name Credits
HGSC801 Sustainable Built Environment Engineering 04

Contact Hours Credits Assigned
Theory Practical Tutorial Theory Practical Tutorial Total
4 - - 4 - - 4

Theory Term Work/Practical/Oral
Total Internal Assessment End Sem
Exam Duration of End
Sem Exam Term
Work Pract. Oral
Test -I Test -II Average
20 20 20 80 03 Hours - - - 100

Rationale
Education for sustainability is an important part of the journey to live and work in a sustainable manner. Curricula
changes to incorporate sustainability education in the built environment disciplines is not a new phenomenon. Often,
curricula changes are made from the perspective of the discipline and the individual learning the course.
Objectives
1. To Understand Sustainable Development
2. To apply knowledge for Understanding Ecosystems
3. To evaluate Environmental Sustainability.
4. To create Socio -economic Sustainability.
5. To create Urban Planning and Environment.
6. To analyze the Built in Environment.
Detailed Syllabus
Module Course Module / Contents Hours
1 Sustainable Development
08 1.1 Definitions and principles of Sustainable Development - History and emergence of the
concept of Sustainable Development.
1.2 Environment and Development linkages - Globalization and environment.
1.3 Millennium Development Goals - Status (global and Indian) -
1.4 Impacts on approach to development policy and practice in India, future directions.
2 Understanding Ecosystems
09 2.1 Understanding Ecosystems -biodiversity hotspots, Understanding Critical
Perspectives on Environment and Development -Environmental Policy and Law,
Landscape Ecology and human development.
2.2 Introduction to Policy, Institutions and Governance -Urbanization -Conservation of
natural resources and livelihood security.

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2.3 Environment - Evaluation and Impact Assessment Frameworks -Knowledge of
ecosystem dynamics, ecosystem -livelihood linkages, Environmental vulnerabilities
and adaptations.
2.4 Resilience towards climate change and disasters -Environment -development -poverty
linkages, issues of access and justice.
2.5 Understanding of field techniques and skills to assess ecological processes -Skills to
engage with local communities, undertake impact assessments.
2.6 Experiential learning of conservation and development issues.
3 Environmental Sustainability
09 3.1 Land, Water and Food production
3.2 Moving towards sustainability: Energy powering
3.3 Sustainable Development - Financing the environment
3.4 Sustainable Development - Development of Environmental Protection Mechanism
4 Socio -economic Sustainability
09 4.1 Empowerment of Women, Children, Youth, Indigenous People
4.2 Non -Governmental Organizations, Local Authorities, Business and Industry
4.3 Sustainability Performance indicators and Assessment mechanism
4.4 Hurdles to sustainability - Constraints and barriers for sustainable development
4.5 Operational guidelines -Interconnected prerequisites for sustainable development
4.6 Science and Technology for sustainable development
5 Urban Planning and Environment
08 5.1 Environment and Resources
5.2 Sustainability Assessment - Future Scenarios
5.3 Form of Urban Region - Managing the change
5.4 Integrated Planning -Sustainable Development
6 The Built in Environment
09 6.1 Urban Form
6.2 Land Use -Compact Development
6.3 Principles of street design -complete streets
6.4 Transport Integrated Urban land use Planning - Guidelines for Environmentally
sound Transportation

Contribution to Outc ome

On completion of this course, the students will be able to:

1. Describe the concept and socio -economic policies of Sustainable Development.
2. Identify the strategies for implementing eco development programs.
3. Identify different approaches for resource conservation and management.

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4. Suggest action plans for implementation of sustainable development.
5. Explain Urban Planning and Environment.
6. Explain the built in environment.
Internal Assessment 20 Marks
Consisting Two Compulsory Class Tests - First test based on approximately 40% of contents and second test based on
remaining contents (approximately 40% but excluding contents covered in Test I)

End Semester Examination 80 Marks
Weightage of each module in end semester examination will be proportional to number of respective lecture hours
mentioned in the curriculum.
1 Question paper will comprise of total six questions, each carrying 20 marks.
2 Question 1 will be compulsory and should cover maximum contents of the curriculum.
3 Remaining questions will be mixed in nature (for example if Q.2 has part (a) from module 3 then part (b) will be
from any module other than module 3).
4 Only Four questions need to be solved.

Recommended Books:
1. Allen, D. T. and Shonnard, D. R., Sustainability Engineering: Concepts, Design and Case Studies, Prentice Hall.
2. Mackenthun, K.M., Basic Concepts in Environmental Management, Lewis Publication, London, 1998
3. ECBC Code 2016, Bureau of Energy Efficiency, New Delhi Bureau of Energy Efficiency Publications -Rating System,
TERI Publications - GRIHA R ating System
4. Ni bin Chang, Systems Analysis for Sustainable Engineering: Theory and Applications, McGraw -Hill Professional.
5. Prohit, S. S., Green Technology - An approach for sustainable environment, Agrobios publication uage Book Society
(ELBS).
6. Ganesha Somayaji and Sakarama Somayaji, "Environmental Concerns and Sustainable development: Some
perspectives from India", Editors: publisher TERI Press, ISBN 8179932249.
7. Kirkby. J, O'Keefe P. and Timberlake, "Sustainable development" Earth Scan Publication, Lon don, 1996.
Reference Books:
1. Bradley. A.S; Adebayo, A.O., Maria, P. Engineering applications in sustainable design and development, Cengage
learning
2. Environment Impact Assessment Guidelines, Notification of Government of India, 2006
3. Twidell, J. W. and Weir, A. D., Renewable Energy Resources, English Lang
4. Gilg A W and Yarwood R, "Rural Change and Sustainability - Agriculture, the Environment and Communities", CABI
Edited by S J Essex, September2005.
5. James H. Weaver, Michael T. Rock, Kenneth Kustere, "Ac hieving Broad -Based Sustainable Development:
Governance, Environment, and Growth with Equity", Kumarian Press, West Hartford, CT. Publication Year, 1997.
6. Kerry Turner. R, "Sustainable Environmental Management", Principles and Practice Publisher: Belhaven Press, ISBN:
1852930039.
7. Munier N, "Introduction to Sustainability", Springer2005.

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University of Mumbai





Syllabus

Honours /Minor Degree Program
In
Infrastructure Policies & Regulations



FACULTY OF SCIENCE & TECHNOLOGY

(As per AICTE guidelines with effect from the academic year 2022 -2023)




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109

University of Mumbai
Infrastructure Policies & Regulations
(With effect from 2022 -23)
Year
&
Sem
Course Code and
Course Title Teaching
Scheme Hours / Week Examination Scheme and Marks Credit
Scheme
Theory Seminar/
Tutorial Pract . Internal
Assess -
ment End
Sem
Exam Term
Work Oral Total Credits

TE
Sem
V HIPC 501:
Environmental
Policies &
Regulations 04 -- -- 20 80 - -- 100 04
Total 04 - -- 100 - - 100 04
Total Credits = 04

TE
Sem.
VI HIPC601:
Land Policies &
Regulations 04 -- -- 20 80 - -- 100 04
Total 04 - - 100 - - 100 04
Tota l Credits = 04


BE
Sem.
VII HIPC 701:
Infrastructure
Finance &
Business Policies 04 -- -- 20 80 -- -- 100 04
HIPSBL 701: Lab -1
Infrastructure
Finance &
Business Policies -- -- 04 -- -- 50 50 100 02
Total 04 - 04 100 50 50 200 06
Tota l Credits = 06

BE
Sem.
VIII HIPC 801:
Arbitration &
Conciliation 04 - -- 20 80 -- -- 100 04
Total 04 - - 100 - - 100 04
Total Credits = 04

Total Credits for Semesters V, VI, VII & VIII = 04+04+06+04 = 18

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110

Contact Hours Credits Assigned
Theory Practical Tutorial Theory Practical Tutorial Total
4 - - 4 - - 4

Theory Term Work/Practical/Oral
Total Internal Assessment End
Sem
Exam Duration of End
Sem Exam TW PR OR Test -I Test -II Average
20 20 20 80 3 hrs. - - - 100

Rationale
Environmental law describes a network of regulations and customary laws that address the effects of human activity on the
natural environment. These laws are also referred to as environmental and natural resource laws and centre on the idea of
environmenta l pollution. Environmental law is necessary to combat issues related to the environment and conservation of
natural resources. Environmental law addresses a wide variety of different areas like reducing air pollution and maintaining
air quality, Water Qual ity, Waste management, Sustainability of resources. This course covers the laws related to sustainable
development and protections of environment under general laws. It also emphasizes the laws regarding hazardous and solid
waste management, water, air and noise pollution and its prevention. It explores the compliance and enforcement of
international environmental law.
Objectives
1. To understand and explain the significance of sustainable development and laws regarding protection of
environment.
2. To study the laws related to environment (protection) act, 1986.
3. To emphasize the salient features of water act and describe the laws related to water pollution.
4. To study the salient features of air pollution act and understand the laws related to air and noise pollu tion.
5. To study the laws regarding hazardous and solid waste management.
6. To understand the International Environment Laws and policies.
Detailed Syllabus

Module Course Modules / Contents Hours

1 Sustainable Development and Protection of environment under General Laws 10
Introduction, Sustainable development, Precautionary principle, the polluter pays principle, the
public trust doctrine, eco -development, sustainable development and the Indian judiciary,
Environment protection under the law of Torts, Environment protection under the Indian Penal
Code:1860, Environment protection under the criminal procedure code:1973, Constitutional
provisions and environment protection in India.
2 The Environment (Protection) Act, 1986 8 Infrastructure Policies & Regulations : Semester -V
Course Code Course Name Credits
HIPC 501 Environmental Policies & Regulations 04

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111
Introduction, Aims and objectives, Scope and commencement of the act, Salient features of the
act, definitions, general powers of the central government, prevention, control and abatement
of environmental pollution, offences and penalties, miscellaneous provisions.
3 Water Pollution 9
Introduction, aims and objectives, Salient features of the water pollution act, constitution of
central and state boards and their powers and functions, appeals and revisions, offences and
penalties, prevention and control of water pollution , miscellaneous provisions.
4 Air pollution and Noise Pollution 10
Introduction, Aims and objectives, Salient features of the air pollution act, constitution of central
and state boards and their powers and functions, appeals and revisions, offences and penalties,
miscellaneous provisions, Noise Pollution regulation and control rule 2000, legislative and non -
legislative measures, control of noise pollution.
5 Hazardous and Solid Waste Management 8
Introduction, ozone depleting substances (Regulation and control rule 2000), Hazardous and
other waste (Management and transboundary movement) Rules 2016, Construction and
demolition waste management Rule 2016, Solid waste management Rule 2016, Wetland
(Conservation and management) Rule 2017.
6 International Environment Law 7
An introduction to international law, Sources and basic principles of international law,
development of international laws, nature and scope, establishment of environment institutions
like UNEP, World charter for nature 1982, Relationship between international laws and domestic
laws: Compliance and enforcement.
Total 52

Contribution to Outcome

On completion of this course, the students will be able to:

1. Illustrate the significance of sustainable development and protection of environment under general laws.
2. Explain and implement the laws related to environment (protection) act, 1986.
3. Summarize the salient features of water act and identify the laws related to water pollution.
4. Understand the salient features of ai r pollution act and classify the laws related to air and noise pollution.
5. Analyze and appraise the laws regarding hazardous and solid waste management.
6. Explore and justify the importance of International Environment Laws and policies.

Internal Assessment (20 Marks):
Consisting Two Compulsory Class Tests
First test based on approximately 40% of contents and second test based on remaining contents (approximately 40%
but excluding contents covered in Test I)
End Semester Examination (80 Marks):
Weightage of each module in end semester examination will be proportional to number of respective lectures hours
mentioned in the curriculum.
1. Question paper will comprise of total six questions , each carrying 20 marks.

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2. Question 1 will be compulsory and should cover m aximum contents of the curriculum
3. Remaining questions will be mixed in nature (for example if Q.2 has part (a) from module 3 then part (b) will be
from any module other than module 3)
4. Only Four questions need to be solved .

Recommended Books:
1. Divan S. and Rosencranz A. (2005) Environmental Law and Policy, 2nd ed., New Delhi.
2. Leelakrishnan P. (2008) Environmental Law in India, 3rd ed., Lexis Nexis, India.
3. Shastri S. C. (2012) Environmental Law, Eastern Book Company, 4th ed., Lucknow.
4. Gurdip Sing h (2016) Environmental Law in India, 2nd ed.
5. Dr. Paramjit Jaswal, Dr. Nishtha Jaswal and Vibhuti Jaswal (2021) Environmental Law, Allahabad Law Agency, 5th ed.,
Allahabad.
Reference Books:
1. Alaxander kiss and Diana Shelton (2007) Guide to International Env ironmental Laws, Martinus Nijhoff Publisher,
USA.
2. Philippe Sands and Jacqueline Peel, Principles of International EnvironmentalLaw (4th ed., 2018).
3. Shibani Ghosh ed., Indian Environmental Law: Key Concepts and Principles (2019).
4. Geetanjoy Sahu, Environment al Jurisprudence and the Supreme Court: Litigation, Interpretation, Implementation
(2014).
5. Stuart Bell & Donald Mc Gillivray, Environmental Law (7th ed., 2008).
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Infrastructure Policies & Regulations : Semester -VI
Course Code Course Name Credits
HIPC 601 Land Policies & Regulations 04

Contact Hours Credits Assigned
Theory Practical Tutorial Theory Practical Tutorial Total
04 - - 04 - - 04

Theory Term Work/Practical/Oral
Total Internal Assessment End Sem
Exam Duration of End Sem
Exam TW PR OR Test -I Test -II Average
20 20 20 80 3 hrs. -- - - 100

Rationale
Land law is important in relation with the Infrastructure Engineering students. This will familiarize the students with
the acts and codes that are applicable as per actual conditions in the field. The course deals with the overall knowledge
of the central and state acts and rules. Land law is the form of law that deals with the rights to use, alienate, or exclude
others from land. In many jurisdictions, these kinds of property are referred to as real estate or real property, as distinct
from personal property. Land use agreements, including renting, are an important intersection of propert y and
contract law. Civil and Infrastructural Engineers need to have a working knowledge of the land laws that affect their
work and that will enable them to comply with local, state & national regulations; understand the boundaries of their
personal and p rofessional liability; negotiate contracts; protect their intellectual property; develop a relationship with
a law firm that understands the engineering business.
Objectives
1. To understand and explain the registration act and coastal regulations zones.
2. To provide knowledge of the urban land act & the land acquisition act.
3. To understand Maharashtra stamp act & the development control regulations.
4. To understand the MHADA and MahaRERA act.
5. To study Maharashtra Regional Town Planning Act.
6. To study the Maharas htra Land Revenue Code.
Detailed Syllabus
Module Course Module / Contents Periods
A CENTRAL LEGISLATION
1 The Registration Act, 1908 & The Environment (Protection) Act, 1986 – Coastal Regulation
Zones (CRZ) 08
1.1 The Registration Act, 1908: Introduction, definitions, documents, time limit for registration
and effects of non -registrations of documents.
1.2 The Environment (Protection) Act, 1986 – Coastal Regulation Zones (CRZ): Areas covered,
prohibited and regulated activities and classification of CRZ.
2 The Urban Land (Celling and Regulation) Act, 1976 & The Land Acquisition Act, 1894 09
2.1 The Urban Land (Celling and Regulation) Act, 1976: Introduction and repeal, definitions,
celling limits on vacan t lands and power to exempt and retention of excess vacant land

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2.2 The Land Acquisition Act, 1894: General, introduction and definitions, acquisition of land,
reference to the court, miscellaneous provisions and case law.
Land Records documents i.e. 7x12 abstract, 8A, Ferfar, property card, Gut book. CTS Plan
B STATE LEGISLATION
3 Maharashtra Stamp Act, 1958 & The Development Control Regulations (DCR), 1991 07
3.1 Maharashtra Stamp Act, 1958: Constitutional provisions, objects & summary of the act,
payment of stamp duty, adjudication of stamp duty, impounding of instruments,
admissibility of instrument and prosecution for stamp law offences.
3.2 The Development Control Regulations (DCR), 1991: Floor Space Index (FSI), transfer of
development rights (TDR), heritage buildings and precincts.
4 The Maharashtra Housing & Area Development Act (MHADA), 1976 & Maharashtra's Real
Estate (Regulation and Development) Act, 2016 (MahaRERA) 14
4.1 The Maharashtra Housing & Area Development Act (MHADA), 1976: Definitions, powers
& duties of the Mumbai repairs and reconstruction board, levy and collection of cess,
structural repairs, acquisition of cessed properties for cooperative societies.
4.2 Maharashtra's Real Estate (Regulation and Development) Act, 2016 (MahaRERA):
Introduction, regulatory framework, registration of real estate project and registration of
real estate agents, functions and duties of promoter, rights and duties of allottees, th e real
estate regulatory authority, central advisory council, offences, penalties and adjudication,
FAQ’s.
5 Maharashtra Regional Town Planning (MRTP) Act, 1966
04 5.1 Introductory & definitions, control of development, unauthorized development and
acquisition of land.
6 Maharashtra Land Revenue Code, 1966
10 6.1 Introduction, use of land, removal & regularisation of encroachments, grant of sanad,
record of rights, rights in unoccupied land, appeals, revision and review
6.2 Special provisions for land revenue in Bombay city: general, assessment and collection of
land revenue, Bombay city survey & boundary marks, government lands and foreshore,
transfer of lands.
Total 52

Contribution to Outcome
After the completion of the course the student should be able to:
1. Understand the functionality of the registration act and coastal regulations zones as per central regulations of India.
2. Analyse and integrate functionality of the urban land act & the land acquisition act in India.
3. Explain Maharashtra Stamp Act & the development control regulations.
4. Understand the MHADA and MahaRERA act.
5. Understand Maharashtra Regional Town Planning Act.
6. Familiarise with the Maharashtra Land Revenue Code.
Internal Assessment (20 Marks):
Consisting Two Comp ulsory Class Tests

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115
First test based on approximately 40% of contents and second test based on remaining contents (approximately 40% but
excluding contents covered in Test I)
End Semester Examination (80 Marks):
Weightage of each module in end semester examination will be proportional to number of respective lecture hours
mentioned in the curriculum.
1. Question paper will comprise of total six questions , each carrying 20 marks.
2. Question 1 will be compulsory and sho uld cover maximum contents of the curriculum
3. Remaining questions will be mixed in nature (for example if Q.2 has part (a) from module 3 then part (b) will be
from any module other than module 3)
4. Only Four questions need to be solved .


Recommended & Reference Books:
1. MahaRERA Act, The Real Estate (Regulation and Development) Act, 2016 and Rule 2017 - Y. M. Agarwala, Adv. A. B.
Shah; Aarti & Company's Publications
2. Land Law – Prof. H.D. Pithawalla; C. Jamndas & Co.
3. Maharashtra Land Laws by D N Mathur, Central Law Publications
4. Land Laws in Maharashtra by Sunil Dighe, Snow White Pub. P Ltd
5. Land Laws by Abhay Shah; Aarti & Company's Publications
6. Land Law (Law and Real Estate Laws) by Krishan Keshav; Singhal’s Publications
7. Land Laws (Including Land Acquisition and Rent Laws) by Kanwal D.P. Singh; Satyam Law International
_______________________*****______________________





















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Infrastructure Policies & Regulations : Semester -VII
Course Code Course Name Credits
HIPC 701 Infrastructure Finance & Business Policies 04

Contact Hours Credits Assigned
Theory Practical Tutorial Theory Practical Tutorial Total
04 - - 04 - - 04
Theory Term Work/Practical/Oral
Total Internal Assessment End
Sem
Exam Duration of End
Sem Exam TW PR OR Test -I Test -II Average
20 20 20 80 3 hrs. -- - - 100

Rationale
Looking at India's exponential growth with the infrastructure space teeming with activity and the government as well as
the private sector heavily investing in the creation of better infrastructure both in terms of its business and with an eye
on its longevity, this course will prove to be a holy grail for students considering the aspects of business law. The course
will provide an overview of the underlying legal framework f or doing business in India including Constitutional Acts,
Companies Act and other relevant statutes. The course will familiarize students with the sector specific legislation, the
constitutional, general legal context, regulatory law, where it exists. The course intends to enable each student to have
knowledge of fundamental tools of legal research and application of the same in development of the infrastructure sector.
Objectives
1. To highlight the business environment, forms of business, scale of business and emerging trends in business.
2. To describe about the general legal environment and framework in India.
3. To provide an overview of Indian Constitutional Acts, Companies Act and other relevant statutes.
4. To define & interpret the financing of infrastructure and growth of PPP (Public Private Partnership) in various sectors
of Infrastructural development.
5. To understand preconstruction and post construction processes involved in infrastructural projects/contracts.
6. To examine the details of Project Financing in Infrastructure Contracts.

Detailed Syllabus
Module Course Modules / Contents Hours
1 Business Environment 8
Types of Business Environment, Forms of Business Organization, Concept and Features in
relation to following business models - Sole Proprietorship; Partnership, Company; Statutory
Bodies and Corporations; HUF and Family Business. Scales of Business, Micro, Small and Medium
Enterprises; Large Scale Enterprises and Public Enterprises; MNC’s Emerging Trends in Business,
Concepts, Advantag es and Limitations -Franchising, Aggregators, Business Process Outsourcing
(BPO)& Knowledge Process Outsourcing (KPO); E -Commerce, Digital Economy.
2 Legal Environment of Business in India 10
Introduction to Bills, Laws/Acts, Rules, Regulations, and associated legal reasoning and
procedures, Introduction to Constitution and Constitutional Law. Stakeholders including legal

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system covering judicial, quasi -judicial authorities & Constitutional Aut horities etc. and other
Advisory Boards/entities. Outline the intent of Business Allocation of Rules of Government (e.g.
Departments in States and Ministries at the Centre)
3 Acts, Statutes and Regulation 10
Introduction to various Acts and their key provisions, such as Indian Companies Act - 2013,
Negotiable Instruments Act, Industrial Dispute Act, Minimum Wages Act, Special Relief Act,
Transfer of property act, Right to fair compensation & transparency in Land Acquisition,
Rehabilitation and Resettlem ent Act, 2013, Income Tax Act.
4 Infrastructure Contracts 8
Introduction and Features of Infrastructure contracts, Introduction to PPP in India, PPP Models
in India, Contracts in PPP model
Principles of contract -essential conditions, Void & voidable contract, capacity & consideration,
types & terms of contracts (in accordance with Indian Contract Act 1872); Performance and
discharge of contract; breaches of contracts and remedies; introduction to special contracts
such as contract of indemnity, guaran tee, leasing agreement.
5 Infrastructure Project Contracts 8
Parties in Infrastructure Contracts, Bidding Process, Negotiation of Infrastructure Project
Management Contracts, Allotment of Contracts, Drafting EPC & Concession Agreements, Project
Appraisal, Compliances and Due Diligence.
6 Project Financing in Infrastructure Contracts 8
Introduction to project financing, Equity and corporate debt financing, Stages in Project
Financing, Regulatory Framework and Authorities, Borrowing from International financial
institutions, FDI in Infrastructure developments, Documentation in Project Financing,
Restructuring in project finance transactions, Case Studies on Infrastructure Project
Management
Total 52
Contribution to Outcome

On completion of this course, the students will be able to:
1. Explain the concepts related to Business environment
2. Elaborate the general legal environment and framework in India
3. Understand the acts, statutes and their regulation involved in infrastructure projects
4. Apply models of infrastructure development on respective projects in PPP
5. Understand preconstruction and post construction processes involved in infrastructural projects/contracts .
6. Define and interpret the financing of Infrastructure Contracts.
Internal Assessment (20 Marks):
Consisting Two Compulsory Class Tests
First test based on approximately 40% of contents and second test based on remaining contents (approximately 40%
but excluding contents covered in Test I)

End Semester Examination (80 M arks):

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Weightage of each module in end semester examination will be proportional to number of respective lectures hours
mentioned in the curriculum.
1. Question paper will comprise of total six questions , each carrying 20 marks.
2. Question 1 will be compulsory and should cover maximum contents of the curriculum
3. Remaining questions will be mixed in nature (for example if Q.2 has part (a) from module 3 then part (b) will be
from any module other than module 3)
4. Only Four questions need to be solved .


Recommended Books:
1. Satyanarayana, G. (2017). Infrastructure Development & the Role of Public -PrivatePartnership. 1st ed. New Delhi,
India: New Century Publications.
2. Piyush Joshi(2003), Law Relating to Infrastructure Projects, New Delhi: Butterworths.
3. N.D. Kapoor &DinkarPagare Business Laws and Management; Sultan Chand & Sons.
4. P. P. S. Gogna A Textbook of Business Law; Sultan Chand & Company, New Delhi.
5. Poonam Gandhi Business Studies; Dhanpat Rai & Company Private Limited, Delhi.
6. Willie Tan, (2007). Pri nciples of Project and Infrastructure Finance, 1 edition. Routledge;
7. Hoffman, Scott L., (2007). The Law and Business of International Project Finance, 3rd Edition, London: Cambridge
University Press.
8. Vinter, Graham (2013) Project Finance, 4th Edition, Lon don: Sweet and Maxwell.
9. Gajendra Haldea, (2011). Infrastructure at Crossroads: The Challenges of Governance, Oxford University Press; 1st
ed edition
10. Dewar, John (2015) International Project Finance: Law and Practice, 2nd Edition, Oxford University Press
11. Mulla, D.F., The Indian Contract Act, 13th Ed., LexisNexis/Butterworths
12. Tripathi, S.C., Modern Company Law, 5th Ed., Central Law Publications
13. I.P Massey (2008), Administrative Law, Lucknow: Eastern Book Company.
14. D D Basu (2009), The Constitutional Law of India, New Delhi: Lexis Nexis Butterworths.
Reference Books:
1. Sen & Mitra Commercial Law; The World Press Pvt. Ltd., Calcutta.
2. Ian Wirthington & Chris Britton The Business Environment; Pearson Education Ltd., England.
3. Raymond W.Y. Kao Entrepreneurship and Enterprises Development
_______________________*****______________________






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Infrastructure Policies & Regulations : Semester -VII
Course Code Course Name Credits
HIPSBL 701 Infrastructure Finance & Business Policies (Lab) 02

Contact Hours Credits Assigned
Theory Practical Tutorial Theory Practical Tutorial Total
- 04 - - 02 - 02

Theory Term Work/Practical/Oral
Total Internal Assessment End
Sem
Exam Duration of End
Sem Exam TW PR OR Test -
I Test -II Average
- - - - - 50 - 50 100

Objectives

1. To study the business environment and emerging trends in business.
2. To learn the general legal environment followed for infrastructure projects in India.
3. To provide detail overview of land acquisition, rehabilitation and redevelopment of infrastructure.
4. To explain emerging sectoral growth of PPP (Public Private Partnership) in various sectors of infrastructural
development.
5. To develop contracts and agreements with various stakeholders related to infrastructure projects.
6. Examine the intric acies of Project Financing in Infrastructure Contracts.

Module Detailed Contents (Any Six) Lab
Sessions/Hr
1 To prepare a case study report of Knowledge Process Outsourcing (KPO) related to
infrastructure -based company. 4
2 To prepare a case study report of Business Process Outsourcing (BPO) related to
infrastructure -based company. 4
3 To prepare a case study report based on legal environment of business in India. 4
4 To prepare a case study report based on land acquisition and rehabilitation (eg. Sardar
Sarovar). 4
5 To prepare a case study report of PPP in one of the sectors of Infrastructural
development. 4
6 Prepare a sample draft of EPC contracts enlisting all the necessary elements for
infrastructure project. 4
7 To prepare a case study re port of business model applying key parameters in project
financing. 4
8 To prepare a case study report highlighting the important features of slum
rehabilitation (eg. SRA project). 4
9 To prepare a case study report based on mega redevelopment projects in India (eg.
BDD chawl). 4

Lab Outcomes

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Learner will be able to…
1. Explain the business environment and emerging trends in business.
2. Elaborate the general legal environment followed for infrastructure projects in India.
3. Apply intricacies of land acquisition, rehabilitation and redevelopment of infrastructure.
4. Apply emerging techniques related to PPP (Public Private Partnership) in various sectors of infrastructural
development.
5. Build contracts and agreements with various stakeholders related to In frastructure projects.
6. Define the intricacies of project financing in infrastructure contracts.

End Semester Oral Examinations:
Oral exam will be based on laboratory work performed (case study report).
Recommended Books:
1. Satyanarayana, G. (2017). Infrastructure Development & the Role of Public -Private Partnership. 1st ed. New Delhi,
India: New Century Publications.
2. Piyush Joshi(2003), Law Relating to Infrastructure Projects, New Delhi: Butterworths.
3. N. D. Kapoor & Dinkar Pagare Business Laws and Ma nagement; Sultan Chand & Sons.
4. P. P. S. Gogna A Textbook of Business Law; Sultan Chand & Company, New Delhi.
5. Poonam Gandhi Business Studies; Dhanpat Rai & Company Private Limited, Delhi.
6. Willie Tan, (2007). Principles of Project and Infrastructure Finance, 1 edition. Routledge;
7. Hoffman, Scott L., (2007). The Law and Business of International Project Finance, 3rd Edition, London: Cambridge
University Press.
8. Vinter, Graham (2013) Project Finance, 4th Edition, London: Sweet and Maxwell.
9. Gajendra Haldea , (2011). Infrastructure at Crossroads: The Challenges of Governance, Oxford University Press; 1st
ed edition
10. Dewar, John (2015) International Project Finance: Law and Practice, 2nd Edition, Oxford University Press
11. Mulla, D. F., The Indian Contract Act, 1 3th Ed., LexisNexis/Butterworths
12. Tripathi, S.C., Modern Company Law, 5th Ed., Central Law Publications
13. I. P. Massey (2008), Administrative Law, Lucknow: Eastern Book Company.
14. D. D. Basu (2009), The Constitutional Law of India, New Delhi: Lexis Nexis But terworths
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Infrastructure Policies & Regulations : Semester -VIII
Course Code Course Name Credits
HIPC801 Arbitration & Conciliation

Contact Hours Credits Assigned
Theory Practical Tutorial Theory Practical Tutorial Total
4 - - 4 - - 4

Theory Term Work/Practical/Oral
Total Internal Assessment End
Sem
Exam Duration of End
Sem Exam TW PR OR Test -I Test -II Average
20 20 20 80 03 -- - - 100

Rationale

The Arbitration and Conciliation concept has been modelled on lines of the UNCITRAL (United Nations Commission on
International Trade Law) framework of laws with the idea to modernize Indian arbitration law and bring it in line with
the best global practic es and also make India a global hub for arbitration. Arbitration and conciliation play significant
role in construction industry due to disputes arising on large scale construction projects. Alternative Dispute Resolution
(ADR) mechanism provides scientifi cally developed techniques to Indian judiciary. ADR provides various modes of
settlement including arbitration, conciliation, mediation, negotiation, etc. This course deals with introduction to
arbitration and conciliation, there requisites, rules, proceed ings, roles of individuals, etc.
Objectives

1. To understand the importance of arbitration in resolving disputes in construction infrastructure industry.
2. To study the constitution of arbitral tribunal in the process of arbitration.
3. To study the procedures and conduct of arbitral proceedings.
4. To understand the making of arbitral award & termination of proceedings.
5. To study the significance and concepts of conciliation.
6. To study of the alternative means of settlement of disputes with negotiations.
Detailed Syllabus

Module Course Modules / Contents Hours

1 Arbitration
09 Arbitration and its significance in construction industry, Role of arbitrator, The Construction
Industry Arbitration Commission (CIAC), Arbitration agreement - Form, constitution, Guarantor
to agreement, Interim measures by court, Arbitral award, Arbitral tribunal, International
commercial arbitration, legal representative, Scope of arbitration, Arbitral disputes, the
arbitration & conciliation act 1996 - Consolidating & amendment ac t, provisions, preamble &
its purpose.
2 Composition of Arbitral Tribunal 09

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Arbitrator, No. of arbitrator, Agreement providing two arbitrators, Appointment of arbitrator,
Appointment of international commercial arbitrator, appointment of sole arbitrator, objection
to nationality of arbitrator, Selection of arbitrator, appointment of arbitrator by court,
Removal of arbitrator, Grounds for challenge, challenge procedure, Termination and
substitution of mandate of arbitrator, insolvency notice.
3 Conduct of Arbitral Proceedings
06 Equal treatment of parties, Determination of rules of procedure - English law, Indian law, Place
of arbitration, Commencement of arbitral proceedings, Statement of claim and defense, Expert
appointment by arbitral tribunal,
4 Making of Arbitral Award & Termination of Proceedings
06 Rules applicable to substance of disputes, decision making by panel of arbitrators, Settlement,
Form and contents of arbitral award, Termination of proceedings, Correction and
interpr etation of award, Additional award
5 Conciliation
Application and scope, commencement of proceedings, Appointment of conciliation, Role of
conciliator, sole conciliator, Communication between conciliator and parties, Settlement
agreement - Concept, status and effect, Confidentiality, Termination of proceedings, costs,
Deposits, Role of conciliator in other proceedings, Difference between conciliation and
mediation.
ICC Rules of Conciliation and arbitration, Rules of arbitration of the Indian council of
arbitration. 13
6 Alternative Means of Settlement of Disputes (ADR)
Introduction, Methods, merits, demerits, Indian statutes, Difference between mediation and
arbitration, Mediator and its necessity, Rules and Limitation of mediation, mediator’s
settlement.
Negotiation - Necessity, state of negotiation, power sources, , styles, kinds of approaches,
qualities of negotiation power, Obstructions to negotiation, Trade unions and negotiation. 09
Total 52

Contribution to Outcome
On completion of this course, the students will be able to:
1. Appraise the significance and concepts of arbitration in resolving disputes in construction infrastructure industry.
2. Explain the intricacies of constitution of arbitral tribunal in the process of arbitration.
3. Value the importance of the procedures and conduct of arbitral proceedings.
4. Comply the making of arbitral award & termination of proceedings.
5. Compare and study the significance and concepts of conciliation and mediation.
6. Apply the process of alternative means of settlement of disputes with negotiations.

Internal Assessment (20 Marks):
Consisting Two Compulsory Class Tests

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First test based on approximately 40% of contents and second test based on remaining contents (approximately 40%
but excluding contents covered in Test I)
End Semester Examination (80 Marks):
Weightage of each module in end semester examination will be proportional to number of respective lecture hours
mentioned in the curriculum.
1. Question paper will comprise of total six questions , each carrying 20 marks.
2. Question 1 will be compulsory and should cover maximum contents of the curriculum
3. Remaining questions will be mixed in nature (for example if Q.2 has part (a) from module 3 then part (b) will
be from any module other t han module 3)
4. Only Four questions need to be solved .


Recommended Books:
1. Dr. S C Tripathi (2012), The Arbitration and Conciliation Act, 1996, 6th Edn. Central Law Publication.
2. Dr. Rega Surya Rao. (2021), Lextures on Arbitration, Conciliation and ADR Systems, Andhra Law House.
3. Dr. Harman Shergil Sullar (2021), Alternative Dispute Resolution - Including Arbitration Conciliation Act, 1996
Amended Amendment Act, 4th Edn., Shreeram Law House Publication.
4. H C Johari Edi tion, A Guide to Arbitration and Conciliation Act, 1996 (2022), Kamal Law House.
5. Rahul Ranjan (2020), Alternative Dispute Resolution Arbitration, Conciliation, Negotiation and Mediation, 2022
Edn., Proflic Publication.
6. Madhusudan Saharay, Textbook on Arbi tration & Conciliation with Alternative Dispute Resolution, 4th Edn.,
Universal Law Publishing.
7. Dr. Anupam Kurlwal (2017), An Introduction to Alternative Dispute Resolution, 3rd Edn., Central Law Publications.
Reference Books:
1. P. C. Markanda, Naresh Marka nda & Rajesh Markanda (2020), Law Relating to Arbitration and Conciliation, 10th
Edn., LexisNexis.
2. Abraham P. Ordover & Andrea Doneff (2002), Alternatives to Litigation: Mediation, Arbitration, and the Art of
Dispute Resolution, 2nd Edn., LexisNexis / Nati onal Institute for Trial Advocacy Publication.
3. Elkouri & Elkouri (2003), How Arbitration Works, Bna Books Publications, Edison, New Jersey, USA.


















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124




University of Mumbai





Syllabus for

Honours /Minor Degree Program
In
Blockchain



FACULTY OF SCIENCE & TECHNOLOGY

(As per AICTE guidelines with effect from the academic year 2022 -2023)





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125









University of Mumbai
Blockchain
(With effect from 2022 -23)
Year &
Sem
Course Code and
Course Title Teaching
Scheme Hours / Week Examination Scheme and Marks Credit
Scheme
Theory Seminar/
Tutorial Pract Internal
Assess
ment End
Sem
Exam Term
Work Oral Total Credits

TE
Sem
V HBCC501:
Bit coin and Crypto
currency 04 -- -- 20 80 -- -- 100 04
Total 04 - -- 100 - - 100 04
Total Credits = 04

TE
Sem.
VI HBCC601:
Blockchain
Platform 04 -- -- 20 80 -- -- 100 04
Total 04 - - 100 - - 100 04
Total Credits = 04


BE
Sem.
VII HBCC701:
Block chain
Development 04 -- -- 20 80 -- -- 100 04
HBCSBL7 01:
Private Blockchain
Setup Lab(SBL) -- -- 04 -- -- 50 50 100 02
Total 04 - 04 100 50 50 200 06
Total Credits = 06

BE
Sem.
VIII
HBCC801:
DeFi
(Decentralized
Finance) 04 - -- 20 80 -- -- 100 04
Total 04 - - 100 - - 100 04
Total Credits = 04

Total Credits for Semesters V,VI, VII &VIII = 04+04+06+04=18

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126

Course
Code Course Title Examination Scheme
Theory Marks
Term
Work Practical Oral Total Internal assessment End
Sem.
Exam Test1 Test 2 Avg.
HBCC501
Bit coin and
Crypto currency 20 20 20 80 -- -- -- 100

Course Objectives:
Sr. No. Course Objectives
The course aims:
1 To get acquainted with the concept of Block and Blockchain.
2 To learn the concepts of consensus and mining in Blockchain.
3 To get familiar with the bitcoin currency and its history.
4 To understand and apply the concepts of keys, wallets and transactions in the Bitcoin Network.
5 To acquire the knowledge of Bitcoin network, nodes and their roles.
6 To analyze the applications& case studies of Blockchain.

Course Outcomes:
Sr. No. Course Outcomes Cognitive levels of
attainment as per
Bloom’s Taxonomy
On successful completion, of course, learner/student will be able to:
1 Describe the basic concept of Block chain. L1,L2
2 Associate knowledge of consensus and mining in Block chain. L1,L2
3 Summarize the bit coin crypto currency at an abstract level. L1,L2
4 Apply the concepts of keys, wallets and transactions in the Bit coin network. L3
5 Interpret the knowledge of Bit coin network, nodes and their roles. L1,L2
6 Illustrate the applications of Block chain and analyze case studies. L3

Detailed S yllabus:
Sr.
No. Module Detailed Content Hours CO
Mapping
0 Prerequisite Introduction to Cryptography: Hash functions, Public key
cryptography, Digital Signature (ECDSA). 2 --
I Introduction
to Block
chain Structure of a Block, Block Header, Block Identifiers: Block Header
Hash and Block Height, The Genesis Block, Linking Blocks in the
Block chain, Merkle Trees and Simplified Payment Verification
(SPV).
Self-learning Topics: Block chain Demo. 6 CO1 Blockchain: Sem V
Course
Code Course Title Theory Practical Tutorial Theory Practical Tutorial Total
HBCC501 Bit coin and
Crypto currency 04 -- -- 04 -- -- 04

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127
II Cons ensus
and Mining Decentralized Consensus, Byzantine General’s Problem,
Independent Verification of Transactions, Mining Nodes,
Aggregating Transactions into Blocks, Constructing the Block
header, Mining the Block, Successfully Mining the Block,
Validating a New Block, Assembling and Selecting Chains of Blocks,
Block chain Forks
Self-learning Topics: Study different consensus algorithms 12 CO2
III Introduction
to Bit coin What is Bit coin and the history of Bit coin, Getting the first bit
coin, finding the current price of bit coin and sending and receiving
bit coin, Bit coin Transactions.
Self-learning Topics: Study the website coinmarketcap.com/ 4 CO3
IV Concepts of
Bit coin Keys and addresses, Wallets and Transactions: Public Key
Cryptography and Crypto currency, Private and Public Keys, Bit
coin Addresses, Base58 and Base58Check Encoding,
Nondeterministic (Random) Wallets, Deterministic (Seeded)
Wallets, HD Wallets (BIP -32/BIP -44), Wallet Best Practices, Using
a Bit coin Wallets, Transaction Outputs and Inputs, Transaction
Fees, Transaction Scripts and Script Language, Turing
Incompleteness, Stateless Verification, Script Construction (Lock +
Unlock), Pay -to-Public -Key-Hash (P2PKH), Bitcoin Addresses,
Balances, and Other Abstractions
Self-learning Topics : Visit and use https://bitcoin.org/en/ 13 CO4

V Bit coin
Networks Peer -to-Peer Network Architecture, Node Types and Roles,
Incentive based Engineering The Extended Bitcoin Network,
Bitcoin Relay Networks, Network Discovery, Full Nodes,
Exchanging “Inventory”, Simplified Payment Verification (SPV)
Nodes, Bloom Filters, SP V Nodes and Privacy, Encrypted and
Authenticated Connections, Transaction Pools
Self-learning Topics: Study techni cal papers based on bitcoin
security 7 CO5
VI Blockchain
Applications
& case
studies Domain -Specific Applications: FinTech, Internet of Things,
Industrial and Manufacturing, Energy, Supply chain & Logistics,
Records & Identities, Healthcare
Case studies related to cryptocurrencies
Concept of Altcoin
Self-learning Topics: Read Technical papers on blockchain
applications 8 CO6

Text Books:
1. “Mastering Bitcoin, PROGRAMMING THE OPEN BLOCKCHAIN” , 2nd Edition by Andreas M. Antonopoulos, June 2017,
O'Reilly Media, Inc. ISBN: 9781491954386.
2. “Blockchain Applications: A Hands -On Approach”, by Ars hdeepBahga, Vijay Madisetti, Paperback – 31 January 2017.
3. “Bitcoin and Cryptocurrency Technologies: A Comprehensive Introduction”, July 19, 2016, by Arvind Narayanan,
Joseph Bonneau, Edward Felten, Andrew Miller, Steven Goldfeder, Princeton University Press.

Reference Books:
1. “Mastering Blockc hain”, by Imran Bashir, Third Edition, Packt Publishing
2. “Mastering Ethereum: Building Smart Contracts and Dapps Paperback” byAndreas Antonopoulos , Gavin Wood ,
Publisher(s): O'Reilly Media

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128
3. “Blockchain revolution: how the technology behind bitcoin is changin g money, business and the world $ don
tapscott and alex tapscot, portfolio penguin, 856157449
Online References:
Sr. No. Website Name
1 https://andersbrownworth.com/blockchain/
2 https://andersbrownworth.com/blockchain/public -private -keys/
3 https://www.coursera.org/learn/cryptocurrency
4 https://coinmarketcap.com/

Assessment:
Internal Assessment (IA) for 20 marks:
 IA will consist of Two Compulsory Internal Assessment Tests. Approximately 40% to 50% of syllabus
content must be covered in First IA Test and remaining 40% to 50% of syllabus content must be covered in
Second IA Test
 Question paper format
 Question Paper will comprise of a total of six questions each carrying 20 marks Q.1 will be compulsory
and should cover maximum contents of t he syllabus
 Remaining questions will be mixed in nature (part (a) and part (b) of each question must be from
different modules. For example, if Q.2 has part (a) from Module 3 then part (b) must be from any other
Module randomly selected from all the module s)
 A total of four questions need to be answered























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129

Course
Code Course Title Examination Scheme
Theory Marks
Term
Work Practical Oral Total Internal assessment End
Sem.
Exam Test1 Test 2 Avg
HBCC601 Block chain
Platform 20 20 20 80 -- -- -- 100

Course Objectives:
Sr. No. Course Objectives
The course aims:
1 Understand the blockchain platform and its terminologies.
2 Understand smart contracts, wallets, and consensus protocols.
3 Design and develop decentralized applications using Ethereum, and Hyperledger.
4 Creating blockchain networks using Hyperledger Fabric deployment.
5 Understand the considerations for creating blockchain applications.
6 Analyze various Blockchain Platforms.

Course Outcomes:
Sr. No. Course Outcomes Cognitive levels of
attainment as per
Bloom’s Taxonomy
On successful completion, of course, learner/student will be able to:
1 Explain the Blockchain platform and its types. L1,L2
2 Create Public Blockchain using Ethereum. L3,L4,L5, L6
3 Develop Smart Contracts using REMIX IDE. L3,L4,L5
4 Apply the concept of private blockchain using Hyperledger. L3
5 Analyze different types of blockchain platforms. L3,L4
6 Deploy Enterprise Applications on Blockchain. L3,L4,L5

DETAILED SYLLABUS:
Sr.
No. Module Detailed Content Hours CO
Mapping
0 Prerequisite Introduction to Block chain and Bit coin, 2 --
I Introduction
to Block
chain
Platforms Why Blockchain Platform: Platform types, Public, Private,
technology requirements for implementation.
Introduction to Ethereum, Hyperledger and Smart Contracts. Case
study of blockchain Application.
Self-learning Topics: Study different applications of block chain. 6 CO1 Blockchain: Sem VI
Course Code Course Title Theory Practical Tutorial Theory Practical Tutorial Total
HBCC601 Block chain
Platform 04 -- -- 04 -- -- 04

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130
II Public Block
chain Introduction, Characteristics of Public Blockchain, Advantages.
Examples of Public Blockchain -Bitcoin: Terminologies and
Transaction, Ethereum: Smart contract, Comparison of Bitcoin and
Ethereum, Other public Blockchain platforms.
Self-learning Topics: Study any one case study on public block
chain. 8 CO2, CO3
III Ethereum
Blockchain Introduction, Ethereum and Its Components: Mining, Gas,
Ethereum, Ether, Ethereum Virtual Machine, Transaction,
Accounts.
Architecture of ethereum, Smart Contract: Remix IDE, Developing
smart contract for ethereum blockchain, e -voting applications
using smart contract, Dapp Architecture .
Types of test -networks used in ethereum, Transferring Ethers
Using MetaMask, Mist Wallet, Ethereum Frameworks, Case study
of Ganache for ethereum blockchain. Deploying e -voting
applications on Ganache framework.
Ethereum 2., Concept of Beacon chain, POS (Proof of Stake),
Shading of Chain.

Self-learning Topics: Study case study on any ethereum
blockchain. 12 CO2, CO3,
CO6
IV Private
Blockchain Introduction, Key Characteristics, Need of Private Blockchain.
Consensus Algorithm for private Blockchain (Ex. R AFT and PAXOS),
Smart Contract in Private Blockchain, Case Study of E -commerce
Website, Design Limitations.

Self-learning Topics: Case study on private block chain. 8 CO4

V Hyperledger
Blockchain Introduction to Hyperledger, tools and frameworks, Hyperledger
Fabric, Comparison between Hyperledger Fabric & Other
Technologies, Distributed Ledgers.
Hyperledger Fabric Architecture, Components of Hyperledger
Fabric: MSP, Chain Codes etc., Transaction Flow, Advantages of
Hyperledger Fabric Blockchain, wo rking of Hyperledger Fabric,
Creating Hyperlegder network, Case Study of Supply chain
management using Hyperledger

Self-learning Topics: Case study on Hyperledger blockchain. 12 CO5, CO6
VI Other
Blockchain
platforms Corda, Ripple, Quorum and other emerging blockchain platforms,
Case Study on any of the blockchain platforms.
Developing Blockchain application on Cloud(AWS/Azure)
Self-learning Topics: Compare different blockchain platforms. 4 CO5
Text Book:
1) Blockchain Technology, Chandramouli Subramanian, Asha A George, Abhillash K. A and MeenaKarthikeyen,
Universities press.
2) Mastering Ethereum, Building Smart Contract and Dapps, Andreas M. Antonopoulos Dr. Gavin Wood, O'reilly.
Reference Books:
1) Blockchai n for Beginners, Yathish R and Tejaswini N, SPD
2) Blockchain Basics, A non Technical Introduction in 25 Steps, Daniel Drescher, Apress.

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131
3) Blockchain with Hyperledger Fabric, LucDesrosiers , Nitin Gaur , Salman A. Baset , Venkatraman Ramakrishna , Packt
Publishing
E Books:
1) Blockchain By Example, BellajBadr, Richard Horrocks, Xun (Brian) Wu, November 2018, Implement decentralized
blockchain applications to build scalable Dapps.
2) Blockchain for Business, https://www.ibm.com/downloads/cas/3EGWKGX7 .
Online References:
Sr. No. Website Name
1. https://www.hyperledger.org/use/fabric

Assessment:
Internal Assessment (IA) for 20 marks:
 IA will consist of Two Compulsory Internal Assessment Tests. Approximately 40% to 50% of syllabus
content must be covered in First IA Test and remaining 40% to 50% of syllabus content must be covered in
Second IA Test
 Question paper format
 Question Paper will comprise of a total of six questions each carrying 20 marks Q.1 will be compulsory
and should cover maximum contents of the syllabus
 Remaining questions will be mixed in nature (part (a) and part (b) of each question must be from
different modules. For example, if Q.2 has part (a) f rom Module 3 then part (b) must be from any other
Module randomly selected from all the modules)
 A total of four questions need to be answered


















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132

Course
Code Course Title Examination Scheme
Theory Marks
Term
Work Practical Oral Total Internal assessment End
Sem.
Exam Test1 Test 2 Avg
HBCC701 Block chain
Development 20 20 20 80 -- -- -- 100

Course Objectives:
Sr. No. Course Objectives
The course aims:
1 To understand Ethereum Ecosystem.
2 To understand aspects of different programming languages.
3 To explain how to use the solidity programming language to develop a smart contract for blockchain.
4 To demonstrate deployment of smart contracts using frameworks.
5 To understand principles of Hyperledger fabric.
6 To understand challenges to apply blockchain in emerging areas.

Course Outcomes:
Sr.
No. Course Outcomes Cognitive levels of
attainment as per
Bloom’s Taxonomy
On successful completion, of course, learner/student will be able to:
1 To use Ethereum Components. L1,L2
2 To a nalyse different blockchain programming languages. L3
3 To implement sma rt contract in Ethereum using solidity. L4,L5
4 To analyse different development frameworks. L4
5 To implement private blockch ain network with Hyperledger fabric. L4,L5
6 To illustrate blockchain integration with emerging technologies and security issues. L1,L2

DETAILED SYLLABUS:
Sr. No. Module Detailed Content Hours CO
Mapping
0 Prerequisite Blockchain cryptocurrency, Blockchain platform 2 --
I Ethereum
Ecosystem Ethereum components: miner and mining node, Ethereum
virtual machine, Ether, Gas, Transactions, accounts, swarm and
whisper, Ethash, end to end transaction in Ethereum,
architecture of Ethereum
Self-learning Topics : Emerging blockchain platforms 4 CO1
II Blockchain
Programming Types of Blockchain Programming, Solidity, GoLang, Vyper, Java,
Simplicity, Rholang, Game Theory and Cryptonomics, 8 CO2 Blockchain: Sem VII
Course
Code Course Title Theory Practical Tutorial Theory Practical Tutorial Total
HBCC701 Blockchain
Development 04 -- -- 04 -- -- 04

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133
Comparative study of different blockchain programming
languages
Decentralized file system -IPFS.
Self-learning Topics: Emerging blockchain pro gramming
languages
III Smart
Contract Solidity programming, Smart Contract programming using
solidity, mapper function, ERC20 and ERC721 Tokens,
comparison between ERC20 & ERC721, ICO, STOMetamask
(Ethereum Wallet), setting up development environment, use
cases of smart contract, smart Contracts: Opportunities, Risks
Self-learning Topics: Cryptocurrencies and their security issues,
Consensus mechanisms, Digital Signatures 10 CO3
IV Blockchain
Deployment Ethereum client, Ethereum Network, Introduction to Go
Ethereum (Geth), Geth Installation and Geth CLI, Setting up a
Private Ethereum Blockchain. Introduction to Truffle, Smart
Contract deployment on a Private Blockchain. Introduction to
Ganache
Introduction to Dapp, Dapp architecture, Daaps Scalability,
testing
Connecting to the Blockchain and Smart Contract, Web3js,
Deployment

Self-learning Topics: Smart Contract deployment using
Ganache. 10 CO4
V Hyperledger
Application
Development Installing Hyperledger Fabric, Hyperledger Fabric Network ,
Building Your First Network, Hyperledger Fabric Demo,
Hyperledger Fabric Network Configuration, Certificate
Authorities, Chaincode Development and Invocation,
Deployment and testing of chaincode on development network,
Hyperledger Fabric Transactions
Self-learning Topics: Hyperledger sawtooth,Hyperledger caliper 12 CO5
VI Blockchain
integration
and Research
challenges Integrating Blockc hain with cloud, IoT, AI, ERP, End to end
blockchain integration, Risks and Limitations of Blockchain:
Privacy & Security. Criminal Use of Payment Blockchains, The
“Dark” Side of Blockchain
Research challenges in blockchain, Self-learning Topics : Use
Cases: Blockchain for Health Insurance, Blockchain in Supp ly
chain management, Blockchain & PropTech, Blockchain in
Banking 6 CO6

Text Books:
1. Mastering Ethereum, Building Smart Contract and Dapps, Andreas M. Antonopoulos Dr. Gavin Wood, O'reilly.
2. Blockchain Technology, Chandramouli Subramanian, Asha A George, Abhillash K. A and Meena Karthikeyen, Universities
press

References:

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134
1. Blockchin enabled Applications, Vikram Dhillon, DevidMetcalf, Max Hooper, Apress
2. Building Blockchain Projects, Narayan Prusty, Packt

Online References:
Sr. No. Website Name
1. https://ethereum.org/en/
2. https://hyperledger -fabric.readthedocs.io/en/release -2.2/whatis.html
3. https://www.blockchain.com/
4. https://docs.soliditylang.org/en/v0.7.4/

Assessment:
Internal Assessment (IA) for 20 marks:
 IA will consist of Two Compuls ory Internal Assessment Tests. Approximately 40% to 50% of syllabus
content must be covered in First IA Test and remaining 40% to 50% of syllabus content must be covered in
Second IA Test
 Question paper format
 Question Paper will comprise of a total of six questions each carrying 20 marks Q.1 will be compulsory
and should cover maximum contents of the syllabus
 Remaining questions will be mixed in nature (part (a) and part (b) of each question must be from
different modules. For example, if Q.2 has part (a) from Module 3 then part (b) must be from any other
Module randomly selected from all the modules)
 A total of four questions need to be answered

















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135
Blockchain: Sem VII
Teaching Scheme
(Contact Hours) Credits Assigned
Course
Code Course Title Theory Practical Tutorial Theory Practical Tutorial Total
HBCSBL7 01
Private
Blockchain Setup
Lab(SBL) -- 4 -- -- 02 -- 02

Course
Code Course Title Examination Scheme
Theory Marks Term
Work Oral Total Internal assessment End Sem.
Exam Test1 Test 2 Avg.
HBCSBL601
Private Blockchain
Setup Lab(SBL) -- -- -- -- 50 50 100

Lab Objectives:
Sr. No. Lab Objectives
The Lab aims:
1 To build and test Private Ethereum Blockchain.
2 To learn the concept of the genesis block and Account in the Blockchain.
3 To get familiar with the mining blocks to create a ether.
4 To understand and apply the concepts of keys, wallets.
5 To acquire the knowledge of gateway and desktop application.
6 To analyze the applications & case studies of Blockchain.

Lab Outcomes:
Sr. No. Lab Outcomes Cognitive levels of
attainment as per
Bloom’s Taxonomy
On successful completion, of lab, learner/student will be able to:
1 To understand how blockchai n systems (mainly Etherum) work . L1,L2
2 To create the genesis block using Puppeth, a CLI tool and account using Smart
Contract. L6
3 To create mining blocks, check the account and PoW. L6
4 To use cryptocurrency exchanges and wallets safely. L1,L2,L3
5 To create Gateway to Blockchain Apps. L6
6 To use Blockchain on Mobile App and on Cloud. L1,L2,L3

Prerequisite: Expertise in Programming, Basic knowledge of Computer Security, Networking.
Hardware & Software Requirements:
Hardware Requirements Software Requirements Other Requirements
PC With Following Configuration
1. PC i3/i5/i7 Processor or above.
2. 4 GB RAM
3. 500 GB Harddisk
4. Network interface card 1. NodeJs
2. Ethereum
3. Geth
4. Solidity 1. Internet Connection.

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136
DETAILED SYLLABUS:
Note: All practical are to be conducted on Linux platform its Compulsory for this entire practical
Sr. No Module . Description Hours LO Mapping
1 Build and Test
Install Ethereum network to create a private
Ethereum Blockchain
Self- learning topic : Hyperledger 4 LO1
2 Build and Test Installation of geth 5 LO1
3 Create the
Genesis block Create the genesis block using Puppeth, a CLI tool 5 LO2
4 Create Account in
the blockchain Smart contract 6 LO2
5 Mining Blocks to
create Ether Mine blocks, check account balance, PoWvsPoA 6 LO3
6 Gateway to
Blockchain Apps Metamask 5 LO4
7 Web and
Desktop
Application Solidity programming on remix 6 LO4
8 Application
Development Crypto Exchange and Wallet
4 LO5
9 Application
Development Blockchain Mobile App or Web Application using Dapp 6 LO6
10 Application
Development Hosting of a private blockchain on cloud(AWS/Azure) 5 LO6

Text Books:
1. Mastering Ethereum: Building Smart Contracts and Dapps, Andreas Antonopoulos , Gavin Wood , O’Reilly Publication
2. Mastering Blockchain, Second Edition: Distributed ledger technology, decentralization, and smart contracts explained,
2nd Edition, Imran Bashir
3. Solidity Programming Essentials: A beginner's Guide to Bu ild Smart Contracts for Ethereum and Blockchain, RiteshModi,
Packt publication
4. Mastering Blockchai n, Imran Bashir, Second Edition , Packt Publication.

References Books:
1. Mastering Bitcoin, PROGRAMMING THE OPEN BLOCKCHAIN , 2nd Edition by Andreas M. Antonopo ulos, June 2017,
Publisher(s): O'Reilly Media, Inc. ISBN: 9781491954386.
2. Blockchain Applications: A Hands -On Approach, by ArshdeepBahga, Vijay Madisetti, Paperback – 31 January 2017.
3. Mastering Blockchain, Imran Bashir, Packt Publication.

Online Reference s:
Sr. No. Website Name
1. https://geth.ethereum.org/downloads/

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137
2. https://medium.com/@agrawalmanas09/how -to-setup -private -ethereum -blockchain -on-windows -10-
machine -ab497e03d6b8
3. https://geth.ethereum.org/docs/dapp/
4. https://www.edureka.co/blog/ethereum -private -network -tutorial
5. https://docs.soliditylang.org/en/develop/index.html
6. https://metamask.io
7. https://medium.com/publicaio/a -complete -guide -to-using -metamask -updated -version -cd0d6f8c338f
8. https://docs.aws.amazon.com/blockchain -templates/latest/developerguide/blockchain -templates -
create -stack.html

Term Work:
The Term work shall consist of at least 10 to 12 practical based on the above syllabus. The term work Journal must
include at least 2 assignments. The assignments should be based on real world applications which cover concepts from
all above syllabus .

Term Work Marks: 50 Marks (Total marks) = 40 Marks (Experiment) + 5 Marks (Assignments/tutorial/write up) + 5
Marks (Attendance)

Oral Exam: An Oral exam will be held based on the above syllabus.



























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Course
Code Course Title Examination Scheme
Theory Marks
Term
Work Practical Oral Total Internal assessment End
Sem.
Exam Test1 Test 2 Avg
HBCC801 DeFi (Decentralized
Finance) 20 20 20 80 -- -- -- 100

Course Objectives:
Sr. No. Course Objectives
The course aims:
1 The basic concepts of Centralized and Decentralized Finance and compare them.
2 The DeFi System and its key categories .
3 The DeFi components, primitives, incentives, metrics and major business models where they are used.
4 The DeFi Architecture and EcoSystem .
5 The DeFi protocols.
6 The real time use cases of DeFi.

Course Outcomes:
Sr. No. Course Outcomes Cognitive levels
of attainment as
per Bloom’s
Taxonomy
On successful completion, of course, learner/student will be able to:
1 Explain the basic concepts of Centralized and Decentralized Finance and compare
them. L1, L2
2 Describe the the DeFi System and its key categories . L1
3 Discuss the DeFi components, primitives, incentives, metrics and major business
models where they are used. L1, L2
4 Explain the DeFi Architecture and EcoSystem . L1, L2
5 Illustrate the DeFi protocols. L1
6 Discuss the real time use cases of DeFi. L1,L2

DETAILED SYLLABUS:
Sr. No. Module Detailed Content Hours CO
Mapping
0 Prerequisite Blockchain & Cryptocurrency, Blockchain Platform,
Blockchain Development 02 -
I Introduction: Difference between Centralized and Decentralized Finance,
Traditional Financial Institution - Banks: 1. Payment and 06 CO1 Blockchain: Sem VIII
Course
Code Course Title Theory Practical Tutorial Theory Practical Tutorial Total
HBCC801 DeFi
(Decentralized
Finance) 04 -- -- 04 -- -- 04

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139
Centralized and
decentralized
finance Clearance systems, 2. Accessibility, 3. Centralization and
Transparency, Decentralized Finance Vs Traditional Finance
Self-learning Topics:
The Potential Impact of Decentraliz ed Finance
II What is
decentralized
finance (defi)? The DeFi Ecosystem, Problems that DeFi Solves How
Decentralized is DeFi? Defi key Categories: -Stablecoins,
Stable coin and pegging, Lending and Borrowing, Exchanges,
Derivations, Fund Management, Lottery, Payments,
Insurance
Self-learning Topics:
How Decentralized Finance Could Make Investing More
Accessible. 06 CO2
III DeFi Primitives
and Business
Models 3.1 DeFi Components: Blockchain Cryptocurrency The Smart
Contract Platform Oracles Stablecoins Decentralized
Applications
3.2 DeFi Primitives: Transactions Fungible Token: Equity
Tokens, Utility Tokens and Governance TokensNFT: NFT
Standard, Multi -token standard Custody Supply Adjustment:
Burn -Reduce Supply, Mint -Increase Supply, Bonding Curve -
Pricing Supply
Incentives: Staking Rewards, Slashing, Direct Rewards and
Keepers, Fees
Swap: Order Book Matching, Automated Market Makers
Collaterlized Loans Flash Loans (Uncollaterlized Loans)
3.3 DeFi Key Metrics: Total Value Locked, Daily Active
Users,Market Cap
3.4 DeFi Major Business Models: Decentralized Currencies ,
Decentralized Payment Services, Decentralized fundraising,
Decentralized Contracting
Self-learning Topics: Study any real time Business model.
10 CO3
IV DeFi
Architecture
and EcoSystem 4.1DeFi Architecture: Consumer Layer: Blockchains, Cross -
Blockchain networks, Oracles, Digital Asset Layer:
Cryptocurrencies, Infrastructure Layer: Wallets and Asset
Management, DEXes and Liquidity, Lending and Borrowing,
Prediction Markets, Synt hetic Assets, Insurance
4.2 DeFi EcoSystem and Protocols: On-chain Asset Exchange,
Loanable Fund Markets on-chain assets, Stablecoins,
Portfolio Management, Derivatives, Privacy -preserving
mixers
4.3 DeFi Risk and Challenges:
Technical Risks, Usability Ris ks,
Centralization Risks, Liquidity Risks, Regulation Risk 10 CO4

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Self-learning Topics: Study of the Problems which are
holding DeFi adoption back
V DeFi Deep Dive 5.1.Maker DAO:Maker Protocol: Dai Stablecoins, Maker
Vaults, Maker Protocol Auctions
Maker Actors: Keepers, Price Oracles, Emergency Oracles,
DAO Teams, Dai Savings Rate
Dai Use case Benefits and Examples
5.2.UniSwap:UniSwap Protocol Overview: How UniSwap
Works, EcoSystem Participants, Smart Contracts
UniSwap Core Concepts: Swaps, Pools, Flash S waps, Oracles
5.3. Compound: Compound Protocol: Supplying Assets,
Borrowing Assets, Interest Rate Model
Compound Implementation and Architecture: cToken
Contracts, Interest Rate Mechanics, Borrowing, Liquidation,
Price Feeds, Comptroller, Governance
5.4. w BTC:Need for wBTC: Tokenization and common Issues
wBTC Implementation and Technology: Users, Custodian
Wallet Setup, Minting, Burning
wBTC Governance, wBTC vs Atomic Swaps, Fees, Legal
Binding, Trust Model and Transparency

Self-learning Topics:
MakerDAO Governance, UniSwap Governance Protocol
Math, Compound Protocol Math 10 CO5
VI Use Cases 6.1Decentralized Exchanges
6.2Decentralized Stablecoins
6.3Decentralized Money Markets
6.4Decentralized Synthetix
6.5Decentralized Insurance
6.6Decentralized Autonomous Organization (DAO),
Self-learning Topics:
Stock Exchange Operations, Derivatives, Tether, Ampleforth,
How to get stablecoins, Synthetix Network, Token, The
Ongoing Impact of The DAO’s Rise and Fall, DAO Projects 08 CO6

Text Books:
1. How to DeFi,Darren Lau, Daryl Lau, Teh Sze Jin,Kristian Kho, Erina Azmi, TM Lee,Bobby Ong -1st Edition, March 2020
2. DeFi and the Future of Finance -Campbell R. Harvey
3. DeFi Adoption 2020 A Definitive Guide to Entering the Industry
Reference Books/White Papers:
1. Blockchain disruption and decentralized finance: The rise of decentralized business models -Yan Chen, Cristiano
Bellavitis
2. SoK: Decentralized Finance (DeFi) -Sam M. Werner, Daniel Perez, Lewis Gudgeon,Ariah Klages -Mundt,Dominik
Harz∗‡, William J. Knottenbel t,Imperial College London, † Cornell University, Interlay
4. Decentralized Finance (DeFi) –A new Fintech Revolution?
5. https://makerdao.com/da/whitepaper/
6. https://uniswap.org/
7. https://compound.finance/documents/Compound.Whitepaper.pdf
8. https://wbtc.network/assets/wrapped -tokens -whitepaper.pdf

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141
9. https://defiprime.com/exchanges
10. https://defirate.com/stablecoins/
11. https://academy.ivanontech.com/blog/decentralized -money -markets -and-makerdao
12. https://www.gemini.com/cryptopedia/nexus -mutual -blockch ain-insurance -nxm -crypto
13. https://consensys.net/blockchain -use-cases/decentralized -finance/
14. https://tokenlon.zendesk.com/hc/en -us/articles/360041114431 -DeFi -Explained -Synthetic -Assets,
https://www.blockchain -council.org/synthetix/synthetix -snx-the-biggest -ecosystem -in-decentralized -finance/
Online References:
Sr. No. Website Name
1. https://www.udemy.com/
2. https://www.coursera.org/

Assessment:


Internal Assessment (IA) for 20 marks:
 IA will consist of Two Compulsory Internal Assessment Tests. Approximately 40% to 50% of syllabus
content must be covered in First IA Test and remaining 40% to 50% of syllabus content must be covered in
Second IA Test
 Question paper format
 Question Paper will comprise of a total of six questions each carrying 20 marks Q.1 will be compulsory
and should cover maximum contents of the syllabus
 Remaining questions will be mixed in nature (part (a) and part (b) of each question must be from
different modules. For example, if Q.2 has part (a) from Module 3 then part (b) must be from any other
Module randomly selected from all the modules)
 A total of four questions need to be answered











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142

University of Mumbai






Syllabus

Honours / Minor Degree Program
in
Cyber Security


FACULTY OF SCIENCE & TECHNOLOGY
(As per AICTE guidelines with effect from the academic year 2022 -2023)

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143


University of Mumbai
Cyber Security
(With effect from 2022 -23)
Year
&Sem
Course Code
and Course
Title Teaching
Scheme Hours / Week Examination Scheme and Marks Credit
Scheme
Theory Seminar/
Tutorial Pract Internal
Assess
ment End
Sem
Exam Term
Work Oral/
Pract Total Credits

TE
Sem
V HCSC501:
Ethical Hacking 04 -- -- 20 80 -- -- 100 04
Total 04 - -- 100 - - 100 04
Total Credits = 04

TE
Sem.
VI HCSC601:
Digital Forensic 04 -- -- 20 80 -- -- 100 04
Total 04 - - 100 - - 100 04
Total Credits = 04


BE
Sem.
VII HCSC701:
Security
Information
Management 04 -- -- 20 80 -- -- 100 04
HCSSBL601:
Vulnerability
Assessment
Penetration
Testing (VAPT)
Lab (SBL) -- -- 04 -- -- 50 50 100 02
Total 04 - 04 100 50 50 200 06
Total Credits = 06

BE
Sem.
VIII
HCSC801:
Application
Security 04 - -- 20 80 -- -- 100 04
Total 04 - - 100 - - 100 04
Total Credits = 04

Total Credits for Semesters V,VI, VII &VIII = 04+04+06+04=18

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144

Course
Code Course
Title Examination Scheme
Theory Marks
Term
Work Practical Oral Total Internal assessment End
Sem.
Exam Test 1 Test 2 Avg. of
2 Tests
HCSC501 Ethical
Hacking 20 20 20 80 -- -- -- 100
Course Objectives:
Sr. No. Course Objectives
The course aims:
1 To describe Ethical hacking and fundamentals of computer Network.
2 To understand about Network security threats, vulnerabilities assessment and social
engineering .
3 To discuss cryptography and its applications .
4 To implement the methodologies and t echniques of Sniffing techniques, tools, and ethical
issues .
5 To implement the methodologies and techniques of hardware security .
6 To demonstrate systems using various case studies.

Course Outcomes:
Sr.
No. Course Outcomes Cognitive levels
of attainment as
per Bloom’s
Taxonomy
On successful completion, of course, learner/student will be able to:
1 Articulate the fundamentals of Computer Networks, IP Routing and core
concepts of ethical hacking in real world scenarios. L1,L2
2 Apply the knowledge of information gathering to prevent penetration testing
and social engineering attacks. L3
3 Demonstrate the core concepts of Cryptography, Cryptographic checksums
and evaluate the various biometric authentication mechanisms. L1,L2
4 Apply the knowledge of n etwork reconnaissance to prevent Network and
web application -based attacks . L3
5 Apply the concepts of hardware elements and endpoint security to provide
security to physical devices. L3
6 Simulate various attack scenarios and evaluate the results. L4,L5

DETAILED SYLLABUS: Course
Code Course Title Theory Practical Tutorial Theory Practical/
Oral Tutorial Tota
l
HCSC501 Ethical
Hacking 04 -- -- 04 -- -- 04

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145
Sr.
No. Module Detailed Content Hours CO
Mapping
0 Prerequisite Computer Networks, Databases , system security 2 -
I Introduction to
Ethical
Hacking Fundamentals of Computer Networks/IP protocol
stack, IP addressing and routing, Routing protocol,
Protocol vulnerabilities, Steps of ethical hacking,
Demonstration of Routing Protocols using Cisco
Packet Tracer
Self-learning Topics :TCP/IP model, OSI model 10 CO1
II Introduction to
Cryptography Private -key encryption, public key -encryption, key
Exchange Protocols, Cryptographic Hash
Functions & applications, steganography, biometric
authentication, lightweight cryptographic
algorithms. Demonstration of various
cryptographic tools and hashing algorithms
Self-learning Topics : Quantum cryptography,
Elliptic curve cryptography 08 CO3
III Introduction to
network
security Information gathering, reconnaissance, scanning,
vulnerability assessment, Open VAS, Nessus,
System hacking: Password cracking, penetration
testing, Social engineering attacks, Malware
threats, hacking wireless networks (WEP, WPA,
WPA -2), Proxy network, VP N security, Study of
various tools for Network Security such as
Wireshark, John the Ripper, Metasploit, etc.
Self-learning Topics : Ransomware(Wannacry),
Botnets, Rootkits, Mobile device security 12 CO2
IV Introduction to
web security
and Attacks OWASP, Web Security Considerations, User
Authentication, Cookies, SSL, HTTPS, Privacy on
Web, Account Harvesting, Web Bugs, Sniffing,
ARP poisoning, Denial of service attacks, Hacking
Web Applications , Clickjacking, Cross -Site
scripting and Request Forgery , Session Hijacking
and Management, Phishing and Pharming
Techniques, SSO, Vulnerability assessments, SQL
injection , Web Service Security, OAuth 2.0,
Demonstration of hacking tools on Kali Linux such
as SQLMap, HTTrack, hping, burp suite,Wireshark
etc.
Self-learning Topics : Format string attacks 10 CO4
V Elements of
Hardware
Security Side channel attacks, physical unclonable
functions, Firewalls,Backdoors and trapdoors, 6 CO5

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Demonstration of Side Channel Attacks on RSA,
IDS and Honeypots.
Self-learning Topics : IoT security
VI Case Studies Various attacks scenarios and their remedies.
Demonstration of attacks using DVWA.
Self-learning Topics : Session hijacking and man -
in-middle attacks 4 CO6
Text Books:
1. Computer Security Principles and Practice --William Stallings, Seventh Edition, Pearson Education, 2017
2. Security in Computing -- Charles P. Pfleeger, Fifth Edition, Pearson Education, 2015
3. Network Security and Cryptography -- Bernard Menezes, Cengage Learning, 2014
4. Network Security Bible -- Eric Cole, Second Edition, Wiley, 2011
5. Mark Stamp's Information Security: Principles and Practice --Deven Shah, Wiley, 2009

References:
1.UNIX Network Programming –Richard Steven,Addison Wesley, 2003
2. Cryptography and Network Security -- Atul Kahate, 3rd edition, Tata Mc Graw Hill, 2013
3.TCP/IP Protocol Suite -- B. A. Forouzan, 4th Edition, Tata Mc Graw Hill, 2017
4. Applied Cryptography, Protocols Algorithms and Source Code in C -- Bruce Schneier, 2nd
Edition / 20th Anniversary Edition, Wiley, 2015

Online Resources:
Sr. No. Website Name
1. https://www.owasp.org/index.php/Category:OWASP_Top_Ten_Project
2. https://dvwa.co.uk/
3. http://testphp.vulnweb.com/

Assessment:
Internal Assessment (IA) for 20 marks:
 IA will consist of Two Compulsory Internal Assessment Tests. Approximately 40% to 50%
of syllabus content must be covered in First IA Test and remaining 40% to 50% of syllabus
content must be covered in Second IA Test
 Question paper format
 Question Paper will comprise of a total of six questions each carrying 20 marks Q.1 will
be compulsory and should cover maximum contents of the syllabus
 Remaining questions will be mixed in nature (part (a) and part (b) of each question must
be from different modules. For example, if Q.2 has part (a) from Module 3 then part (b)
must be from any other Module r andomly selected from all the modules)
 A total of four questions need to be answered

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147

Course
Code Course
Title Examination Scheme
Theory Marks
Term
Work Practical Oral Total Internal assessment End
Sem.
Exam Test1 Test 2 Avg. of 2
Tests
HCSC601 Digital
Forensic 20 20 20 80 -- -- -- 100
Course Objectives:
Sr. No. Course Objectives
The course aims:
1 To understand the various computer and cyber -crimes in the digital world .
2 To understand a significance of digital forensics life cycle, underlying forensics principles and
investigation process.
3 To understand the importance of File system management with respect to computer forensics .
4 To be able to identify the live data in case of any incident handling and application of
appropriate tools and practices for the same .
5 To Develop the skills in application of various tools and investigat ion report writing with
suitable evidences .
6 To be able to identify the network and mobile related threats and recommendation of suitable
forensics procedures for the same .

Course Outcomes:
Sr.
No. Course Outcomes Cognitive levels
of attainment as
per Bloom’s
Taxonomy
On successful completion, of course, learner/student will be able to:
1 Identify and define the class for various computer and cyber -crimes in the digital
world. L1,L2
2 Understand the need of digital forensic and the role of digital evidence . L1,L2
3 Understand and analyze the role of File systems in computer forensics . L1,L2,L3
4 Demonstrate the incident response methodology with the best practices for
incidence response with the application of forensics tools . L3
5 Generate/Write the report on application of appropriate computer forensic tools
for investigation of any computer security incident . L5
6 Identify and investigate threats in network and mobile . L4
DETAILED SYLLABUS: Course
Code Course Title Theory Practical Tutorial Theory Practical/
Oral Tutorial Total
HCSC601 Digital
Forensic 04 -- -- 04 -- -- 04

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148
Sr.
No. Module Detailed Content Hours
CO
Mapping
0 Prerequisite Computer Hardware : Motherboard, CPU,
Memory: RAM, Hard Disk Drive (HDD), Solid
State Drive (SSD), Optical drive
Computer Networks: Introduction CN
Terminology: Router, Gateway, OSI and
TCP/IP Layers
Operating Systems: Role of OS in file
management, Memory management utilities,
Fundamentals of file systems used in Windows
and Linux. 2 --
I Introduction to
Cybercrime and
Computer -crime
1.1 Definition and classification of
cybercrimes: Definition, Hacking, DoS
Attacks, Trojan Attacks, Credit Card Frauds,
Cyber Terrorism, Cyber Stalking.
1.2 Definition and classification of computer
crimes: Computer Viruses, Computer Worms.
1.3 Prevention of Cybercrime : Steps that can
be followed to prevent cybercrime, Hackers,
Crackers, Phreakers.
Self-learning Topics: Steps performed by
Hacker
4 CO1
II Introduction to
Digital Forensics
and Digital
Evidences 2.1 Introduction to Digital Forensics:
Introduction to Digital Forensics and lifecycle,
Principles of Digital Forensic.
2.2 Introduction to Digital Evidences:
Challenging Aspects of Digital Evidence,
Scientific Evidence, Presenting Digital
Evidence.
2.3 Digital Investigation Process Models:
Physical Model, Stairc ase Model, Evidence
Flow Model.
Self-learning Topics: Digital Investigation
Process Models comparison and its application,
Rules of Digital Evidence. 5 CO2
III Computer
Forensics 3.1 OS File Systems Review: Windows
Systems - FAT32 and NTFS, UNIX File
Systems, MAC File Systems
3.2 Windows OS Artifacts: Registry, Even t
Logs 7 CO3

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3.3 Memory Forensics : RAM Forensic
Analysis, Creating a RAM Memory Image,
Volatility framework, Extracting Information
3.4 Computer Forensic Tools: Need of
Computer Forensic Tools, Types of Computer
Forensic Tools, Tasks performed by Computer
Forensic Tools
Self-learning Topics: Study of ‘The Sleuth
Kit’ Autopsy tool for Digital Forensics

IV Incident
Response
Management,
Live Data
Collection and
Forensic
Duplication 4.1 Incidence Response Methodology: Goals
of Incident Response, Finding and Hiring IR
Talent
4.2 IR Process: Initial Response, Investigation,
Remediation, Tracking of Significant
Investigative Information.
4.3 Live Data Collection: Live Data Collection
on Microsoft Windows,
4.4 Forensic Duplication: Forensic Duplicates
as Admissible Evidence, Forensic Duplication
Tools: Creating a Forensic evidence,
Duplicate/Qualified Forensic Duplicate of a
Hard Drive.
Self-learning Topics: Live Data Collection on
Unix -Based Systems
10 CO4
V Forensic Tools
and Report
Writing 5.1 Forensic Image Acquisition in Linux :
Acquire an Image with dd Tools, Acquire an
Image with Forensic Formats, Preserve Digital
Evidence with Cryptography, Image
Acquisition over a Network, Acquire
Removable Media
5.2 Forensic Investigation Report Writi ng:
Reporting Standards, Report Style and
Formatting, Report Content and Organization.
Self-learning Topics: Case study on Report
Writing 10 CO5
VI Network
Forensics and
Mobile Forensics 6.1 Network Forensics: Sources of Network -
Based Evidence, Principles of Internetworking,
Internet Protocol Suite, Evidence Acquisition,
Analyzing Network Traffic: Packet Flow and
Statistical Flow, Network Intrusion Detection
and Analysis, Investigation of Routers,
Investigation of Firewalls
6.2 Mobile Forensics: Mobile Phone
Challenges, Mobile phone evidence extraction 14 CO6

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150
process, Android OS Architecture, Android File
Systems basics, Types of Investigation,
Procedure for Handling an Android Device,
Imaging Android USB Mass Storage Devices.
Self-learning Topic: Elcomsoft iOS Forensic
Toolkit, Remo Recover tool for Android Data
recovery


Text Books:
1. Digital Forensics by Dr. Dhananjay R. Kalbande Dr. Nilakshi Jain, Wiley Publications,
First Edition, 2019.
2. Digital Evidence and Computer Crime by Eoghan Casey, Elsevier Academic Press, Third
Edition, 2011.
3. Incident Response & Computer Forensics by Jason T. Luttgens, Matthew Pepe and Kevin
Mandia, McGraw -Hill Education, Third Edition (2014).
4. Network Forensics : Tracking Hackers through Cyberspace by Sherri Davidoff and
Jonathan Ham, Pearson Edu,2012
5. Practical Mobile Forensic by Satish Bommisetty, Rohit Tamma, Heather Mahalik,
PACKT publication, Open source publication, 2014 ISBN 978 -1-78328 -831-1
6. The Art of Memory Forensics: Detecting Malware and Threats in Windows, Linux, and
Mac Memory by Michael Hale Ligh (Author), Andrew Case (Author), Jamie Levy
(Author), AAron Walters (Author), Publisher : Wiley; 1st editio n (3 October 2014),


References:
1. Scene of the Cybercrime: Computer Forensics by Debra Littlejohn Shinder, Syngress
Publication, First Edition, 2002.
2. Digital Forensics with Open Source Tools by Cory Altheide and Harlan Carvey, Syngress
Publication, First Edition, 2011.
3. Practical Forensic Imaging Securing Digital Evidence with Linux Tools by Bruce
Nikkel,NoStarch Press, San Francisco,(2016)
4. Android Forensics : Investigation, Analysis, and Mobile Security for Google Android by
Andrew Hogg, Elsevier Publication,2011

Online References:
Sr.
No. Website Name
1. https://www.pearsonitcertification.com/articles/article.aspx?p=462199&seqNum=2
2. https://flylib.com/books/en/3.394.1.51/1/
3. https://www.sleuthki t.org/autopsy/
4. http://md5deep.sourceforge.net/md5deep.html
5. https://tools.kali.org/
6. https://kalilinuxtutorials.com/
7. https://accessdata.com/product -download/ftk -imager -version -4-3-0
8. https://www.amazon.in/Art -Memory -Forensics -Detecting -Malware/dp/1118825098

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Research Papers: Mobile Forensics/ Guidelines on Cell Phone Forensics
1. Computer Forensics Resource Center: NIST Draft Special Publication 800 -101 :
https://csrc.nist.gov/publications/detail/sp/800 -101/rev -1/final
2. https://cyberforensicator.com/category/white -papers
3. https://www.magnetforensics.com/resources/ios -11-parsing -whitepaper/
4. Samarjeet Yadav , Satya Prakash , Neelam Dayal and Vrijendra Singh, "Forensics Analysis
WhatsApp in Android Mobile Phone", Electronic copy available
at: https://ssrn.com/abstract=3576379
Assessment:
Internal Assessment (IA) for 20 marks:
 IA will consist of Two Compulsory Internal Assessment Tests. Approximately 40% to 50%
of syllabus content must be covered in First IA Test and remaining 40% to 50% of syllabus
content must be covered in Second IA Test
 Question paper format
 Question Paper will comprise of a t otal of six questions each carrying 20 marks Q.1 will
be compulsory and should cover maximum contents of the syllabus
 Remaining questions will be mixed in nature (part (a) and part (b) of each question must
be from different modules. For example, if Q.2 ha s part (a) from Module 3 then part (b)
must be from any other Module randomly selected from all the modules)
 A total of four questions need to be answered

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152

Course
Code Course Title Examination Scheme
Theory Marks
Term
Work Practical Oral Total Internal assessment End
Sem.
Exam Test1 Test 2 Avg. of 2
Tests
HCSC701 Security
Information
Management 20 20 20 80 -- -- -- 100
Course Objectives:
Sr. No. Course Objectives
The course aims:
1 The course is aimed to focus on cybercrime and need to protect information.
2 Understand the types of attacks and how to tackle the amount of risk involved.
3 Discuss the role of industry standards and legal requirements with respect to compliance.
4 Distinguish between different types of access control models, techniques and policy.
5 Awareness about Business Continuity and Disaster Recovery.
6 Awareness about Incident Management and its life cycle.

Course Outcomes:
Sr.
No. Course Outcomes Cognitive levels
of attainment as
per Bloom’s
Taxonomy
On successful completion, of course, learner/student will be able to:
1 Understand the scope of policies and measures of information security to
people. L1,L2
2 Interpret various standards available for Information security. L1,L2
3 Apply risk assessment methodology. L3
4 Apply the role of access control to Identity management. L3
5 Understand th e concept of incident management , disaster recovery and
business continuity. L1,L2
6 Identify common issues in web application and server security. L3

DETAILED SYLLABUS:
Sr.
No. Module Detailed Content Hours CO
Mapping
0 Prerequisite Vulnerability Assessment for Operating Systems, Network
(Wired and Wireless). Tools for conducting Reconnaissance. 2 -- Course
Code Course Title Theory Practical Tutorial Theory Practical/
Oral Tutorial Total
HCSC701 Security
Information
Management 04 -- -- 04 -- -- 04

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153
I Basics of
Information
Security
1.1 What is Information Security & Why do you need it? –
1.2 Basics Principles of Confidentiality, Integrity
1.3 Availability Concepts, Policies, procedures, Guidelines,
Standards
1.4 Administrative Measures and Technical Measures, People,
Process, Technology, IT ACT 2000, IT ACT 2008
Self-learning Topics: Impact of IT on organizations,
Importance of IS to Society 6 CO1, CO2
II Current
Trends in
Information
Security
2.1 Cloud Computing: benefits and Issues related to
information Security.
2.2 Standards available for InfoSec: Cobit, Cadbury, ISO
27001, OWASP, OSSTMM.
2.3 An Overview, Certifiable Standards: How, What, When,
Who.
Self-learning Topics: Cloud Threats, Impact of cloud
computing on users, examples of cloud service providers:
Amazon, Google, Microsoft, Salesforce etc. 8 CO2
III Threat &
Risk
Management
3.1 Threat Modelling : Threat, Threat -Source,
Vulnerability, Attacks.
3.2 Risk Assessment Frameworks : ISO 31010, NIST -SP-800-
30, OCTAVE
3.3 Risk Assessment and Analysis: Risk Team Formation,
Information and Asset Value, Identifying Threat and
Vulnerability, Risk Assessment Methodologies
3.4 Quantification of Risk, Identification of Monitoring
mechanism, Calculating Total Risk and Residual Risk.
Self-learning Topics: Risk management trends today and
tomorrow. 8 CO3
IV Identity and
Access
Management
4.1 Concept s of Identification, Authentication, Authorization
and Accountability.
4.2 Access Control Models: Discretionary, Mandatory,
Role based and Rule -based.
4.3 Access Control Techniques: Constrained User, Access
control Matrix, Content -dependent, Context – dependent
4.4 Access Control Methods: Administrative, Physical,
Technical, Layering of Access control
4.5 Access Control Monitoring: IDS and IPS and anomal y
detection.
4.6 Accountability: Event -Monitoring and log reviews.
Log Protection
4.7 Threats to Access Control: Various Attacks on the
Authentication systems.

Self-learning Topics: challenges and solutions in identity and
access management 10 CO4

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V Operational
Security
5.1 Concept of Availability, High Availability,
Redundancy and Backup.
5.2 Calculating Availability, Mean Time Between Failure
(MTBF), Mean Time to Repair (MTTR)
5.3 Incident Management : Detection, Response,
Mitigation, Reporting, Recovery and Remediation
5.4 Disaster Recovery:
Metric for Disaster Recovery, Recovery Time Objective
(RTO), Recovery Point Objective (RPO), Work Recovery
Time (WRT), Maximum Tolerable Downtime (MTD),
Business Pro cess Recovery, Facility Recovery (Hot site, Warm
site, Cold site, Redundant site), Backup & Restoration

Self-learning Topics: Challenges and Opportunities of
Having an IT Disaster Recovery Plan
10 CO5
VI Web
Application,
Windows,
and Linux
security
6.1 Types of Audits in Windows Environment
6.2 Server Security, Active Directory (Group Policy),
Anti-Virus, Mails, Malware
6.3 Endpoint protection, Shadow Passwords, SUDO users,
etc.
6.4 Web Application Security: OWASP, Common Issues in
Web Apps, what is XSS, SQL injection, CSRF, Password
Vulnerabilities, SSL, CAPTCHA, Session Hijacking,
Local and Remote File Inclusion, Audit Trails, Web
Server Issues, etc.
Self-learning Topics: , Network firewall protection, Choosing
the Right Web Vulnerability Scanner 8 CO6

Textbooks:
1. Shon Harris, Fernando Maymi, CISSP All -in-One Exam Guide, McGraw Hill Education, 7th Edition,
2016.
2. Andrei Miroshnikov, Introduction to Information Security - I, Wiley, 2018
3. Ron Lepofsky, The Manager’s Guide to Web Application Security, Ap ress; 1st ed. edition, 2014

References:
1. Rich -Schiesser, IT Systems Management: Designing, Implementing and Managing World - Class
Infrastructures, Prentice Hall; 2 edition, January 2010.
2. NPTEL Course: - Introduction to Information Security – I (URL:
https://nptel.ac.in/noc/courses/noc15/SEM1/noc15 -cs03/)
3. Dr. David Lanter – ISACA COBIT – 2019 Framework - Introduction and Methodology
4. Pete Herzog, OSSTMM 3, ISECOM
5. NIST Special Publication 800 -30, Guide for Conducting Risk Assessments, September 2012

Online References:
Sr. No. Website Name
1. https://www.ultimatewindowssecurity.com/securitylog/book/Default.aspx
2. http://www.ala.org/acrl/resources/policies/chapter14
3. https://advisera.com/27001academy/what -is-iso-27001/

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4. https://nvlpubs.nist.gov/nistpubs/legacy/sp/nistspecialpublication800 -30r1.pdf
5. http://www.diva -portal.org/smash/get/diva2:1117263/FULLTEXT01.pdf

Assessment:
Internal Assessment (IA) for 20 marks:
 IA will consist of Two Compulsory Internal Assessment Tests. Approximately 40% to 50%
of syllabus content must be covered in First IA Test and remaining 40% to 50% of syllabus
content must be covered in Second IA Test
 Question paper format
 Question Paper will comprise of a total of six questions ea ch carrying 20 marks Q.1 will
be compulsory and should cover maximum contents of the syllabus
 Remaining questions will be mixed in nature (part (a) and part (b) of each question must
be from different modules. For example, if Q.2 has part (a) from Module 3 then part (b)
must be from any other Module randomly selected from all the modules)
 A total of four questions need to be answered

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156
Teaching Scheme
(Contact Hours)
Credits Assigned
Course Code Course Title Theory Practical Tutori
al Theory Practical Tutorial Total
HCS SBL601 Vulnerability
Assessment
Penetration
Testing (VAPT)
Lab (SBL) -- 4 -- -- 2 -- 02

Course Code Course Title Examination Scheme
Theory Marks
Term
Work Oral Total Internal assessment End
Sem.
Exam Test 1 Test 2 Avg. of 2
Tests
HCS SBL601 Vulnerability
Assessment
Penetration
Testing (VAPT)
Lab (SBL) -- -- -- -- 50 50 100

Lab Objectives:
Sr. No. Lab Objectives
The Lab aims:
1 To identify security vulnerabilities and weaknesses in the target applications.
2 To discover potential vulnerabilities which are present in the system in network using vulnerability
assessment tools.
3 To identify threats by exploiting them using penetration test attempt by utilizing the vulnerabilities
in a system
4 To recognize h ow security controls can be improved to prevent hackers gaining access controls to
database.
5 To test and exploit systems using various tools and understands the impact in system logs.
6 To write a report with a full understanding of current security po sture and what work is necessary
to both fix the potential threat and to mitigate the same source of vulnerabilities in the future

Lab Outcomes:
Sr.
No. Lab Outcomes Cognitive levels
of attainment as
per Bloom’s
Taxonomy
On successful completion, of lab, learner/student will be able to:
1 Understand the structure where vulnerability assessment is to be performed. L1,L2
2 Apply assessment tools to identify vulnerabilities present in the system in
network. L3

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3 Evaluate attacks by executing penetration tests on the system or network. L4
4 Analyse a secure environment by improving security controls and applying
prevention mechanisms for unauthorised access to database. L5
5 Create security by testing and exploit systems using various tools a nd remove
the impact of hacking in system. L6
6 Formation of documents as per applying the steps of vulnerabilities of
assessment and penetration testing. L3, L4, L5

Prerequisite: Computer Networks, Basic of Network Security .
Hardware & Software Requirements:
Hardware Requirements Software Requirements Other Requirements
PC With Following
Configuration
1. Intel PIV Processor
2. 4 GB RAM
3. 500 GB Harddisk
4. Network interface card 1. Windows or Linux Desktop OS
2. Security Software and tools
1. Internet Connection .

DETAILED SYLLABUS:
Sr.
No. Module Detailed Content Hours CO
Mapping
0 Prerequisite Computer Network, Basics of Network Security,
Ethical Hacking, Digital Forensics 2
I Human Security
(Social
Engineering)
Assessment
Visibility Audit: C ollecting information through social
media and internet. Collecting contact details (like
phone number, email ID, What’s App ID, etc)
Active Detection Verification: Test if the phone
number, email id etc are real by test message. Test
whether the information is filtered at point of reception.
Test if operator / another person assistance can be
obtained.
Device Information: IP Address, Port details,
Accessibility, Permissions, Role in business
Trust Verification: Test whether the inform ation can
be planted in form of note / email / Message (Phishing)
Test Subjects: College Staff, Reception, PA to
Director / Principal.
To conduct information gathering to conduct social
engineering audit on various sections in your college.
Self-Learning Topics: Networking Commands 8 LO1
II Network &
Wireless Security
Assessment Network Discovery: Using various tools to discover
the various connected devices, to get device name, IP
Address, relation of the device in network, Detection of 8 LO2

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Active port, OS Fingerprinting, Network port and
active service discovery
Tools: IP Scanner, Nmap etc
Network Packet Sniffing: Packet Sniffing to detect
the traffic pattern, Packet capturing to detect protocol
specific traffic pattern, Packet capturing t o reassemble
packet to reveal unencrypted password
Tools: Wireshark
Self-Learning Topics: Learning the CVE database for
vulnerabilities detected.
III Setting up
Pentester lab Including an attacker machine preferably Kali and in
the same subnet victim machines either DVWA/
SEEDlabs/ multiple VULNHUB machines as and when
required. Understanding Categories of pentest and
legalities/ ethics.
Installed Kali machine on VM environment with some
VULNHUB machines and we can find out vulnerability
of Level 1 -VULNHUB machine like deleted system
files, permissions of files.
Self learning Topics: Vulnerability exploitation for
acquire root access of the Kioptrx machine 9 LO3
IV Database and
Access Control
Security
Assessment Database Password Audit: Tool based audit has to be
performed for strength of password and hashes.
Tools: DBPw Audit
Blind SQL Injection: Test the security of the Database
for SQL Injection
Tools: BSQL Hacker
Password Audit: Perform the password audit on the
Linux / Windows based system
Tools: Cain & Able, John the ripper, LCP Password
Auditing tools for Windows.
Active Directory and Privileges Audit: Conduct a
review of the Active Directory and the Group Pol icy to
assess the level of access privileges allocated.
Tools: SolarWinds
Self-Learning Topics: Federated Database security
challenges and solutions. 9 LO4
V Log Analysis Conduct a log analysis on Server Event Log / Firewall
Logs / Server Security Log to review and obtain
insights
Tools: graylog, Open Audit Module.
Self-Learning Topics: Python and R -Programming
scripts 6 LO5
VI Compliance and
Observation
Reporting License Inventory Compliance:
Identify the number of licenses and its deployment in
your organization.
Tools: Belarc Advisor, Open Audit Report
Writing: NESSUS tool
Report should contain: 10 LO6

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a. Vulnerability discovered
b. The date of discovery
c. Common Vu lnerabilities and Exposure (CVE)
database reference and score; those vulnerabilities
found with a medium or high CVE score should be
addressed immediately
d. A list of systems and devices found vulnerable
e. Detailed steps to correct the vulnerability, whi ch can
include patching and/or reconfiguration of operating
systems or applications
f. Mitigation steps (like putting automatic OS updates
in place) to keep the same type of issue from happening
again
Purpose of Reporting: Reporting provides an
organizatio n with a full understanding of their current
security posture and what work is necessary to both fix
the potential threat and to mitigate the same source of
vulnerabilities in the future.
Self-Learning Topics: Study of OpenVAS, Nikto, etc.

Text & Reference Books and Links:
1. The Web Application Hacker's Handbook: Finding and Exploiting Security Flaws Paperback –
Illustrated, 7 October 2011 by Dafydd Stuttard
2. Hacking: The Art of Exploitation, 2nd Edition 2nd Edition by Jon Erickson
3. Important links of Vulnhub: Vulnhub Kioptrix
Download Link: https://www.vulnhub.com/entry/basic -pentesting -1,216/
https://www.vulnhub.com/entry/kioptrix -level -1-1,22/
Installation Video: https://youtu.be/JupQRHtfZmw
Walkthrough/solutions Video: https://yo utu.be/Qn2cKYZ6kBI
4. OWASP Broken Web Application Projects
https://sourceforge.net/projects/owaspbwa/
5. Mastering Modern Web Penetration Testing By Prakhar Prasad, October 2016, Packt Publishing.
6. Kali Linux Revealed: Mastering the Penetration Testing Distribution – June 5, 2017 by Raphael
Hertzog (Author), Jim O'Gorman (Author), Offsec Press Publisher

Term Work:
The Term w ork shall consist of at least 10 to 12 practical based on the above syllabus . The term work Journal
must include at least 2 assignments. The assignments should be based on real world applications which
cover concepts from all above syllabus .
Term Work Marks: 50 Marks (Total marks) = 40 Marks (Experiment) + 5 Marks Assignments/tutorial/write
up) + 5 Marks (Attendance)
Oral Exam: An Oral exam will be held based on the above syllabus.

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Course
Code Course Title Examination Scheme
Theory Marks
Term
Work Practical Oral Total Internal assessment End
Sem.
Exam Test1 Test 2 Avg. of 2
Tests
HCSC801 Application
Security 20 20 20 80 -- -- -- 100
Course Objectives:
Sr. No. Course Objectives
The course aims:
1 The terms and concepts of application Security, Threats, and Attacks
2 The countermeasures for the threats wrt Application security.
3 The Secure Coding Practices
4 The Secure Application Design and Architecture
5 The different Security Scanning and testing techniques
6 The threat modeling approaches

Course Outcomes:
Sr. No. Course Outcomes Cognitive levels of
attainment as per
Bloom’s
Taxonomy
On successful completion, of course, learner/student will be able to:
1 Enumerate the terms of application Security, Threats, and Attacks L1
2 Describe the countermeasures for the threa ts with respect to Application
security. L1
3 Discuss the Secure Coding Practices. L2
4 Explain the Secure Applicat ion Design and Architecture. L2
5 Review the different Security Scanning and testing techniques. L2
6 Discuss the threat modeling approaches. L2

DETAILED SYLLABUS:
Sr.
No. Module Detailed Content Hour
s CO
Mapping
0 Prerequisite Operating System, DBMS, Computer Network, Web
Programming, OOP 02 - Course Code Course
Title Theory Practical Tutorial Theory Practical/
Oral Tutorial Total
HCSC801 Application
Security 04 -- -- 04 -- -- 04

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I
Introduction to
Application
Security,
Threats, and
Attacks Introduction to Web Application Reconnaissance,
Finding Subdomains, API Analysis, Identifying Weak
Points in Application Architecture
Offense: Cross -Site Scripting (XSS), Cross -Site Request
Forgery (CSRF), XML External Entity (XXE) Injection,
Injection Attacks, Denial of Service (DoS), Cross -Origin
Resource Sharing Vulnerabilities
Self-learning Topics: Simulate the attacks using
open -source tools in virtual environment 05 CO1

II
Defence and
tools
Securing Modern Web Applications, Secure Application
Architecture, Reviewing Code for Security, Vulnerability
Discovery, Defending Against XSS Attacks, Defending
Against CSRF Attacks, Defending Against XXE,
Defending Against Injection attacks, Defending Against
DoS, Defending against CORS based attacks

Self-learning Topics: Implement the
countermeasures to the attacks using open -source
tools 09 CO2


III
Secure Coding
Practices
Security Requirements, Encryption, Never Trust System
Input, Encoding and Escaping, Third -Party Components,
Security Headers: Seatbelts for Web Apps, Securing Your
Cookies, Passwords, Storage, and Other Important
Decisions, HT TPS Everywhere, Framework Security
Features, File Uploads, Errors and Logging, Input
Validation and Sanitization, Authorization and
Authentication, Parameterized Queries, Least Privilege,
Requirements Checklist
Self-learning Topics: OWASP Secure Coding
Practices 09 CO3

IV
Secure
Application
Design and
Architecture



Secure Software Development Lifecycle
Averting Disaster Before It Starts, Team Roles for
Security, Security in the Software Development
Lifecycle,
Design Flaw vs. Security Bug,
Secure Design Concepts,
Segregation of Production Data, 09 CO4

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Application Security Activities
Self-learning Topics: Secure Hardware architecture

V
Security
Scanning and
testing


Testing Your Code, Testing Your Application, Testing
Your Infrastructure, Testing Your Database, Testing
Your APIs and Web Services, Testing Your Integrations,
Testing Your Network, Dynamic Web Application
Profiling

Self-learning Topics: Open -source Application
Security Tools, IAST, RASP and WAF, Selenium
09 CO5

VI
Threat
Modeling

Objectives and Benefits of Threat Modeling ,
Defining a Risk Mitigation Strategy, Improving
Application Security, Building Security in the Software
Development Life Cycle
Existing Threat Modeling Approaches
Security, Software, Risk -Based Variants
Threat Modeling Within the SDLC
Building Security in SDLC with Threat Modeling,
Integrating Threat Modeling Within the Different Types
of SDLCs,

Self-learnin g Topics: The Common Vulnerability
Scoring System (CVSS) 09 CO6
Text Books:
1.Alice and Bob Learn Application Security, by Tanya Janca Wiley; 1st edition (4 December 2020)
2. Web Application Security, A Beginner's Guide by Bryan Sullivan McGraw -Hill Education; 1st edition
(16 January 2012)
3. Web Application Security: Exploitation and Countermeasures for Modern Web
Applications by Andrew Hoffman Shroff/O'Reilly; First edition (11 March 2020)
4. The Security Development Lifecycle by Michael Howard Microsoft Press US; 1st edition (31 May 2006)
5. Risk Centric Threat Modeling Process for Attack Simulation And Threat Analysis, Tony
Ucedavélez and Marco m. Morana, Wiley
6. Iron -Clad Java: Building Secure Web Applications (Oracle Press) 1st Edition by Jim Manico

References:
1. Software Security: Building Security In by Gary McG raw Addison -Wesley Prof essional; 1st edition
(January 23, 2006)
2. A Guide to Securing Modern Web Applications by Michal Zalewski
3. Threat Modeling: A Practical Guide for Development Te ams by Izar Tarandach and Matthew J.
Coles Dec 8, 2020

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Online References:
Sr.
No. Website Name
1. https://owasp.org/www -project -top-ten/
2. https://owasp.org/www -pdf-archive/OWASP_SCP_Quick_Reference_Guide_v2.pdf
3. https://pentesterlab.com/
4. https://app.cybrary.it/browse/course/advanced -penetration -testing
5. https://www.udemy.com/
6. https://www.coursera.org/

Assessment:
Internal Assessment (IA) for 20 marks:
 IA will consist of Two Compulsory Internal Assessment Tests. Approximately 40% to 50%
of syllabus content must be covered in First IA Test and remaining 40% to 50% of syllabus
content must be covered in Second IA Test
 Question paper format
 Question Paper will comprise of a total of six questions each carrying 20 marks Q.1 will
be compulsory and should cover maximum contents of the syllabus
 Remaining questions will be mixed in nature (part (a) and part (b) of each question must
be from different modules. For example, if Q.2 has part (a) from Module 3 then part (b)
must be from any other Module randomly selected from all the modules)
 A total of four questions need to be answered








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University of Mumbai












Syllabus

Honours /Minor Degree Program
In
Augmented Reality and Virtual Reality



FACULTY OF SCIENCE & TECHNOLOGY

(As per AICTE guidelines with effect from the academic year 2022 -2023)

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University of Mumbai
Augmented Reality and Virtual Reality
(With effect from 2022 -23)
Year
& Sem
Course Code and
Course Title Teaching
Scheme Hours / Week Examination Scheme and Marks Credit
Scheme
Theory Seminar/
Tutorial Pract Internal
Assess
ment End
Sem
Exam Term
Work Oral/
Pract Total Credits

TE
Sem
V HARV RC501:
Virtual Reality 04 -- -- 20 80 -- -- 100 04
Total 04 - -- 100 - - 100 04
Total Credits = 04

TE
Sem.
VI HARV RC601:
AR and Mix Reality 04 -- -- 20 80 -- -- 100 04
Total 04 - - 100 - - 100 04
Total Credits = 04


BE
Sem.
VII HARV RC701:
ARVR Application -I 04 -- -- 20 80 -- -- 100 04
HARV RSBL701:
ARVR Lab (SBL) -- -- 04 -- -- 50 50 100 02
Total 04 - 04 100 50 50 200 06
Total Credits = 06

BE
Sem.
VIII
HARV RC801:
Game
Development with
VR 04 - -- 20 80 -- -- 100 04
Total 04 - - 100 - - 100 04
Total Credits = 04

Total Credits for Semesters V,VI, VII &VIII = 04+04+06+04 = 18

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Course Code Course
Title Examination Scheme
Theory Marks
Term
Work Practical Oral Total Internal assessment End Sem.
Exam Test1 Test 2 Avg.
HARV RC501
Virtual
Reality 20 20 20 80 -- -- -- 100

Course Objectives:
Sr. No. Course Objectives
The course aims:
1 To understand primitives of computer graphics fundamental.
2 To analyze various Hardware devices suitable for VR.
3 To analyze visual physiology and issues related to it.
4 To apply the knowledge of Visual rendering.
5 To evaluate problems faced due to audio scattering in VR.
6 To create different interface in VR environment.

Course Outcomes:
Sr. No. Course Outcomes Cognitive levels of
attainment as per
Bloom’s Taxonomy
On successful completion, of course, learner/student will be able to:
1 Solve Computer Graphics Problems. L1
2 Analyze application of VR hardware and software components. L1, L2, L3
3 Identify issues related to visual physiology. L1, L2
4 Integrate various shading and rendering techniques. L6
5 Solve problems due to Audio distortions. L5
6 Create User Interface for VR. L6

Prerequisite: Basic C programming
DETAILED SYLLABUS:

Sr. No. Module Detailed Content Hours CO
Mapping
0 Prerequisite Functioning of human sensory organs – EYE, Ear, Touch
etc. 02 -- Augmented Reality and Virtual Reality : Sem V
Course Code Course Title Theory Practical Tutorial Theory Practical Tutorial Total
HARV RC501
Virtual
Reality 04 -- -- 04 -- -- 04

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Light and Lenses
Basic functioning of camera
Matrix multiplication
I Geometry of
Virtual World
Geometric Modeling, 2D transformations, Homogenous
coordinate system, 3D rotation and 6 degree of freedom,
Viewport Transformation
Self: Eye Transformation, demo of 2D transformation 10 CO1
II Introduction
to VR
Introduction to VR and definitions and its components.,
Hardware components: Display devices: LCD, OLED
Audio: Speakers, Earphones, Bone conduction
Touch: Haptic Device
GPU and CPU, Input devices like game controller, data
glows, Joysticks
Tracking Hardware: Industrial measurement Unit -IMU,
Gyroscope, accelerometer
Software component: Java3D, VRML
Self: Feedback mechanisms in VR environment 07 CO2
III Visual
Physiology,
perception
and tracking
Functioning of Eye with photoreceptors, Resolution for VR,
Eye movements and issues with it in VR, Neuroscience of
vision, Depth and motion perception, Frame rates and
display, Orientation tracking, tilt and yaw drift correction,
Tracking with camera
Self: Light House approach 08 CO3
IV Visual
Rendering Overview, shading models, rendering pipelines,
rasterization, pixel shading, Distortion shading, post
rendering image wrap
Self: Rendering for VR application 09 CO4
V Audio Physics of Audio, Auditory Perception, localization,
rendering, Problems due to scattering of audio
Self: Study reaction of audio and other senses for VR
environment 10 CO5
VI Interfaces
Locomotion, Manipulation, system control, social
interaction using open -source tool like Gopro VR etc.
Self: Explore tools for UI in VR 06 CO6

Text Books:
1. Hearn and Baker, “Computer Graphics - C version”, 2nd edition, Pearson, 2002.
2. R. K Maurya, “Computer Graphics with Virtual Reality”, 3rd Edition, Wiley India, 2018.
3. Steven M. LaVelle,” Virtual Reality”, Cambridge University press, 2019

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4. Grigore Burdea, Philippe Coiffet, “Virtual Reality Technology”, 2nd Edition, Wiley India,
2003
5. Vince, “Virtual Reality Systems”, 1st Edition, Pearson Education, 2002

References:
1. George Mather, “Foundations of Sensation and Perception”, Psychology Press book; 3rd
Edition, 2016
2. Tony Parisi, “ Learning Virtual Reality”, 1st edition, O’Reilly, 2015
3. Alan Craig and William Sherman,” Understanding virtual reality: Interface, application and
design”, 2nd Edition, Morgan Kaufmann Publisher, 2019
4. Peter Shirley, Michael Ashikhmin, and Steve Marschner, “Fundamentals of Computer Graphics” , A K Peters/CRC
Press; 4th Edition, 2016.

Online Resources:
Sr. No. Website Name
1. https://nptel.ac.in/courses/121/106/121106013/#
2. http://msl.cs.uiuc.edu/vr/
3. http://lavalle.pl/vr/

Assessment:
Internal Assessment (IA) for 20 marks:
 IA will consist of Two Compulsory Internal Assessment Tests. Approximately 40% to 50% of syllabus
content must be covered in First IA Test and remaining 40% to 50% of syllabus content must be
covered in Second IA Test
 Question paper format
 Question Paper will comprise of a total of six questions each carrying 20 marks Q.1 will be
compulsory and should cover ma ximum contents of the syllabus
 Remaining questions will be mixed in nature (part (a) and part (b) of each question must be from
different modules. For example, if Q.2 has part (a) from Module 3 then part (b) must be from any
other Module randomly selected from all the modules)
 A total of four questions need to be answered







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169

Course Code Course Title Examination Scheme
Theory Marks
Term
Work Practical Oral Total Internal assessment End
Sem.
Exam Test1 Test 2 Avg. of 2
Tests
HARV RC601
AR and Mix
Reality 20 20 20 80 -- -- -- 100

Course Objectives:
Sr. No. Course Objectives
The course aims:
1 To understand the concepts of Augmented Reality and related technologies.
2 To understand the AR tracking system and use of computer vision in AR/MR.
3 To describe the technology for multimodal user interaction and authoring in AR.
4 To use different AR toolkits and apply them to develop AR applications.
5 To demonstrate AR Applications using Mobile AR Toolkits and SDKs.
6 To understand the use of AR/MR in interdisciplinary immersive applications.

Course Outcomes:
Sr. No. Course Outcomes Cognitive levels of
attainment as per
Bloom’s Taxonomy
On successful completion, of course, learner/student will be able to:
1 Identify and compare different Augmented Reality and Mixed Reality Technologies. L1, L2
2 Apply concepts of Computer Vision for tracking in AR and MR Systems. L3
3 Model different interfaces and authoring in AR/MR. L3
4 Design AR/MR applications using open source platforms and toolkits. L6
5 Design Mobile based AR Applications. L6
6 Apply insights of AR/MR in different applications. L3


Prerequisite : Programming Language, Computer Graphics, Virtual Reality
DETAILED SYLLABUS:
Module Title Description Hours CO
0 Pre-requisite Basics of Computer Graphics, Coordinate Systems, VR
Introduction, Tracking in VR 02 -- Augmented Reality and Virtual Reality : Sem VI
Course Code Course Title Theory Practical Tutorial Theory Practical Tutorial Total
HARV RC601
AR and Mix
Reality 04 -- -- 04 -- -- 04

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I Introduction
to Augmented
Reality and
Mixed Reality Definition and Scope, A Brief History of Augmented Reality, AR
Architecture, Related Fields of AR (like Mixed Reality, Virtual
Reality, Immersive Reality, Extended Re ality) and Their
comparison, General Architecture of Mixed Reality System,
Algorithm Steps in Mixed Reality

Self-Learning Topics : How AR/MR are related to Ubiquitous
Computing, Multidimensional Systems. 06 CO1
II Tracking and
Computer
Vision for AR
and MR Multimodal Displays; Visual Perception; Spatial Display Model;
Visual Displays; Tracking, Calibration and Registration;
Coordinate Systems; Characteristics of Tracking Technology;
Stationary Tracking Systems; Mobile Sensors; Optical Tracking;
Sensor Fus ion; Marker Tracking; Multiple Camera Infrared
Tracking; Natural Feature Tracking by Detection; Incremental
Tracking; Simultaneous Localization and Tracking; Outdoor
Tracking

Self-Learning Topics : Indoor Tracking, Full Body Tracking 07 CO2
III Interactio n,
Modeling and
Annotation
and Authoring Output Modalities, Input Modalities, Tangible Interfaces,
Virtual User Interfaces on Real Surfaces, Multi -view Interfaces,
Haptic Interaction, Multimodal Interaction, Specifying
Geometry, Specifying Appearance, Semi -automatic
Reconstruction, Free -form Modeling, Annotation,
Requirement of AR Authoring, Elements of Authoring, Stand -
alone Authoring Solutions, Plug -in Approaches, Web
Technology

Self-Learning Topics : Case Study on Object Annotation in Real
Time, Avatar M odeling. 08 CO3
IV Software
Architecture in
AR
and AR
Development
Toolkits AR Application Requirements, Software Engineering
Requirements, Distributed Object Systems, Data Flow, Scene
Graphs; Developer Support: Parameter Configuration,
Declarative Scripting, Procedural Scripting, Mixed Language
Programming, Runtime Reconfiguratio n, Choosing an AR
Platforms and Toolkits; AR Non -programming Frameworks, AR
Programming Frameworks, Programming AR using ARToolkit.

Self-Learning Topics : Commercial AR Frameworks, AR Related
Markup Languages 10 CO4
V Mobile AR Types of Mobile Apps, AR Browsers for Smartphones, Point of
Interests (POI) in Mobile AR, POI Authoring and Publishing
Tools, AR Applications for Android, AR Games for Android,
Mobile AR Toolkits and SDKs, Developing Mobile AR
Applications, AR Application Development for Android
Smartphone

Self-Learning Topics : AR Applications for iOS, AR Games for
iOS, AR Application Development for iOS Smartphone 10 CO5
VI Applications
of AR/MR and
Human Applications of AR/MR in: Edutainment, Medical, Military,
Production and Manufacturing, Navigation, Astronomical
Observation, E -commerce; What are Human Factors, Physical 07 CO6

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Factors, Legal
and Social
Considerations Side Effects, Visual Side Effects, Legal Considerations, Moral
and Ethical Considerat ions.

Self-Learning Topics : Applications of AR/MR in Civil
Construction and Architecture, Collaboration, Information
Control and Big Data Visualization

Textbooks :
1. Dieter Schmalsteig and Tobias Hollerer, “Augmented Reality - Principles and Practice”, Pearson Education,
Inc. 2016 Edition.
2. Chetankumar G Shetty, “Augmented Reality - Theory, Design and Development”, Mc Graw Hill, 2020 Edition.
3. Alan B. Craig, “Understanding Augmented Reality – Concepts and Applications”, Morgan Kaufmann, Elsevier,
2013 Edition.
References :
1. Borko Furht, “Handbook of Augmented Reality”, Springer, 2011 Edition.
2. Erin Pangilinan, Steve Lukas, and Vasanth Mohan, “Creating Augmented and Virtual Realities - Theory and
Practice for Next -Generation Spatial Computing”, O’Reill y Media, Inc., 2019 Edition.
3. Jens Grubert, Dr. Raphael Grasset, “Augmented Reality for Android Application Development”, PACKT
Publishing, 2013 Edition.
Online Resources:
Sr. No. Website Name
1. www.nptel.ac.in
2. www.coursera.org

Assessment:
Internal Assessment (IA) for 20 marks:
 IA will consist of Two Compulsory Internal Assessment Tests. Approximately 40% to 50% of syllabus
content must be covered in First IA Test and remaining 40% to 50% of syllabus content must be
covered in Second IA Tes t
 Question paper format
 Question Paper will comprise of a total of six questions each carrying 20 marks Q.1 will be
compulsory and should cover maximum contents of the syllabus
 Remaining questions will be mixed in nature (part (a) and part (b) of each question must be from
different modules. For example, if Q.2 has part (a) from Module 3 then part (b) must be from any
other Module randomly selected from all the modules)
 A total of four questions need to be answered

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172

Course Code Course Title Examination Scheme
Theory Marks
Term
Work Practical Oral Total Internal assessment End
Sem.
Exam Test 1 Test 2 Avg
HARV RC701
ARVR
Application -I 20 20 20 80 -- -- -- 100

Course Objectives:
Sr. No. Course Objectives
The course aims:
1 To learn the underlying concepts of Virtual Reality, Augmented Reality and related technologies.
2 To analyse the principles of VR design, prototype.
3 To analyse the principles of AR design, prototype.
4 To design Graphical User interface using VR
5 To identify trends in XR, key issues in XR and XR Tools.
6 To analyse privacy, ethical, social concern on AR/VR problem.

Course Outcomes:
Sr. No. Course Outcomes Cognitive levels of
attainment as per
Bloom’s Taxonomy
On successful completion, of course, learner/student will be able to:
1 Apply modelling techniques on Augmented Reality applications.. L1, L2, L3
2 Gets an overview of guidelines, methods, tools and pick design problems in Virtual
Reality. L1, L2
3 Gets an overview of guidelines, methods, tools and pick design problems in
Augmented Reality. L1, L2
4 Evaluate designs based on theoretical frameworks and build Graphical User
interface using VR, Tools L3, L4
5 Apply the appropriate XR development Approach on problem L3
6 Analyse main concerns with respect to designed solut ions and discuss the privacy,
ethical, social concerns. L3, L4
Prerequisite : Programming Language, Computer Graphics, Virtual Reality
DETAILED SYLLABUS:
Module Title Description Hours CO Augm ented Reality and Virtual Reality : Sem VII
Course Code Course Title Theory Practical Tutorial Theory Practical Tutorial Total
HARV RC701
ARVR
Application -I 04 -- -- 04 -- -- 04

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0 Prerequisite Fundamental Concept and Components of Virtual Reality,
Augmented Reality and Mixed Reality Technologie s,
Authoring in AR 02 --
I AR/VR
Concepts and
Technologies Difference between AR and VR , Rendering for VR/AR ,
Challenges with AR,AR systems and functionality
Augmented Reality Application Development : Types of
Augmented Reality Application (Location Based AR Apps
Marker -Based AR Applications), three -dimensional modeling
and computer vision , displays & tracking technologies
Self-learning Topic: Case study on Retail shopping using AR 08 CO1
II VR Design
Overview Principles of VR design, Overview o f guidelines, methods,
tools & design problem, Physical Prototyping for VR - Physical
prototype of potential solution, Digital Prototyping for VR -
tool choices, digital prototype of (key aspects of) solution
Self-learning Topic: Study of 3D navigation , layout and
contents 09 CO2
III AR Design
Overview Principles of AR design, Overview o f guidelines, methods,
tools & design problem, Physical Prototyping for AR - Physical
prototype of potential solution, Digital Prototyping for AR -
tool choices, digital prototype of (key aspects of) solution.
Self-learning Topic: Use of Anchors in AR 09 CO3
IV 3 D
interaction
with VR 3 D interaction Overvie w and types, Navigation in VR, Object
interaction, Graphical User interface using VR, Challenges in
VR interaction, Tools
Self-learning Topic: Case study of Mobile applications using
3D interface 10 CO4
V XR Application
Development XR overview, XR development Approach, XR design process,
Trends in XR, key issues in XR, Tools
Self-learning Topic: Difference between, AR, VR, MR and XR 10 CO5
VI Privacy and
security Privacy, Ethical, and Social Implications, and the Future of
AR/VR
Self-learning Topic: Case study on Privacy and security issues
using AR and VR 04 CO6

Textbooks :
1. John Vince, “ Virtual Reality Systems”, Pearson publication
2. Tony Parisi, “ Learning Virtual Reality”, O’REILLY’
3. Dieter Schmalsteig and Tobias Hollerer, “Augmented Reality - Principles and Practice”, Pearson Education, Inc.
2016 Edition.
4. Chetankumar G Shetty, “Augmented Reality - Theory, Design and Development”, Mc Graw Hill, 2020 Edition.
5. Alan B. Craig, “Understanding Augmented Reality – Concepts and Applications”, Morgan Kaufmann, Elsevier, 2013
Edition.

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174
References :
1. Borko Furht, “Handbook of Augment ed Reality”, Springer.
2. Erin Pangilinan, Steve Lukas, and Vasanth Mohan, “Creating Augmented and Virtual Realities - Theory and Practice
for Next -Generation Spatial Computing”, O’Reilly Media, Inc., 2019 Edition.
3. Jens Grubert, Dr. Raphael Grasset, “Augmented Reality for Android Application Development”, PACKT Publishing.
Online Resources:
Sr. No. Website Name
1 www.nptel.ac.in
2 www.coursera.org

Assessment:
Internal Assessment (IA) for 20 marks:
 IA will consist of Two Compulsory Internal Assessment Tests. Approximately 40% to 50% of syllabus
content must be covered in First IA Test and remaining 40% to 50% of syllabus content must be
covered in Second IA Test.
 Question paper format
 Question Paper will comprise of a total of six questions each carryin g 20 marks Q.1 will be
compulsory and should cover maximum contents of the syllabus
 Remaining questions will be mixed in nature (part (a) and part (b) of each question must be from
different modules. For example, if Q.2 has part (a) from Module 3 then part (b) must be from any
other Module randomly selected from all the modules)
 A total of four questions need to be answered












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Augmented Reality and Virtual Reality : Sem VII
Teaching Scheme
(Contact Hours) Credits Assigned
Course Code Course Title Theory Practical Tutorial Theory Practical Tutorial Total
HARV RSBL7 01
ARVR Lab
(SBL) -- 4 -- -- 2 -- 2

Course Code Course Title Examination Scheme
Theory Marks
Term
Work Oral Total Internal assessment End
Sem.
Exam Test1 Test2 Avg.
HARV RSBL601 ARVR Lab (SBL) -- -- -- -- 50 50 100

Lab Objectives:
Sr. No. Lab Objectives
The lab course aims:
1 To Understand the definition and significance of the VR,AR and MR.
2 To Design various applications in VR .
3 To Examine various audio tools for audio embedded in scene
4 To Explore AR and MR applications in real world
5 To develop interface for VR and AR applications
6 To Explore the interconnection and integration of the physical world and able to design & develop Mobile
applications.

Lab Outcomes
Sr. No. Lab Outcomes Cognitive levels of
attainment as per
Bloom’s Taxonomy
On successful completion, of course, learner/student will be able to:
1 Adapt different tools to implement VR,AR and MR. L1,L2
2 Demonstrate the working of VR background design. L1,L2
3 Apply audio tools and developed real world application. L1,L2,L3
4 Adapt different techniques for Integrating AR and MR concepts in applications. L5
5 Create interface for selected application L6
6 Create application and interface for mobile application /desktop version L6

Hardware & Software Requirements:
Hardware Requirements Software Requirements Other Requirements
PC With Following Configuration
1. PC i3/i5/i7 Processor or above.
2. 4 GB RAM
3. 500 GB Harddisk
4. Network interface card 1. Unity
2. Python
3.OpenCV
4. Solidity 1. Internet Connection.
Prerequisite: VR, AR and MR concepts

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Suggested List of Experiments
ARVR lab will describe the Designing of VR and AR applications using different Tools. It starts with installation of
software and then learner learn how to design background of various application. Now a day’s audio implementation
in VR scenes is also getting lots of attention so this aspect is also covered in the lab exper iments. AR and MR are
important concepts where learner design the applications for desktop as well as mobile environment.

Sr. No. Detailed Content LO Mapping
1 To install Open source software /Unity with its functionality LO1
2 Select real world application and design background for the same LO2
3 To add sound in the selected application using Open source software /Unity
software LO3
4 To study interface requirements and apply for the selected application LO3
5 Creating Your Digital Prototype of your objects/environment – (WebVR/ Sketchup /
Blender/Unity/Keynote/Figma) LO6
6 To implement a depth map with Python and OpenCV and using Unity LO5
7 Identify multiple surfaces and move objects between them using ARCore LO3
8 To study Interact with AR objects and detect collisions. LO2
9 Marker less Object Placement - WebAR LO4
10 In a group of three to five students develop one real world application in VR/ AR or
MR with object details and sound with good user interface LO6

Text Books/ References:
1. Hearn and Baker, “Computer Graphics - C version”, 2nd edition, Pearson, 2002.
2. R. K Maurya, “Computer Graphics with Virtual Reality”, 3rd Edition, Wiley India, 2018.
3. Dieter Schmalsteig and Tobias Hollerer, “Augmented Reality - Princip les and Practice”, Pearson Education, Inc.
2016 Edition.
4. Chetankumar G Shetty, “Augmented Reality - Theory, Design and Development”, Mc Graw Hill, 2020 Edition.
5. Alan B. Craig, “Understanding Augmented Reality – Concepts and Applications”, Morgan Kaufmann, E lsevier, 2013
Edition.
Online Resources:
Sr. No. Website Name
1. https://nptel.ac.in/courses/121/106/121106013/#
2. http://msl.cs.uiuc.edu/vr/
3. http://lavalle.pl/vr
4. http://nptel.ac.in
5. www.coursera.org

Term Work:
The Term work shall consist of at least 10 to 12 practical based on the above syllabus. The term work Journal must
include at least 2 assignments. The assignments should be based on real world applications which cover concepts
from all above syllabus .
Term Work Marks: 50 Marks (Total marks) = 40 Marks (Experiment) + 5 Marks (Assignments/tutorial/write up) + 5
Marks (Attendance)
Oral Exam: An Oral exam will be held based on the above syllabus.

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177

Course Code Course Title Examination Scheme
Theory Marks
Term
Work Practical Oral Total Internal assessment End
Sem.
Exam Test1 Test 2 Avg.
HARV RC801
Game Development
with VR 20 20 20 80 -- -- -- 100

Course Objectives
Sr. No. Course Objectives
The course aims:
1 The different genres of game and explain the Unity UI Basics.
2 The use of navigation and cursor control to create a game environment.
3 How to import assets, interact with them using action objects and manage object states.
4 To build transitions by scripting events ,using physics, particle systems, and other Unity functionality action
sequences with UnityGUI design.
5 To build the game project together by handling mecanim ,using dialogue trees, creating and setting up the
game environment and menus for the game.
6 The VR development in Unity.
Course Outcomes
Sr.
No. Course Outcomes Cognitive levels of
attainment as per
Bloom’s Taxonomy
On successful completion, of course, learner/student will be able to:
1 Identify the different genres of game and explain the Unity UI Basics L1,L2
2 Make use of navigation and cursor control to create a game
environment L3
3 Apply how to import assets ,interact with them using action objects
and manage object states L3
4 Build transitions by scripting events ,using physics, particle systems,
and other Unity functionality action sequences with UnityGUI design L3
5 Build the game project together by handling mecanim ,using
dialogue tr ees,creating and setting up the game environment and
menus for the game L3
6 Explain VR development in Unity L2

Prerequisite: Basics of VR
DETAILED SYLLABUS: Augmented Reality and Virtual Reality : Sem VIII
Course Code Course Title Theory Practical Tutorial Theory Practical Tutorial Total
HARV RC801
Game
Development
with VR 04 -- -- 04 -- -- 04

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178
Sr.
No. Module Detailed Content Hours CO
Mapping
0 Prerequisite VR Basic concepts 02 -
I Game
Development
and Unity UI
Basics


The Adventure Genre, Fast Forward to Real -Time, What Draws
People to This Genre? Designing Your Game: Defining a Style,
Compartmentalizing Environments, First -Person or Third?
Animation, Basic Human Characteristics Make for Fun? Managing
Your Project, Tips for Completing the Game, Real Time vs. Pre -
render.AI in Gaming -AI Guidelines, a simple workflow.
Unity UI: The Layout, Toolbar, Menus, Creating Simple Objects,
Selecting and Focusing, Transforming Objects In 3D, Snaps, Scene
Gizmo.Lights,3D Objects, Materials
Scripting: What is a script? Components of a Script, Picking an
Object in the Game, Conditionals and State, Order of Evaluation
Self-learning Topics: Understanding the role of AI in gaming 08 CO1







II Navigation and
Cursor Control
Creating Environments, Navigation -Arrow Navigation and Input,
Fun with Platforms, Collision Walls, Cursor visibility, Custom
cursors, GUI Texture Cursor, Hardware Cursor, UnityGUI Cursor,
Object -to-Object Communication, Mouse over Cursor Changes,
Object Reaction to Mouseover
Self-learning Topics: Multimodal Gaming for Navigation Skills in
Players Who Are Blind 06 CO2
III Imported
Assets, Objects
& Managing
states
Imported Assets:3D Art Assets, Setting Up Materials, Shadows.
Action Objects: Colliders, Triggering Animation, Adding Sound F/X,
Managing States: Identifying the Action Objects, Developing a
State Machine, Lookup Table, Scripting in Unity, Picking a script
Editor, Fundamentals of scripting in Unity. The Object Lookup
Script, Action -Related Messages
Self-learning Topics: Study the new Asset Import Pipeline: Solid
foundation for speeding up asset imports, Effects of scripting on
dialogues. 09 CO3
IV Transitions,
Text
Management

Processing the Auxiliary Objects, Handling Object Visibility,
Ensuring Player Focus,
Adding New Assets, Physics, Combining Physics and Keyframe
Animation, Particle systems,
GUI Skin, Text Visibility, Using Layers, Creating the Inventory
Screen, Adding Inventory Icons, Managing the inventor y.
Self-learning Topics: Importance of effective Text management in
Gaming 09 CO4

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179
V Game
Deployment
Dialogue Trees, The Scenario, Starting a Conversation, Mecanim
and Characters, Game Environment, Setting up the game, Menus
and levels
Self-learning Topics: Branching dialogue trees and its effect in
Gaming. Study of different UI designs for Menus in Games. 09 CO5
VI XR
development
in Unity

Unity platform and services, XR Getting started with AR
development in Unity , Getting started with VR development in
Unity , XR Plug -in Framework , Configuring your Unity Project for
XR, Universal Render Pipeline compatibility in XR , XR API
reference , Single Pass Stereo rendering (Double -Wide rendering) ,
VR Audio Spatializers , VR frame timing ,Unity XR SDK , Open -source
repositories using Bitbucket, Asset Store Publishing, use of unity as
library in other application.
Self-learning Topics: Study any open source tool for VR
Development 09 CO6
Text Books:
1. Beginning 3D Game Development with Unity 4 All -in-one Multi -platform Game development, 2nd Edition,
Apress, Sue Backman
2. Game Development with Unity 2nd Edition, Michelle Menard and Bryan Wagstaff
3. Unity Game development Essentials, Will Goldstone, PACKT Publishing
4. Unity Game Development Cookbook -Essentials for every Game, O’reilly, Paris Buttfield -Addison, Jon Manning -
Tim Nugent.

Reference Books:
1. Introduction to Gam Development, Second Edition, Steve Rabin, CENGAGE Learning
2. Sams Teach Yourself Unity Game Development in 24 Hours -Mike Geig
Online References:
Sr. No. Website Name
1. https://docs.unity3d.com/Manual/VROverview.html
2. https://www.coursera.org/
3. https://www.udemy.com/

Assessment:
Internal Assessment (IA) for 20 marks:
 IA will consist of Two Compulsory Internal Assessment Tests. Approximately 40% to 50% of syllabus
content must be covered in First IA Test and remaining 40% to 50% of syllabus content must be
covered in S econd IA Test
 Question paper format
 Question Paper will comprise of a total of six questions each carrying 20 marks Q.1 will be
compulsory and should cover maximum contents of the syllabus
 Remaining questions will be mixed in nature (part (a) and part (b) of each question must be from
different modules. For example, if Q.2 has part (a) from Module 3 then part (b) must be from any
other Module randomly selected from all the modules)
 A total of four questions need to be answered

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180

University of Mumbai




Syllabus for

Honours /Minor Degree Program
In
Artificial Intelligence and Machine Learning



FACULTY OF SCIENCE & TECHNOLOGY

(As per AICTE guidelines with effect from the academic year 2022 -2023)




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181
University of Mumbai
Artificial Intelligence and Machine Learning (AI&ML)
(With effect from 2022 -23) Year & Sem
Course Code &
Course Title Teaching Scheme Hrs
/ Week Examination Scheme and Marks Credit Scheme Theory
Seminar /
Tutorial
Practical
Internal
Assessment
End Sem
Exam
Term Work
Oral
Total
Credits
TE
Sem
V HAIML C501:
Mathematics
for AI & ML 04 -- -- 20 80 -- -- 100 04
Total 04 - -- 100 - - 100 04
Total Credits = 04

TE
Sem
VI HAIML C601:
Game Theory
using AI & ML 04 -- -- 20 80 -- -- 100 04
Total 04 - - 100 - - 100 04
Total Credits = 04

BE
Sem
VII HAIML C701:
AI&ML in
Healthcare 04 -- -- 20 80 -- -- 100 04
HAIML SBL701:
AI&ML in
Healthcare:
Lab -- -- 04 -- -- 50 50 100 02
Total 04 - 04 100 50 50 200 06
Total Credits = 06

BE
Sem
VIII HAIML C801:
Text, Web and
Social Media
Analytics 04 - -- 20 80 -- -- 100 04
Total 04 - - 100 - - 100 04
Total Credits = 04

Total Credits for Semesters V,VI, VII &VIII = 04+04+06+04 = 18

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182
Module
No. Topics Hrs.
1.0 Linear Algebra 05
1.1 Vectors and Matrices, Solving Linear equations, The four Fundamental Subspaces,
Eigenvalues and Eigen Vectors, The Singular Value Decomposition (SVD).
2.0 Probability and Statistics 09
2.1 Introduction, Random Variables and their probability Distribution, Random Sampling,
Sample Characteristics and their Distributions, Chi -Square, t -, and F -Distributions: Exact
Sampling Distributions, Sampling from a Bivariate Normal Distribution, The Central Limit
Theorem.
3.0 Introduction to Graphs 10 Artificial Intelligence and Machine Learning: Sem V
Course
Code Course
Name Teaching Scheme (Contact
Hours) Credits Assigned
Theory Practical Tutorial Theory Practical Tutorial Total
HAIML C501 Mathematics
for AI&ML 04 -- -- 04 -- -- 04
Course
Code Course
Name Examination Scheme
Theory Marks Exam
Duration
In Hours Term
Work Practical
and
Oral Total
Internal Assessment End
Sem.
Exam. Test1 Test2 Avg.
HAIML C501 Mathematics
for AI&ML 20 20 20 80 03 -- -- 100
Course Prerequisites:
Applied Mathematics, Discrete mathematics
Course Objectives:
1 To build an intuitive understanding of Mathematics and relating it to Artificial Intelligence, Machine Learning
and Data Science.
2 To provide a strong foundation for probabilistic and statistical analysis mostly used in varied applications in
Engineering.
3 To focus on exploring the data with the help of graphical representation and drawing conclusions.
4 To explore optimization and dimensionality reduction tech niques.
Course Outcomes:
After successful completion of the course, the student will be able to:
1 Use linear algebra concepts to model, solve, and analyze real -world problems.
2 Apply probability distributions and sampling distributions to various business problems.
3 Select an appropriate graph representation for the given data.
4 Apply exploratory data analysis to some real data sets and provide interpretations via relevant visualization
5 Analyze various optimization techniques.
6 Describe Dimension Reduction Algorithms

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183
3.1 Quantitative vs. Qualitative data, Types of Quantitative data: Continuous data, Discrete
data, Types of Qualitative data: Categorical data, Binary data, Ordina ry data, Plotting data
using Bar graph, Pie chart, Histogram, Stem and Leaf plot, Dot plot, Scatter plot, Time -series
graph, Exponential graph, Logarithmic graph, Trigonometric graph, Frequency distribution
graph.
4.0 Exploratory Data Analysis 09
4.1 Need of exploratory data analysis, cleaning and preparing data, Feature engineering,
Missing values, understand dataset through various plots and graphs, draw conclusions,
deciding appropriate machine learning models.
5.0 Optimization Techniques 10
5.1 Types of optimization -Constrained and Unconstrained optimization, Methods of
Optimization -Numerical Optimization, Bracketing Methods -Bisection Method, False
Position Method, Newton’s Method, Steepest Descent Method, Penalty Function
Method.
6.0 Dimension Reduction Algorithms 05
6.1 Introduction to Dimension Reduction Algorithms, Linear Dimensionality Reduction:
Principal component analysis, Factor Analysis, Linear discriminant analysis.
6.2 Non -Linear Dimensionality Reduction: Multidimension al Scaling, Isometric Feature
Mapping. Minimal polynomial
Total 48

Text Books:
1 Linear Algebra for Everyone,
2 Gilbert Strang, Wellesley Cambridge Press.
3 An Introduction to Probability and Statistics, Vijay Rohatgi, Wiley Publication
4 An introduction to Optimization, Second Edition, Wiley -Edwin Chong, Stainslaw Zak.
5 Mathematics for Machine Learning, Marc Peter Deisenroth, A. Aldo Fa isal, Cheng Soon Ong, Cambridge
University Press.
6 Exploratory Data Analysis, John Tukey, Princeton University and Bell Laboratories.
References:
1 Introduction to Linear Algebra, Gilbert Strang.
2 Advanced Engineering Mathematics, Erwin Kreyszig
3 Mehryar Mohri, Afshin Rostamizadeh, and Ameet Talwalkar. Foundations of Machine Learning. MIT Press,
2018.
4 Shai Shalev -Shwartz and Shai Ben -David. Understanding Machine Learning: From Theory to Algorithms.
Cambridge University Press, 2014
5 Last updated on Sep 9, 2018.
6 Mathematics and Programming for Machine Learning with R, William B. Claster, CRC Press,2020
Useful Links:
1 https://math.mit.edu/~gs/linearalgebra/
2 https://www.coursera.org/learn/probability -theory -statistics
3 https://nptel.ac.in/courses/111/105/111105090/
4 https://onlinecourses.nptel.ac.in/noc21_ma01/preview
5 https://ocw.mit.ed u/courses/mathematics/18 -06-linear -algebra -spring -2010/video -lectures/

Assessment:
Internal Assessment: (20)
1 Assessment consists of two class tests of 20 marks each.

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184
2 The first -class test is to be conducted when approx. 40% syllabus is completed and second -class test when
additional 40% syllabus is completed.
3 Duration of each test shall be one hour.
End Semester Theory Examination: (80)
1 Question paper will comprise of total 06 questions, each carrying 20 marks .
2 Question No: 01 will be compulsory and based on the entire syllabus wherein 4 to 5 sub -questions will be
asked.
3 Remaining questions will be mixed in nature and randomly selected from all the modules.
4 Weightage of each module will be proportional to number of respec tive lecture hours as mentioned in the
syllabus.
5 Total 04 questions need to be solved.


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185
Artificial Intelligence and Machine Learning: Sem VI
Course
Code Course Name Teaching Scheme (Contact
Hours) Credits Assigned
Theory Practical Tutorial Theory Practical Tutorial Total
HAIML C601 Game Theory
using AI & ML 04 -- -- 04 -- -- 04

Course
Code Course Name Examination Scheme
Theory Marks Exam
Duration
In Hours Term
Work Practical
and Oral Total
Internal Assessment End Sem.
Exam.
Test1 Test2 Avg.
HAIML C601 Game Theory
using AI & ML 20 20 20 80 03 -- -- 100

Course Prerequisites:
Knowledge of probability theory, discrete mathematics, and algorithm design is required.
Course Objectives:
1 To acquire the knowledge of game theory.
2 To understand the basic concept of AI, strength and weakness of problem solving and search
3 To study about various heuristic and game search algorithms
4 To optimize the different linear methods of regression and classification
5 To interpret the different supervised classification methods of support vector machine.
6 To acquire the knowledge of different generative models through unsupervised learnin g
Course Outcomes:
After successful completion of the course, the student will be able to:
1 Understand basic concept of game theory.
2 Evaluate Artificial Intelligence (AI) methods and describe their foundations
3 Analyze and illustrate how search algorithms play vital role in problem solving, inference, perception,
knowledge representation and learning
4 Demonstrate knowledge of reasoning and knowledge representation for solving real world problems
5 Recognize the characteristics of machine learning that makes it useful to realworld problems and apply
different dimensionality reduction techniques
6 Apply the different supervised learning methods of support vector machine and tree based models

Module
No. Topics Hours.
1.0 Introduction to Game Theory 05
1.1 Introduction, The theory of rational choice, Games with Perfect Information, Nash
Equilibrium: Theory, Prisoner’s Dilemma, Stag Hunt, Matching pennies, BOS, Multi NE,
Cooperative and Competitive Games, Strict and Non Strict NE, Best response functions
for NE.
1.2 Nash Equilibrium: Illustrations, Cournot’s model of oligopoly, Bertrand’s model of
oligopoly, Electoral competition, The War of Attrition, Auctions, Mixed Strategy
Equilibrium, Strategic games in which players may randomize, Dominated actions,
Extensive Games with Perfect Information

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186
2.0 Games with Imperfect Information 09
2.1 Bayesian Games, Introduction, Motivational examples, General definitions, two
examples concerning information, Strictly Competitive Games and Maxminimization ,
Rationalizability
2.2 Evolutionary Equilibrium, Monomorphic pure strategy equilibrium, Mixed strategies
and polymorphic equilibrium, Repeated games: The Prisoner’s Dilemma, Infinitely
repeated games, Strategies, General Results,
3.0 Introductio n to AI & Problem Solving 10
3.1 Definitions – Foundation and History of AI, Evolution of AI - Applications of AI,
Classification of AI systems with respect to environment. Artificial Intelligence vs
Machine learning,
3.2 Heuristic Search Techniques: Generate -and-Test; Hill Climbing; Properties of A*
algorithm, Best first Search; Problem Reduction.
3.3 Beyond Classical Search: Local search algorithms and optimization problem, local
search in continuous spaces, searching with nondetermin istic action and partial
observation, online search agent and unknown environments
4.0 Knowledge and Reasoning 09
4.1 Knowledge and Reasoning: Building a Knowledge Base: Propositional logic, first order
Logic, situation calculus. Theorem Proving i n First Order Logic, Planning, partial order
planning. Uncertain Knowledge and Reasoning, Probabilities,
4.2 Bayesian Networks. Probabilistic reasoning over time: time and uncertainty, hidden
Markova models, Kalman filter, dynamic bayesian network, keeping track of many
objects
5.0 Introduction to ML 10
5.1 Introduction to Machine Learning, Examples of Machine Learning Applications, Learning
Types, Supervised Learning -Learning a Class from Examples, Vapnik - Chervonenkis (VC)
Dimen sion, Probably Approximately Correct (PAC) Learning, Noise, Learning Multiple
Classes, Regression, Model Selection and Generalization, Dimensions of a Supervised
Machine Learning Algorithm
5.2 Introduction, Linear Regression Models and Least Squares, Subset Selection, Shrinkage
Methods, Logistic Regression - Fitting Logistic Regression Models,
Quadratic Approximations and Inference, L1 Regularized Logistic Regression,
SVM -Introduction to SVM, The Support Vector Classifier, Support Vector Machines a nd
Kernels - Computing the SVM for Classification
6.0 Unsupervised Learning 05
6.1 Introduction, Association Rules -Market Basket Analysis, The Apriori Algorithm,
Unsupervised as Supervised Learning, Generalized Association Rules, Cluster Analysis
Proximity Matrices,
Clustering Algorithms -K-mean, Gaussian Mixtures as Soft K -means Clustering, Example:
Human Tumor Microarray Data, Vector Quantization, K -medoids, Hierarchical
Clustering, Self -Organizing Maps, PCA -Spectral Clustering
6.2 Hidden Markov Models -Introduction, Discrete Markov Processes, Hidden Markov
Models, Three Basic Problems of HMMs, Evaluation Problem, Finding the State
Sequence, Learn ing Model Parameters, Continuous Observations, The HMM with
Input, Model Selection in HMM
Total 48

Text Books:

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187
1 Martin Osborne, An Introduction to Game Theory, Oxford University Press.
2 Russell, S. and Norvig, P. 2015. Artificial Intelligence - A Modern Approach, 3rd edition,Prentice Hall
3 Introduction to Machine Learning Edition 2, by Ethem Alpaydin
References:
1 Thomas Ferguson, Game Theory, World Scientific, 2018.
2 Stef Tijs. Introduction to Game Theory, Hindustan Book Agency
3 J. Gabriel, Artificial Intelligence: Artificial Intelligence for Humans (Artificial Intelligence, Machine Learning),
Create Space Independent Publishing Platform, First edition , 2016
4 Introduction to Artificial Intelligence & Expert Systems, Dan W Patt erson, PHI.,2010 2. S Kaushik, Artificial
Intelligence, Cengage Learning, 1st ed.2011
5 Machine Learning. Tom Mitchell. First Edition, McGraw - Hill, 1997

Assessment:
Internal Assessment: (20)
1 Assessment consists of two class tests of 20 marks each.
2 The first -class test is to be conducted when approx. 40% syllabus is completed and second -class test when
additional 40% syllabus is completed.
3 Duration of each test shall be one hour.
End Semester Theory Examination: (80)
1 Question paper will comprise of total 06 questions, each carrying 20 marks .
2 Question No: 01 will be compulsory and based on the entire syllabus wherein 4 to 5 sub -questions will be
asked.
3 Remaining questions will be mixed in nature and randomly selec ted from all the modules.
4 Weightage of each module will be proportional to number of respective lecture hours as mentioned in the
syllabus.
5 Total 04 questions need to be solved.














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Artificial Intelligence and Machine Learning: Sem VII
Course Code Course
Name Teaching Scheme (Contact
Hours) Credits Assigned
Theory Practical Tutorial Theory Practical Tutorial Total
HAIML C701 AI&ML in
Healthcare 04 -- -- 04 -- -- 04

Course Code Course
Name Examination Scheme
Theory Marks Exam
Duration
In Hours Term
Work Practical and
Oral Total
Internal Assessment End
Sem.
Exam. Test1 Test2 Avg.
HAIML C701 AI&ML in
Healthcare 20 20 20 80 03 -- -- 100

Course Prerequisites:
Artificial Intelligence, Machine Learning
Course Objectives: The course aims
1 To understand the need and significance of AI and ML for Healthcare .
2 To study advanced AI algorithms for Healthcare.
3 To learn Computational Intelligence techniques .
4 To understand evaluation metrics and ethics in intelligence for Healthcare systems,
5 To learn various NLP algorithms and their application in Healthcare,
6 To investigate the current scope, implications of AI and ML for developing futuristic Healthcare Applications.
Course Outcomes:
After successful completion of the course, the student will be able to:
1 Understand the role of AI and ML for handling Healthcare data.
2 Apply Advanced AI algorithms for Healthcare Problems.
3 Learn and Apply various Computational Intelligence techniques fo r Healthcare Application.
4 Use evaluation metrics for evaluating healthcare systems.
5 Develop NLP applications for healthcare using various NLP Techniques..
6 Apply AI and ML algorithms for building Healthcare Applications

Module Topics Hours.
1.0 Introduction 04
1.1 Overview of AI and ML,A Multifaceted Discipline, Applications of AI in Healthcare -
Prediction, Diagnosis, personalized treatment and behavior modification, drug
discovery, followup care etc,
1.2 Realizing potential of AI and ML in healthcare, Healthcare Data - Use Cases.
2.0 AI, ML, Deep Learning and Data Mining Methods for Healthcare 10
2.1 Knowledge discovery and Data Mining, ML, Multi classifier Decision Fusion, Ensemble
Learning, Meta -Learning and other Abstract Methods.
2.2 Evolutionary Algorithms, Illustrative Medical Application -Multiagent Infectious Disease
Propagation and Outbreak Prediction, Automated Amblyopia Screening System etc.
2.3 Computational Intelligence Techniques, Deep Learning, Unsupervise d learning,
dimensionality reduction algorithms.

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3.0 Evaluating learning for Intelligence 06
3.1 Model development and workflow, evaluation metrics, Parameters and
Hyperparameters, Hyperparameter tuning algorithms, multivariate testing, Ethics of
Intelligence.
4.0 Natural Language Processing in Healthcare 08
4.1 NLP tasks in Medicine, Low -level NLP components, High level NLP components, NLP
Methods.
4.2 Clinical NLP resources and Tools, NLP Applications in Healthcare. Model Interpretability
using Explainable AI for NLP applications.
5.0 Intelligent personal Health Record 04
5.1 Introduction, Guided Search for Disease Information, Recommending SCA's.
Recommending HHP's , Continuous User Monitoring.
6.0 Future of Healthcare using AI and ML 07
6.1 Evidence based medicine, Personalized Medicine, Connected Medicine, Digital Health
and Therapeutics, Conversational AI, Virtual and Augmented Reality, Blockchain for
verifying supply chain, patient record access, Robot - Assisted Surg ery, Smart Hospitals,
Case Studies on use of AI and ML for Disease Risk Diagnosis from patient data,
Augmented reality applications for Junior doctors.
6.2 Blockchain for verifying supply chain, patient record access, Robot - Assisted Surgery,
Smart Hospitals, Case Studies on use of AI and ML for Disease Risk Diagnosis from
patient data, Augmented reality applications for Junior doctors.
Total 48

Textbooks:
1 Arjun Panesar, "Machine Learning and AI for Healthcare”, A Press.
2 Arvin Agah, "Medical applications of Artificial Systems ", CRC Press
References:
1 Erik R. Ranschaert Sergey Morozov Paul R. Algra, “Artificial Intelligence in medical Imaging -
Opportunities, Applications and Risks”, Springer
2 Sergio Consoli Diego Reforgiato Recupero Milan Petković,“Data Science for Healthcare -
Methodologies and Applications”, Springer
3 Dac-Nhuong Le, Chung Van Le, Jolanda G. Tromp, Gia Nhu Nguyen, “Emerging technologies for
health and medicine”, Wiley.
4 Ton J. Cleophas • Aeilko H. Zwinderman, “Machine Learning in Medicine - Complete Overview”,
Springer

Assessment:
Internal Assessment: (20)
1 Assessment consists of two class tests of 20 marks each.
2 The first -class test is to be conducted when approx. 40% syllabus is completed and second -class test
when additional 40% syllabus is completed.
3 Duration of each test shall be one hour.
End Semester Theory Examination: (80)
1 Question paper will comprise of total 06 questions, each carrying 20 marks .
2 Question No: 01 will be compulsory and based on the entire syllabus wherein 4 to 5 sub -questions
will be asked.
3 Remaining questions will be mixed in nature and randomly selec ted from all the modules.
4 Weightage of each module will be proportional to number of respective lecture hours as mentioned
in the syllabus.
5 Total 04 questions need to be solved.

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Artificial Intelligence and Machine Learning: Sem VIII
Course Code Course Name Teaching Scheme (Contact
Hours) Credits Assigned
Theory Practical Tutorial Theory Practical Tutorial Total
HAIML C801 Text, Web and
Social Media
Analytics 04 -- -- 04 -- -- 04

Course Code Course Name Examination Scheme
Theory Marks Exam
Duration
In Hours Term
Work Practical
and
Oral Total
Internal Assessment End
Sem.
Exam. Test1 Test2 Avg.
HAIML C801 Text, Web and
Social Media
Analytics 20 20 20 80 03 -- -- 100

Course Prerequisites:
Python, Data Mining
Course Objectives: The course aims
1 To have a strong foundation on text, web and social media analytics.
2 To understand the complexities of extracting the text from different data sources and analysing it.
3 To enable students to solve complex real -world problems using sentiment analysis and Recommendation
systems.
Course Outcomes:
After successful completion of the course, the student will be able to:
1 Extract Information from the text and perform data pre -processing
2 Apply clustering and classific ation algorithms on textual data and perform prediction.
3 Apply various web mining techniques to perform mining, searching and spamming of web data.
4 Provide solutions to the emerging problems with social media using behaviour analytics and Recommendation
systems.
5 Apply machine learning techniques to perform Sentiment Analysis on data from social media.

Module Topics Hours.
1.0 Introduction 06
1.1 Introduction to Text Mining: Introduction, Algorithms for Text Mining, Future Directions
1.2 Information Extraction from Text : Named Entity Recognition, Relation Extraction,
Unsupervised Information Extraction
1.3 Text Representation: tokenization, stemming, stop words, NER, N -gram modelling
2.0 Clustering and Classification 10

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2.1 Text Clustering : Feature Selection and Transformation Methods, distance based
Clustering Algorithms, Word and Phrase based Clustering, Probabilistic document
Clustering
2.2 Text Classification : Feature Selection, Decision tree Classifiers, Rule -based Classifiers,
Probabilistic based Classifiers, Proximity based Classifiers.
2.3 Text Modelling: Bayesian Networks, Hidden Markovian Models, Markov random Fields,
Conditional Random Fields
3.0 Web -Mining: 05
3.1 Introduction to Web -Mining: Inverted indices and Compression, Latent Semantic
Indexing, Web Search,
3.2 Meta Search: Using Similarity Scores, Rank Positons
3.3 Web Spamming : Content Spamming, Link Spamming, hiding Techniques, and
Combating Spam
4.0 Web Usage Mining: 05
4.1 Data Collection and Pre -processing, Sources and types of Data, Data Modelling, Session
and Visitor Analysis, Cluster Analysis and Visitor segmentation, Association and
Correlation Analysis, Analysis of Sequential and Navigational Patterns, Classification and
Prediction based on Web User Transactions.
5.0 Social Media Mining : 05
5.1 Introduction, Challenges, Types of social Network Graphs
5.2 Mining Social Media: Influence and Homophily, Behaviour Analytics, Recommendation
in Social Media: Challenges, Classical recommendation Algorithms, Recommendation
using Social Context, Evaluating recommendations.
6.0 Opinion Mining and Sentiment Analysis : 08
6.1 The problem of opinion mining,
6.2 Document Sentiment Classification : Supervised, Unsupervised
6.3 Opinion Lexicon Expansion: Dictionary based, Corpus based
6.4 Opinion Spam Detection : Supervised Learning, Abnormal Behaviours, Group Spam
Detection.

Total 48

Textbooks:
1 Daniel Jurafsky and James H. Martin, “Speech and Language Processing,” 3rd edition, 2020
2 Charu. C. Aggarwal, Cheng Xiang Zhai, Mining Text Data, Springer Science and Business Media, 2012.
3 BingLiu, “Web Data Mining -Exploring Hyperlinks, Contents, and Usage Data”, Springer, Second Edition, 2011.

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4 Reza Zafarani, Mohammad Ali Abbasiand Huan Liu, “Social Media Mining - An Int roduction”, Cambridge
University Press, 2014

Assessment:
Internal Assessment: (20)
1 Assessment consists of two class tests of 20 marks each.
2 The first -class test is to be conducted when approx. 40% syllabus is completed and second -class test when
additional 40% syllabus is completed.
3 Duration of each test shall be one hour.
End Semester Theory Examination: (80)
1 Question paper will comprise of total 06 questions, each carrying 20 marks .
2 Question No: 01 will be compulsory and based on the entire syllabus wherein 4 to 5 sub -questions will be
asked.
3 Remaining questions will be mixed in nature and randomly selected from all the modules.
4 Weightage of each module will be proportional to number of respective lecture hours as mentioned in the
syllabus.
5 Total 04 questions need to be solved.


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193
Artificial Intelligence and Machine Learning:Sem V II
Course Code Course Name Teaching Scheme (Contact
Hours) Credits Assigned
Theory Practical Tutorial Theory Practical Tutorial Total
HAIML SBL701 AI&ML in
Healthcare: Lab -- 04 -- -- 02 -- 02

Course Code Course Name Examination Scheme
Theory Marks Exam
Duration Term
Work Oral Total
Internal Assessment End
Sem.
Exam. Test1 Test2 Avg.
HAIML SBL701 AI&ML in
Healthcare: Lab 50 50 100

Course Prerequisites:
Python
Course Outcomes:
After successful completion of the course, the student will be able to:
1 Students will be able to understand computational models of AI and ML.
2 Students will be able to develop healthcare applications using appropriate computational tools.
3 Students will be able to apply appropriate models to solve specific healthcare problems.
4 Students will be able to analyze and justify the performance of specific models as appl ied to healthcare
problems.
5 Students will be able to design and implement AI and ML -based healthcare applications.

Suggested Experiments:
Sr.
No. Name of the Experiment
1 Collect, Clean, Integrate and Transform Healthcare Data based on specific disease.
2 Perform Exploratory data analysis of Healthcare Data.
3 AI for medical diagnosis based on MRI/X -ray data.
4 AI for medical prognosis .
5 Natural language Entity Extraction from medical reports.
6 Predict disease risk from Patient data.
7 Medical Reviews Analysis from social media data.
8 Explainable AI in healthcare for model interpretation.
9 Mini Project -Design and implement innovative web/mobile based AI application using Healthcare
Data.
10 Documentation and Presentation of Mini Project.

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Useful Links:
1 https://www.coursera.org/learn/introduction -tensorflow?specialization=tensorflow -in-practice
2 https://www.coursera.org/learn/convolutional -neural -networks -tensorflow?specialization=tensorflow -in-practice
3 https://datarade.ai/data -categories/electronic -health -record -ehr-data
4 https://www.cms.gov/Medicare/E -Health/ EHealthRecords
5 https://www.coursera.org/learn/tensorflow -sequences -time-series -and-prediction?specialization=tensorflow -in-practice

Term Work:
1 Term work should consist of 8 experiments and a Mini Project.
2 The final certification and acceptance of term work ensures satisfactory performance of laboratory
work and minimum passing marks in term work.
3 Total 50Marks (Experiments: 3 0-Marks, Mini P roject -15 Marks, Attendance - Theory & Practical: 05 -
marks)
Oral & Practical exam
1 Based on the entire syllabus of AI ML for Healthcare




















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195

University of Mumbai




Syllabus for

Honours /Minor Degree Program
In
Data Science



FACULTY OF SCIENCE & TECHNOLOGY
(As per AICTE guidelines with effect from the academic year 2022 -2023)




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196
University of Mumbai
Data Science
(With effect from 2022 -23) Year & Sem
Course Code &
Course Title Teaching Scheme
Hrs / Week Examination Scheme and Marks Credit Scheme Theory
Seminar /
Tutorial
Practical
Internal
Assessment
End Sem
Exam
Term Work
Oral
Total
Credits
TE
Sem
V HDSC501:
Mathematics
for Data
Science 04 -- -- 20 80 -- -- 100 04
Total 04 - -- 100 - - - 100 04
Total Credits = 04

TE
Sem
VI HDS C601:
Statistical
Learning for
Data Science 04 -- -- 20 80 -- -- 100 04
Total 04 - - 100 - - - 100 04
Total Credits = 04

BE
Sem
VII HDS C701:
Data Science
for Health and
Social Care 04 -- -- 20 80 -- -- 100 04
HDS SBL701:
Data Science
for Health and
Social Care:
Lab -- -- 04 -- -- 50 50 100 02
Total 04 - 04 100 50 50 200 06
Total Credits = 06

BE
Sem
VIII HDS C801:
Text, Web and
Social Media
Analytics 04 - -- 20 80 -- -- 100 04
Total 04 - - 100 - - 100 04
Total Credits = 04

Total Credits for Semesters V,VI, VII &VIII = 04+04+06+04 = 18


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Data Science : Sem V
Course
Code Course
Name Teaching Scheme (Contact
Hours) Credits Assigned
Theory Practical Tutorial Theory Practical Tutorial Total
HDS C501 Mathematics
for Data
Science 04 -- -- 04 -- -- 04

Course
Code Course
Name Examination Scheme
Theory Marks Exam
Duration Term
Work Practical
and
Oral Total
Internal Assessment End
Sem.
Exam. Test1 Test2 Avg.
HDS C501 Mathematics
for Data
Science 20 20 20 80 03 -- -- 100

Course Prerequisites:
1 Applied Mathematics, Discrete Mathematics
Course Objectives:
1 To build an intuitive understanding of Mathematics and relating it to Data Analytics.
2 To provide a strong foundation for probabilistic and statistical analysis mostly used in varied applications in
Engineering.
3 To focus on exploring the data with the help of graphical representation and drawing conclusions.
4 To explore optimization and dimensionality reduction techniques.
Course Outcomes:
After successful completion of the course, the student will be able t o:
1 Use linear algebra concepts to model, solve, and analyze real -world problems.
2 Apply probability distributions and sampling distributions to various business problems.
3 Select an appropriate graph representation for the given data analysis.
4 Apply exploratory data analysis to some real data sets and provide interpretations via relevant visualization
5 Analyze various optimization techniques for data analysis.
6 Describe Dimension Reduction Algorithms in analytics

Module Topics Hours.
1.0 Linear Algebra 05
1.1 Vectors and Matrices, Solving Linear equations, The four Fundamental Subspaces,
Eigenvalues and Eigen Vectors, The Singular Value Decomposition (SVD).
2.0 Probability and Statistics 09
2.1 Introduction, Random Variables and their probability Distribution, Random Sampling,
Sample Characteristics and their Distributions, Chi -Square, t -, and F -Distributions: Exact
Sampling Distributions, Sampling from a Bivariate Normal Distribution, The Central
Limit Theorem.
3.0 Introductio n to Graphs 10
3.1 Quantitative vs. Qualitative data, Types of Quantitative data: Continuous data, Discrete
data, Types of Qualitative data: Categorical data, Binary data, Ordinary data, Plotting

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198
data using Bar graph, Pie chart, Histogram, Stem and Leaf plot, Dot plot, Scatter plot,
Time -series graph, Exponential graph, Logarithmic graph, Trigonometric graph,
Frequency distribution graph.
4.0 Exploratory Data Analysis 09
4.1 Need of exploratory data analysis, cleaning and preparing data, Feature engi neering,
Missing values, understand dataset through various plots and graphs, draw
conclusions, deciding appropriate machine learning models.
5.0 Optimization Techniques 10
5.1 Types of optimization -Constrained and Unconstrained optimization, Methods of
Optimization -Numerical Optimization, Bracketing Methods -Bisection Method, False
Position Method, Newton’s Method, Steepest Descent Method, Penalty Function
Method.
6.0 Dimension Reduction Algorithms 05
6.1 Introduction to Dimension Reduction Algorithms, Linear Dimensionality Reduction:
Principal component analysis, Factor Analysis, Linear discriminant analysis.
6.2 Non -Linear Dimensionality Reduction: Multidimensional Scaling, Isometric Feature
Mapping. Minimal polynomial
Total 48

Text Books:
1 Linear Algebra for Everyone,
2 Gilbert Strang, Wellesley Cambridge Press.
3 An Introduction to Probability and Statistics, Vijay Rohatgi, Wiley Publication
4 An introduction to Optimization, Second Edition, Wiley -Edwin Chong, Stainslaw Zak.
5 Mathematics for Machine Learning, Marc Peter Deisenroth , A. Aldo Faisal, Cheng Soon Ong, Cambridge
University Press.
6 Exploratory Data Analysis, John Tukey, Princeton University and Bell Laboratories.
References:
1 Introduction to Linear Algebra, Gilbert Strang.
2 Advanced Engineering Mathematics, Erwin Kreyszig
3 Mehryar Mohri, Afshin Rostamizadeh, and Ameet Talwalkar. Foundations of Machine Learning. MIT Press,
2018.
4 Shai Shalev -Shwartz and Shai Ben -David. Understanding Machine Learning: From Theory to Algori thms.
Cambridge University Press, 2014
5 Last updated on Sep 9, 2018.
6 Mathematics and Programming for Machine Learning with R, William B. Claster, CRC Press,2020
Useful Links:
1 https://math.mit.edu/~gs/linearalgebra/
2 https://www.coursera.org/learn/probability -theory -statistics
3 https://nptel.ac.in/courses/111/105/111105090/
4 https://onlinecourses.nptel.ac.in/noc21_ma01/preview
5 https://ocw.mit.edu/courses/mathematics/18 -06-linear -algebra -spring -2010/video -lectures/

Assessment:
Internal Assessment: (20)
1 Assessment cons ists of two class tests of 20 marks each.
2 The first -class test is to be conducted when approx. 40% syllabus is completed and second -class test when
additional 40% syllabus is completed.

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199
3 Duration of each test shall be one hour.
End Semester Theory Examination: (80)
1 Question paper will comprise of total 06 questions, each carrying 20 marks .
2 Question No: 01 will be compulsory and based on the entire syllabus wherein 4 to 5 sub -questions will be
asked.
3 Remaining questions will be mixed in nature and randomly selected from all the modules.
4 Weightage of each module will be proportional to number of respective lecture hours as mentioned in the
syllabus.
5 Total 04 questions need to be solved.


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200
Data Science : Sem VI
Course
Code Course Name Teaching Scheme (Contact
Hours) Credits Assigned
Theory Practical Tutorial Theory Practical Tutorial Total
HDS C601 Statistical Learning
for Data Science 04 -- -- 04 -- -- 04

Course
Code Course Name Examination Scheme
Theory Marks Exam
Duration Term
Work Practical
and Oral Total
Internal Assessment End
Sem.
Exam. Test1 Test2 Avg.
HDS C601 Statistical Learning
for Data Science 20 20 20 80 03 -- -- 100

Course Prerequisites:
1 Engineering Mathematics, Probability and Statistics
Course Objectives:
1 To understand basic statistical foundations for roles of Data Scientist.
2 To develop problem -solving skills.
3 To infer about the population parameters using sample data and perform hypothesis testing.
4 To understand importance and techniques of predicting a relationship between data and determine
the goodness of model fit.
Course Outcomes:
After successful completion of the course, the student will be able to:
1 Develop various visualizations of the data in hand.
2 Analyze a real -world problem and solve it with the knowledge gained from sampling and probability
distributions.
3 Analyze large data sets and perform data analysis to extract meaningful insights.
4 Develo p and test a hypothesis about the population parameters to draw meaningful conclusions.
5 Fit a regression model to data and use it for prediction.

Module
No. Topics Hours.
1.0 Introduction 08
1.1 Data and Statistics : Elements, Variables, and Observations, Scales of
Measurement , Categorical and Quantitative Data , Cross -Sectional and Time
Series Data , Descriptive Statistics , Statistical Inference , Descriptive Statistics:
Tabular and Graphical Summarizing Categorical Data , Summarizing
Quantitative Data , Cross Tabulations and Scatter Diagram.
1.2 Descriptive Statistics: Numerical Measures : Measures of Location , Measures
of Variability , Measures of Distribution Shape, Relative Location, and Detecting
Outliers , Box Plot , Measures of Association Between Two Variables

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201
2.0 Probability 08
2.1 Probability : Experiments, Counting Rules, and Assigning Probabilities , Events
and Their Probabilities , Complement of an Event , Addition Law
Independent Events , Multiplication Law , Baye’s theorem
2.2 Discrete Probability Distributions
Random Variables, Discrete Probability Distributions, Expected Value and
Variance, Binomial Probability Distribution, Poisson Probability Distribution
2.3 Continuous Probability Distributions : Uniform Probability Distribution, Normal
Curve, Standard Normal Probability Distribution, Computing Probabilities for
Any Normal Probability Distribution
3.0 Sampling and Sampling Distributions 05
3.1 Sampling from a Finite Population, Sampling from an Infinite Population, Other
Sampling Methods, Stratified Random Sampling, Cluster Sampling, Systematic
Sampling, Convenience Sampling, Judgment Sampling
3.2 Interval Estimation : Population Mean: Known, Population Mean: Unknown,
Determining the Sample Size, Population Proportion
4.0 Hypothesis Tests 05
4.1 Developing Null and Alternative Hypotheses, Type I and Type II Errors,
Population Mean: Known Population Mean: Unknown Inference About Means
and Proportions with Two Populations -Inferences About Population Variances ,
Inferences About a Population Variance, Inferences About Two Population
Variances
4.2 Tests of Goodness of Fit and Independence , Goodness of Fit Test: A Multinomial
Population, Test of Independence
5.0 Regression 08
5.1 Simple Linear Regression: Simple Linear Regression Model, Regression Model
and Regression Equation, Estimated Regression Equation, Least Squares
Method, Coefficient of Determination, Correlation Coefficient, Model
Assumptions, testing for Significance, Usi ng the Estimated Regression Equation
for Estimation and Prediction Residual Analysis: Validating Model Assumptions,
Residual Analysis: Outliers and Influential Observations
5.2 Multiple Regression: Multiple Regression Model, Least Squares Method,
Multiple Coefficient of Determination, Model Assumptions, Testing for
Significance, Categorical Independent Variables, Residual Analysis
6.0 Time Series Analysis and Forecasting 05
6.1 Time Series Patterns, Forecast Accuracy, Moving Averages and Expon ential
Smoothing, Trend Projection, Seasonality and Trend and Time Series
Decomposition
6.2 Nonparametric Methods
Sign Test, Wilcoxon Signed -Rank Test, Mann -Whitney -Wilcoxon Test, Kruskal -
Wallis Test, Rank Correlation
Total 48

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202
Text Books:
1 https://static1.squarespace.com/static/5ff2adbe3fe4fe33db902812/t/6009dd9fa7bc363aa822d2c7/
1611259312432/ISLR+Seventh+Printing.pdf
2 Data Science from Scratch, FIRST PRINCIPLES WITH PYTHON, O’Reilly, Joel Grus,
3 Data Science from Scratch (oreillystatic.com)
4 Practical Time Series Analysis, Prediction with statistics an d Machine Learning, O’Reilly, Aileen
Nielsen [DOWNLOAD] O'Reilly Practical Time Series Analysis PDF (lunaticai.com)
5 R for data science: Import, Tidy, Transform, Visualize, And Model Data, O’Reilly , Garrett Grolemund,
Hadley Wickham
6 Python for Data Analysis, 2nd Edition, O'Reilly Media, Wes McKinney.
7 https://static1.squarespace.com/static/5ff2adbe3fe4fe33db902812/ t/6009dd9fa7bc363aa822d2c7/
1611259312432/ISLR+Seventh+Printing.pdf
References:
1 Data Science for Dummies Paperback, Wiley Publications, Lillian Pierson
2 Storytelling with Data: A Data Visualization, Guide for Business Professionals, Wiley Publications,
Cole Nussbaumer Knaflic
3 Probability and Statistics for Engineering and the Sciences, Cengage Publications Jay L. Devore.

Assessment:
Internal Assessment: (20)
1 Assessment consists of two class tests of 20 marks each.
2 The first -class test is to be conducted when approx. 40% syllabus is completed and second -class
test when additional 40% syllabus is completed.
3 Duration of each test shall be one hour.
End Semester Theory Examination: (80)
1 Question paper will comprise of total 06 questions, each carrying 20 marks .
2 Question No: 01 will be compulsory and based on the entire syllabus wherein 4 to 5 sub -questions
will be asked.
3 Remaining questions will be mixed in nature and randomly selected from all the modules.
4 Weightage of each module will be proportional to number of respective lecture hours as mentioned
in the syllabus.
5 Total 04 questions need to be solved.









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203
Data Science : Sem VII
Course
Code Course Name Teaching Scheme (Contact
Hours) Credits Assigned
Theory Pract
ical Tutorial Theory Practical Tutorial Total
HDSC701 Data Science for Health
and Social Care 04 -- -- 04 -- -- 04

Course
Code Course Name Examination Scheme
Theory Marks Exam
Duration Term
Work Oral Total
Internal Assessment End Sem.
Exam. Test1 Test2 Avg.
HDS C701 Data Science for
Health and Social Care 20 20 20 80 03 -- -- 100

Course Prerequisites:
Artificial Intelligence, Machine Learning
Course Objectives: The course aims
1 To gain perspective of Data Science for Health and Social Care.
2 To understand different techniques of Biomedical Image Analysis.
3 To learn NLP techniques for processing Clinical text.
4 To understand the role of social media analytics for Healthcare data .
5 To learn advanced analytics techniques for Healthcare Data.
6 To investigate the current scope, potential, limitations, and implications of data science and its application s for
healthcare.
Course Outcomes:
After successful completion of the course, the student will be able to:
1 Identify sources and structure of healthcare data.
2 Apply structured lifecycle approach for handling Healthcare data science projects.
3 Analyze the data, create models, and identify insights from Healthcare data.
4 Apply various data analysis and visualization techniques for Healthcare and social media data.
5 Apply various algorithms and develop models for Healthcare data science projects.
6 To Provide data science solutions for solving problems of Health and Social Care.

Module Topics Hours.
1.0 Data Science for Healthcare 05
1.1 Introduction, Healthcare Data Sources and Data Analytics for Healthcare, Applications
and Practical Systems for Healthcare.
1.2 Electronic Health Records(EHR), Components of EHR, Benefits of EHR, Barriers to
Adopting EHR, Challenges of using EHR data, Phenotyping Algorithms
2.0 Biomedical Image Analysis 06
2.1 Biomedical Imaging Modalities, Object detection ,Image segmentation, Image
Registration, Feature Extraction
2.2 Mining of Sensor data in Healthcare, Challenges in Healthcare Data Analysis
2.3 Biomedical Signal Analysis, Genomic Data Analysis for Personalized Medicine.
3.0 Data Science and Natural Language Processing for Clinical Text 06

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3.1 NLP, Mining information from Clinical Text, Information Extraction, Rule Based
Approaches, Pattern based algorithms, Machine Learning Algorithms.
3.2 Clinical Text Corpora and evaluation metrics, challenges in processing clinical reports,
Clinical Applications.
4.0 Social Media Analytics for Healthcare 06
4.1 Social Media analysis for detection and tracking of Infectious Disease outbreaks.
4.2 Outbreak detection, Social Media Analysis for Public Health Research, Analysis of Social
Media Use in Healthcare.
5.0 Advanced Data Analytics for Healthcare 08
5.1 Review of Clinical Prediction Models, Temporal Data Mining for Healthcare Data
5.2 Visual Analytics for Healthcare Data, Information Retrieval for Healthcare - Data
Publishing Methods in Healthcare.
6.0 Data Science Practical Systems for Healthcare 08
6.1 Data Analytics for Pervasive Health, Fraud Detection in Healthcare
6.2 Data Analytics for Pharmaceutical discoveries, Clinical Decision Support Systems
6.3 Computer -Assisted Medical Image Analysis Systems - Mobile Imaging and Analytics for
Biomedical Data.
Total 48

Textbooks:
1 Chandan K. Reddy and Charu C Aggarwal, “Healthcare data analytics”, Taylor & Francis, 2015.
2 Hui Yang and Eva K. Lee, “Healthcare Analytics: From Data to Knowledge to Healthcare
Improvement, Wiley, 2016.
References:
1 Madsen, L. B. (2015). Data -driven healthcare: how analytics and BI are transforming the industry.
Wiley India Private Limited
2 Strome, T. L., & Liefer, A. (2013). Healthcare analytics for quality and performance improvement.
Hoboken, NJ, USA: Wiley
3 McNeill, D., & Davenport, T. H. (2013). Analytics in Healthcare and the Life Sciences: Strategies,
Implementation Methods, and Best Practices. Pearson Education.
4 Rachel Schutt and Cathy O’Neil, “Doing Data Science”, O’Reilly Media
5 Joel Grus, Data Science from Scratch: First Principles with Python, O'R eilly Media
6 EMC Education Services,”Data Science and Big Data Analytics”,Wiley

Assessment:
Internal Assessment: (20)
1 Assessment consists of two class tests of 20 marks each.
2 The first -class test is to be conducted when approx. 40% syllabus is completed and second -class
test when additional 40% syllabus is completed.
3 Duration of each test shall be one hour.
End Semester Theory Examination: (80)
1 Question paper will comprise of total 06 questions, each carrying 20 marks .
2 Question No: 01 will be compulsory and based on the entire syllabus wherein 4 to 5 sub -
questions will be asked.
3 Remaining questions will be mixed in nature and randomly selected from all the modules.
4 Weightage of each module will be proportional to number of respective lecture hours as
mentioned in the syllabus.
5 Total 04 questions need to be solved.

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205
Data Science : Sem VIII
Course
Code Course Name Teaching Scheme (Contact Hours) Credits Assigned
Theory Practical Tutorial Theory Practical Tutorial Total
HDSC801 Text, Web
and Social
Media
Analytics 04 -- -- 04 -- -- 04

Course
Code Course Name Examination Scheme
Theory Marks Exam
Duration Term
Work Practical
and
Oral Total
Internal Assessment End
Sem.
Exam. Test1 Test2 Avg.
HDS C801 Text, Web and
Social Media
Analytics 20 20 20 80 03 -- -- 100

Course Prerequisites:
Python, Data Mining
Course Objectives: The course aims
1 To have a strong foundation on text, web and social media analytics.
2 To understand the complexities of extracting the text from different data sources and analysing it.
3 To enable students to solve complex real -world problems using sentiment analysis and Recommendation
systems.
Course Outcomes:
After successful complet ion of the course, the student will be able to:
1 Extract Information from the text and perform data pre -processing
2 Apply clustering and classification algorithms on textual data and perform prediction.
3 Apply various web mining techniques to perform mining, searching and spamming of web data.
4 Provide solutions to the emerging problems with social media using behaviour analytics and
Recommendation systems.
5 Apply machine learning techniques to perform Sentiment Analysis on data from social media.

Module
No. Topics Hours.
1.0 Introduction 06
1.1 Introduction to Text Mining: Introduction, Algorithms for Text Mining, Future
Directions
1.2 Information Extraction from Text : Named Entity Recognition, Relation Extraction,
Unsupervised Information Extraction
1.3 Text Representation: tokenization, stemming, stop words, NER, N -gram modelling
2.0 Clustering and Classification 10

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206
2.1 Text Clustering : Feature Selection and Transformation Methods, distance based
Clustering Algorithms, Word and Phrase based Clustering, Probabilistic document
Clustering
2.2 Text Classification : Feature Selection, Decision tree Classifiers, Rule -based Classifiers,
Probabilistic based Classifiers, Proximity based Classifiers.
2.3 Text Modelling: Bayesian Networks, Hidden Markovian Models, Markov random
Fields, Conditional Random Fields
3.0 Web -Mining: 05
3.1 Introduction to Web -Mining: Inverted indices and Compression, Latent Semantic
Indexing, Web Search,
3.2 Meta Search: Using Similarity Scores, Rank Positons
3.3 Web Spamming : Content Spamming, Link Spamming, hiding Techniques, and
Combating Spam
4.0 Web Usage Mining: 05
4.1 Data Collection and Pre -processing, Sources and types of Data, Data Modelling,
Session and Visitor Analysis, Cluster Analysis and Visitor segmentation, Association
and Correlation Analysis, Analysis of Sequential and Navigational Patterns,
Classification and Prediction based on Web User Transactions.
5.0 Social Media Mining : 05
5.1 Introduction, Challenges, Types of social Network Graphs
5.2 Mining Social Media: Influence and Homophily, Behaviour Analytics,
Recommendation in Social Media: Challenges, Classical recommendation Algorithms,
Recommendation using Social Context, Evalua ting recommendations.
6.0 Opinion Mining and Sentiment Analysis : 08
6.1 The problem of opinion mining,
6.2 Document Sentiment Classification : Supervised, Unsupervised
6.3 Opinion Lexicon Expansion: Dictionary based, Corpus based
6.4 Opinion Spam Detection : Supervised Learning, Abnormal Behaviours, Group Spam
Detection.

Total 48

Textbooks:
1 Daniel Jurafsky and James H. Martin, “Speech and Language Processing,” 3rd edition, 2020
2 Charu. C. Aggarwal, Cheng Xiang Zhai, Mining Text Data, Springer Science and Business Media, 2012.
3 BingLiu, “Web Data Mining -Exploring Hyperlinks, Contents, and Usage Data”, Springer, Second Edition, 2011.

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207
4 Reza Zafarani, Mohammad Ali Abbasiand Huan Liu, “Social Media Mining - An Introduction”, Cambridge
University Press, 2014

Assessment:
Internal Assessment: (20)
1 Assessment consists of two class tests of 20 marks each.
2 The first -class test is to be conducted when approx. 40% syllabus is completed and second -class
test when additional 40% syllabus is completed.
3 Duration of each test shall be one hour.
End Semester Theory Examination: (80)
1 Question paper will comprise of total 06 questions, each carrying 20 marks .
2 Question No: 01 will be compulsory and based on the entire syllabus wherein 4 to 5 sub -questions
will be asked.
3 Remaining questions will be mixed in nature and randomly selec ted from all the modules.
4 Weightage of each module will be proportional to number of respective lecture hours as mentioned
in the syllabus.
5 Total 04 questions need to be solved.


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208
Data Science : Sem VII
Course Code Course Name Teaching Scheme (Contact
Hours) Credits Assigned
Theory Practical Tutorial Theory Practical Tutorial Total
HDS SBL701 Data Science for
Health and Social
Care: Lab -- 04 -- -- 02 -- 02

Course Code Course Name Examination Scheme
Theory Marks Exam
Duration Term
Work Oral Total
Internal Assessment End
Sem.
Exam. Test1 Test2 Avg.
HDSSBL701 Data Science for
Health and Social
Care: Lab 50 50 100

Course Prerequisites:
Python
Course Outcomes:
After successful completion of the course, the student will be able to:
1 Students will be able to, Identify sources of data, suggest methods for collecting, sharing and analyzing
Healthcare data.
2 Students will be able to Clean, integrate and transform healthcare data.
3 Students will be able to apply various data analysis and visualization techniques
on healthcare data.
4 Students will be able to apply various algorithms and develop models for healthcare data Analytics.
5 Students will be able to implement data scie nce solutions for solving healthcare problems.

Suggested Experiments:
Sr.
No. Name of the Experiment
Introduction
1 Clean, Integrate and Transform Electronic Healthcare Records.
2 Apply various data analysis and visualization techniques on EHR.
3 Bio Medical Image Preprocessing, Segmentation.
4 Bio Medical Image Analytics.
5 Text Analytics for Clinical Text Data.
6 Diagnose disease risk from Patient data.
7 Social Media Analytics for outbreak prediction/ Drug review analytics.
8 Visual Analytics for Healthcare Data.

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9 Implement an innovative Data Science application based on Healthcare Data.
10 Documentation and Presentation of Mini Project.

Useful Links:
1 http://openclassroom.stanford.edu/MainFolder/CoursePage.php?course=MachineLearning
2 http: //www.cse.wustl.edu/~kilian/cse517a2010/
3 https://datarade.ai/data -categories/electronic -health -record -ehr-data
4 https://www.cms.gov/Medicare/E -Health/EHealthRecords
5 https://onlinecourses.nptel.ac.in/noc20_ee40

Term Work:
1 Term work should consist of 8 experiments and a Mini Project.
2 The final certification and acceptance of term work ensures satisfactory performance of laboratory
work and minimum passing marks in term work.
3 Total 50Marks (Experiments: 3 0-Marks, Mini P roject -15 Marks, Attendance - Theory & Practical: 05 -
marks)
Oral & Practical exam
1 Based on the entire syllabus of Data Science for Health and Social Care



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University of Mumbai




Syllabus

Honours /Minor Degree Program
In
Internet of Things



FACULTY OF SCIENCE & TECHNOLOGY
(As per AICTE guidelines with effect from the academic year 2022 -2023

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University of Mumbai
Internet of Things
(With effect from 2022 -23)
Year &
Sem
Course Code and
Course Title Teaching
Scheme Hours / Week Examination Scheme and Marks Credit
Scheme
Theory Seminar/
Tutorial Pract Internal
Assess
ment End
Sem
Exam Term
Work Oral Total Credits

TE
Sem
V HIoTC501:
IoT Sensor
Technologies 04 -- -- 20 80 -- -- 100 04
Total 04 - -- 100 - - 100 04
Total Credits = 04

TE
Sem.
VI HIoTC601:
IoT System Design 04 -- -- 20 80 -- -- 100 04
Total 04 - - 100 - - 100 04
Total Credits = 04


BE
Sem.
VII HIoTC701:
Dynamic Paradigm
in IoT 04 -- -- 20 80 -- -- 100 04
HIoTSBL7 01:
Interfacing &
Programming with
IoTLab (SBL) -- -- 04 -- -- 50 50 100 02
Total 04 - 04 100 50 50 200 06
Total Credits = 06

BE
Sem.
VIII
HIoTC801:
Industrial IoT 04 - -- 20 80 -- -- 100 04
Total 04 - - 100 - - 100 04
Total Credits = 04

Total Credits for Semesters V,VI, VII &VIII = 04+04+06+04=18

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Course
Code Course Title Examination Scheme
Theory Marks Term
Work Practical Oral Total Internal assessment End Sem.
Exam Test1 Test 2 Avg
HIoTC501 IoT Sensor
Technologies 20 20 20 80 -- -- -- 100

Course Objectives:
Sr. No. Course Objectives
The course aims:
1 To provide in depth knowledge about the sensing mechanism.
2 To make students understand about the use of sensors in design of IoT based systems.
3 To familiarize students various types of sensors used to measure the physical quantities.
4 To develop reasonable level of competence in the design, construction and development of sensor
suitable to the system requirements.
5 To Introduce students the current state of the art in sensor tech nology.
6 To familiarize students with electronics used to interface with sensors.

Course Outcomes:
Sr. No. Course Outcomes Cognitive levels of
attainment as per
Bloom’s Taxonomy
On successful completion, of course, learner/student will be able to:
1 Understand the sensing mechanism and structural details of sensors. L1, L2
2 Explain principles and working of the sensors. L1,L2
3 Evaluate the performance of various types of sensors. L5
4 Select the sensor suitable to system requirements. L5
5 Interface the sensors with microcontrollers and Arduino L6
6 Understand the current state of the art in sensor technology. L2

DETAILED SYLLABUS:
Sr.
No. Module Detailed Content Hours CO Mapping
0 Prerequisite 1. Basics of Electrical and Electronics Engineering
2. Applied Mechanics
3. Applied Physics, Applied Chemistry 2 CO 1, CO2, CO3,
CO4, CO5 Internet of Things: Sem V

Course Code Course Title Theory Practical Tutorial Theory Practical/
Oral Tutorial Total
HIoTC501 IoT Sensor
Technologies 04 -- -- 04 -- -- 04

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I Sensor
Fundamental
s and
Properties Sensor Fundamentals and Properties: Introduction to IoT,
Need for sensors in IoT, Data Acquisition – sensor
characteristics – electric charges, fields, potentials –
capacitance – magnetism – inductance – resistance –
piezoelectric – pyroelectric – Hall effect thermoelectric
effects – sound waves – heat transfer – light – dynamic
models of sensors. Need of actuat ors, all types of actuators
and their working. Identification of sensor and actuator for
real-time application
Self-learning Topics: IoT Systems, Transfer function and
modelling of sensors 8 CO1, CO2
II Optical,
radiation and
Displacement
sensors Optical, radiation and Displacement sensors Photosensors:
Photodiode, phototransistor and photo resistor, imaging
sensors, UV detectors, Basic Characteristics of radiation
sensors, Thermal infrared sensors, X -ray and Nuclear
Radiation Sensors, Fibre Optic Sensors, Capacitive and
Inductive Displacement Sensor, Electromagnetism and
Inductance, Magnetic Field Sensors
Self-learning Topics: Optical sources and detectors, Sensors
based on polymer optical fibers, Micro -structured and solid
fibers 8 CO1, CO2, CO3,
CO4
III Presence,
force,
Pressure,
Flow Sensors
Presence, force, Pressure, Flow Sensors
Potentiometric Sensors, Piezoresistive Sensors, Capacitive
Sensors for presence, Inductive and Magnetic Sensors, Strain
gages, Pressure sensitive films, piezoelectric force sensor,
Piezoelectric Cables, Concept of Pressure, Mercury Pressure
Sensor, Bellows, Membranes, and Thin Plates, Piezo resistive
Sensors, Capacitive Sensors, VRP Sensors, Optoelectronic
Pressure Sensors, Indirect Pressure Sensor, Vacuu m Sensors,
Basics of Flow Dynamics, Pressure Gradient Technique,
Thermal Transport Sensors, Ultrasonic Sensors, Level Sensors
Self-learning Topics: Vibration energy harvesting with
Piezoelectric, MEMS systems. Develop a sensor system for
force measurement using piezoelectric transducer. Develop
Resistance Temperature Detector 9 CO1, CO2, CO3,
CO4
IV Humidity,
Moisture
Chemical and
Biological
Sensors
Humidity, Moisture Chemical and Biological Sensors
Microphones: Characteristics, Resistive, condenser, Electret,
Optical, Pizoelectric, Dynamic,
Concept of humidity, Capacitive Humidity Sensors, Resistive
Humidity Sensors, Thermal Conductivity Sensors, Optical
Hygrometers, Oscillating Hygrometer, Soil Moi sture
Chemical Sensor Characteristics, Electrical and
Electrochemical Sensors, Photoionization Detectors, Physical 8 CO1, CO2, CO3,
CO4, CO5

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Transducers, Spectrometers, Thermal Sensors, Optical
Transducers, Multi -sensor Arrays
Artificial Microsystems for Sensing Airflow, Temperatur e, and
Humidity by Combining MEMS and CMOS Technologies
Self-learning Topics: Biosensors for biomedical applications
V Interface
Electronic
Circuits
Interface Electronic Circuits
Introduction, Signal Conditioners, Sensor Connections,
Excitation Circuits, Analog to Digital Converters, Integrated
Interfaces, Data Transmission, Noise in Sensors and Circuits,
Batteries for Low -Power Sensors, Types of Single board
computers, various sensor interfacing with Arduino,
Embedded C P rogramming. data communication protocol
interfacing, study the properties of LDR, Build a simple LED
light intensity controller, Linux on Raspberry Pi, Interfaces, and
Programming.
Self-learning Topics: Python Programming to interface
sensors 8 CO1, CO2, C O5
VI Current
Trends in
sensors and
Technology
Current Trends in sensors and Technology
Smart Sensors: Introduction, Primary sensors, Excitation,
Amplification, Filters, Converters, Compensation, Information
Coding/Processing, Data Communication, Standards for Smart
Sensor Interface, The Automation
Sensor Technologies: Introduction, Film Sensors, Thick Film
Sensors, Thin Film Sensors, Semiconductor IC Technology —
Standard Methods, Microelectromechanical Systems (MEMS),
Nano -sensors
Sensor Applicatio ns: Onboard Automobile sensors, Home
appliances sensors, Aerospace Sensors, Sensors for
Environmental Monitoring
Self-learning Topics: Energy Harvesting, Self -powered
Wireless Sensing in ground, Ground penetrating sensors 9 CO1, CO2, CO3,
CO4, CO5, CO6

Text Books:
1. Jacob Fraden, “Hand Book of Modern Sensors: physics, Designs and Applications”, 2015, 3rd edition,
Springer, New York.
2. Jon. S. Wilson, “Sensor Technology Hand Book”, 2011, 1st edition, Elsevier, Netherland
3. D. Patranabis – Sensor and Transducers (2e) Prentice Hall, New Delhi, 2003
4. Vijay Madisetti and Arshdeep Bahga, “Internet of Things (A Hands -on-Approach)”,1st Edition, VPT, 2014

References:
1. Edited by Qusay F Hasan, Atta ur rehman Khan, Sajid A madani, “Internet of Things Challenges, Advances,
and Application”, CRC Press
2. Triethy HL - Transducers in Electronic and Mechanical Designs, Mercel Dekker, 2003
3. Gerd Keiser,”Optical Fiber Communications”, 2017, 5th edition, McGraw -Hill Science, Delhi.

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4. John G Webster, Halit Eren, “Measurement, Instrumenta tion and sensor Handbook”, 2014, 2nd edition, CRC
Press, Taylor and Fransis Group, New York.
5. Adrian McEwen, “Designing the Internet of Things”, Wiley Publishers, 2013, ISBN: 978 -1-118-43062 -0
6. Nathan Ida, “Sensors, Actuators and their Interfaces: A Multidis ciplinary Introduction”, Second Edition, IET
Control, Robotics and Sensors Series 127, 2020
Online References:
Sr. No. Website Name
3. https://nptel.ac.in/courses/108/108/108108123/
4. https://nptel.ac.in/courses/108/108/108108098/
3. https://nptel.ac.in/noc/courses/noc19/SEM2/noc19 -ee41/
4. https://nptel.ac.in/courses/108/106/108106165/

Assessment:
Internal Assessment (IA) for 20 marks:
 IA will consist of Two Compulsory Internal Assessment Tests. Approximately 40% to 50% of syllabus
content must be covered in First IA Test and remaining 40% to 50% of syllabus content must be
covered in Second IA Test
 Question paper format
 Question Paper will comprise of a total of six questions each carrying 20 marks Q.1 will be
compulsory and should cover ma ximum contents of the syllabus
 Remaining questions will be mixed in nature (part (a) and part (b) of each question must be from
different modules. For example, if Q.2 has part (a) from Module 3 then part (b) must be from any
other Module randomly selected from all the modules)
 A total of four questions need to be answered











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Internet of Things: Sem V I

Course Code Course Title Theory Practical Tutorial Theory Practical/
Oral Tutorial Total
HIoTC601 IoT System
Design 04 -- -- 04 -- -- 04

Course
Code Course Title Examination Scheme
Theory Marks
Term
Work Practical Oral Total Internal assessment End
Sem.
Exam Test1 Test 2 Avg.
HIoTC601
IoT System
Design 20 20 20 80 -- -- -- 100

Course Objectives :
Sr. No. Course Objectives
The course aims:
1 To learn basic principles, concepts, and technologies for internet of things.
2 To understand various architectures of IOT.
3 To train the students to build IoT systems using sensors, single board computers and open source IoT
platform for given application.
4 To learn and implement various networking and communication protocols.
5 To design and analyze IoT for given applications.
6 To Evaluate performance of given IoT system.

Course Outcomes :
Sr. No. Course Outcomes Cognitive levels of
attainment as per
Bloom’s Taxonomy
On successful completion, of course, learner/student will be able to:
1 Able to explain principles, concepts, and technologies for internet of things. L1, L2
2 Able to identify various building blocks of IoT system L1,L2
3 Able to analyze and evaluate various networking and communication protocols used
in IoT system L3,L4
4 Able to select appropriate interface for given application L3
5 Able to design and analyze IoT system for given application L4,L5
6 Able to evaluate performance of given IOT System L5

DETAILED SYLLABUS :
Sr. No. Module Detailed Content Hours CO
Mapping
0 Prerequisite Comment (Prerequisite syllabus should not be considered for paper
setting) Basics of Embedded System, IoT Sensors, Digital design 2 --

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I Overview of
IoT System What is IoT System? IoT Impact, Current Trends in IoT , IoT Challenges,
Comparing IoT Architectures, A Simplified IoT Architecture, The Core
IoT Functional Stack How are IoT Systems different from traditional
system Values and Uses of IoT Functional View and Infrastructure
view of IoT Systems
Self-learning Topics: Understanding the Issues and Challenges of a
More Connected World 6 CO1, CO2
II Networking
Protocols OSI Model for the IoT/M2M System Lightweight M2M
Communication Protocols, Internet based Communications, IP
addressing in IoT, Network Model, TCP & UDP, Client -Server
architecture
Self-learning Topics: How to choose correct protocol for our network. 8 CO3
III Communicat
ion Protocols IoT Edge to Cloud protocols: HTTP, REST APIs, WebSocket, MQTT,
COAP, Comparison of Protocols.M2M Communication Protocols ,
Bluetooth BR/EDR and Bluetooth low energy . RFID IoT System , RFID
IoT Network Architecture, ZigBee IP/Zig Bee SE2.0, Wifi(WLAN),
Message Communication protocols for connected devices Data
exchange formats: JSON & XML, Node -Red, Flow control using Node -
Red, learning the different nodes of Node -RED for implementing the
Communication Protocols
Self-learning Topic s: Types of Communication 10 CO3,CO4
IV Sensor
Interfaces Digital Interfaces : UART, Serial Peripheral Interface (SPI), I2C (Inter -
Integrated Circuit), Controller Area Network (CAN), Middleware
Technologies, Communication Protocols and Models. Practical
Components Programming with interface in Arduino, MBed and
Raspberry Pi
Self-learning Topics: SMART SENSOR INTERFACES 10 CO4
V Design
principles for
prototyping Design solution for ubiquitionos and utility, Interface design for user
experience, Designing for data privacy, Interfacing – Apps & Webs,
Designing for Affordability, Cost v/s Ease of Prototyping, Prototypes
and Production, Selection of embedded platform, Prototype and
Mass personalizat ion, Open Source v/s Closed Source ,Amplification
and Signal Conditioning - Integrated Signal Conditioning - Digital
conversion - MCU Control MCUs for Sensor Interface - Techniques and
System Considerations - Sensor Integration
Self-learning Topics: Principles for Prototyping and moving towards
Product Development 8 CO5
VI IoT, case
studies Arduino Programming for Ethernet and Wifi connectivity , Networking
and Data logging with Raspberry Pi Applications -Agriculture, Medical,
Fire detection, Air pollution prediction, Earthquake early detection;
for smart environmental care, smart traveling, Home Automation
Self-learning Topics : IoT enabled Business solution in Supply Chain 8 CO6

Text Books :
1. S. Misra, A. Mukherjee, and A. Roy, 2020. Introduction to IoT. Cambridge University Press.
2. Adrian McEwen and Hakim Cassimally, ―Designing the Internet of Things‖, John Wiley and Sons Ltd, UK, 2014.

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3. Milan Milenkovic, Internet of Things: Concepts and System Design, Springer International Publishing,May
2020cation
4. Dr.Raj Kamal,Internet of Things(IoT) , Architecture and Design Principles.McGraw Hill Education.

References:
1. David Hanes, Gonzalo Salgueiro, Patrick Grossetete, Robert Barton, Jerome Henry,"IoT Fundamentals:
Networking Technologies, Protoco ls, and Use Cases for the Internet of Things
2. N. Ida, Sensors, Actuators and Their Interfaces, Scitech Publishers, 2014.
3. Editors OvidiuVermesan Peter Friess,'Internet of Things – From Research and Innovation to Market
4. Dr. Guillaume Girardin , Antoine Bonnab el, Dr. Eric Mounier, 'Technologies Sensors for the Internet of Things
Businesses & Market Trends 2014 -2024',Yole Development Copyrights ,2014
Assessment:
Internal Assessment (IA) for 20 marks:
 IA will consist of Two Compulsory Internal Assessment Tests. Approximately 40% to 50% of syllabus
content must be covered in First IA Test and remaining 40% to 50% of syllabus content must be
covered in Second IA Test
 Question paper format
 Question Paper will comprise of a total of six questions each carrying 20 ma rks Q.1 will be
compulsory and should cover maximum contents of the syllabus
 Remaining questions will be mixed in nature (part (a) and part (b) of each question must be from
different modules. For example, if Q.2 has part (a) from Module 3 then part (b) mu st be from any
other Module randomly selected from all the modules)
 A total of four questions need to be answered










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Internet of Things: Sem V II

Course
Code Course Title Theory Practical Tutorial Theory Practical/
Oral Tutorial Total
HIoTC701 Dynamic Paradigm
in IoT 04 -- -- 04 -- -- 04

Course
Code Course Title Examination Scheme
Theory Marks
Term
Work Practical Oral Total Internal assessment End Sem.
Exam Test1 Test 2 Avg. of 2
Tests
HIoTC701 Dynamic
Paradigm in IoT 20 20 20 80 -- -- -- 100

Course Objectives:
Sr. No. Course Objectives
The course aims:
1 To explore the role of the cloud in Internet of Things deployment.
2 To introduce the usage of different machine learning algorithms on IoT Data.
3 To explore data analytics and data visualization on IoT Data.
4 To explore the role of Fog computing in Internet of Things.
5 To explore design issues and working principles of various security measures and various standards for
secure communication in IoT.
6 To develop the ability to integrate IoT with Dev -ops.

Course Outcomes:
Sr. No. Course Outcomes Cognitive levels of
attainment as per
Bloom’s Taxonomy
On successful completion, of course, learner/student will be able to:
1 Identify the need for the cloud in IoT deployment and describe different Cloud
provider’s architecture. L1,L2
2 Use and correlate machine learning techniques on IoT Data. L3,L4
3 Apply IoT analytics and data visualization. L3
4 Recognize the use of Fog Computing in the Internet of things. L1,L2
5 Explain the need of security measures in the Internet of Things. L4
6 Apply the knowledge of Dev -ops in IoT applications. L3

DETAILED SYLLABUS:
Sr. No. Module Detailed Content Hours CO
Mapping
0 Prerequisite Basics of Cloud Computing, Basics of Machine learning and
primitives of cryptography 2 --

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I IoT and
CLOUD Cloud Computing Concept, Grid/SOA and Cloud Computing, Cloud
Middleware
NIST’s SPI Architecture and Cloud Standards, The Cloud of Things --
The Internet of Things and Cloud Computing
The Cloud of Things Architecture -- Four Deployment Models,
Vertical Applications, Fifteen Essential Features, Four
Technological Pillars, Three Layers of IoT Systems, Foundational
Technological Enabler Cloud Providers and System s -- Microsoft
Azure IoT, Amazon Web Services, Google’s cloud IoT s.

Self-learning Module: IBM Watson Cloud 10 CO1
II IoT and
Machine
Learning Advantages of IoT and Machine Learning Integration,
Implementation of Supervised Algorithm - Regression (Linear and
Logistic), SVM for IoT -Neural Network on case study: Agriculture and
IoT, Smart Home etc.

Self-Learning Module: Regression, SVM 6 CO2
III IoT and Data
Analytics Defining IoT Analytics, IoT Analytics challenges, IoT analytics for the
cloud -Microsoft Azure overview – Strategies to organize Data for IoT
Analytics, Linked Analytics Data Sets, Managing Data lakes, The data
retention strategy. Communicating with Others - Visualization and
Dash boarding - Designing visual analysis for IoT d ata, creating a
dashboard –creating and visualizing alerts.
Self-learning Topics: Study real time case study on IoT Analytics. 8 CO3
IV IoT and Fog
Computing Fog computing Basics, The Hadoop philosophy for Fog computing,
Fog Computing versus Edge Computing versus cloud computing,
Open Fog Reference Architecture Application services -- Application
support, Node management and software backplane, Hardware
virtualization, Open Fog node security, Network Accelerators
Compute, Storage Hardware platform i nfrastructure, Protocol
abstraction, Sensors, actuators, and control systems, Fog Topology.

Self-learning Module: Amazon Green grass and Lambda
(implementation) 8 CO4
V IoT and it’s
Security Cyber security vernacular Attack and threat terms, Defense terms,
Anatomy of IoT cyber attacks – Mirai, Stuxnet, Chain Reaction,
Physical and hardware security, Root of Trust, Key management and
trusted platform modules, Processor and memory space, Storage
security, Network stack – Transport Layer Security, Softw are defined
perimeter, Software -Defined Perimeter architecture,

Self-learning Module: OWASP -Existing Security attacks and its
prevention methods. 8 CO5
VI IoT and
Devops Introduction to DevOps , DevOps application - business scenarios ,
DevOps process -- Source Code Management (SCM) , Code review ,
Configuration Management , Build management , Artifacts repository
management , Release management , Test automation , Continuous
integration , Continuous delivery , Continuous deployment ,
Infrastructure as Code , Routine automation , Key application
performance monitoring/indicators . DevOps frameworks --DevOps
maturity life cycle , DevOps maturity map , DevOps progression 10 CO6

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framework/readiness model , DevOps maturity checklists , Agile
framework for DevOps process projects , Agile ways of development
Tool for IoT —Chef and Puppet, Setting up Chef and Puppet, Multi -tier
Application Deployment, NETCONF -YANG Case Studies - Steps for IoT
device management with NETCONF -YANG, Managing Smart irrigation
IoT system with NETCONF -YANG, Managing Home Intrusion
Detection IoT system with NETCONF -YANG
Self-learning Topics: Compare different tool of IoT.

Text Books:
1. The Internet of Things in the Cloud A Middleware Perspective, Honbo Zhou – CRC Publication.
2. Analytics for the Internet of Things (IoT), Andrew Minteer , Packt Publication 2017
3. Internet of Things - Hands on Approach, Arshdeep Bagha, Vijay Medisetti, Published by Arshdeep Bagha and Vijay
Medisetti,2014.
4. Hands -on DevOps, Sricharan Vadapalli, Packt Publication, 2017
5. Internet of things For Architects, Perry Lea Packt Publication,2018

References:
1. Enterprise Cloud Computing, Gautam Shroff, Cambridge,2010
2. Mastering Cloud Computing -Foundations and Applications Programming, Raj Kumar Buyya, Christian Vecchiola,
S. Thamarai Selvi, MK Publication, 2013.
3. Machine Learning in Action‖, Peter Harrington, DreamTech Press
4. Introduction to Machine Learning‖, Ethem Alpaydın, MIT Press
5. Learning AWS IoT - Effectively Manage Connected Devices on the AWS Cloud Using Se rvices Such as AWS
Greengrass, AWS Button, Predictive Analytics and Machine Learning, Agus Kurniawan , Packt Publication,2018
6. Practical Dev -Ops, Joakim Verona, Packt Publication, 2016

Online References:
Sr. No. Website Name
1. https://hub.packtpub.com/25 -datasets -deep -learning -iot/
2. https://data.world/datasets/iot
3. https://dashboard.healthit.gov/datadashboard/data.php
4. https://www.data.gov/
5. https://dev.socrata. com/data/
6. https://www.kaggle.com/
Assessment:
Internal Assessment (IA) for 20 marks:
 IA will consist of Two Compulsory Internal Assessment Tests. Approximately 40% to 50% of syllabus
content must be covered in First IA Test and remaining 40% to 50% of syllabus content must be
covered in Second IA Test
 Question paper format
 Question Paper will comprise of a total of six questions each carrying 20 marks Q.1 will be
compulsory and should cover maximum contents of t he syllabus
 Remaining questions will be mixed in nature (part (a) and part (b) of each question must be from
different modules. For example, if Q.2 has part (a) from Module 3 then part (b) must be from any
other Module randomly selected from all the module s)
 A total of four questions need to be answered

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Internet of Things: Sem V II
Teaching Scheme
(Contact Hours)
Credits Assigned
Course Code Course Title Theory Practical Tutorial Theory Practical Tutorial Total
HIoTSBL7 01 Interfacing &
Programming
with IoT Lab (SBL) -- 4 -- -- 2 -- 02

Course Code Course Title Examination Scheme
Theory Marks
Term
Work Oral Total Internal assessment End
Sem.
Exam Test1 Test 2 Avg. of 2 Tests
HIoTSBL7 01 Interfacing &
Programming with
IoT Lab (SBL) -- -- -- -- 50 50 100

Lab Objectives:
Sr. No. Lab Objectives
The Lab aims:
1 To Understand the definition and significance of the Internet of Things.
2 To Discuss the architecture, operation, and business benefits of an IoT solution.
3 To Examine the potential business opportunities that IoT can uncover.
4 To Explore the relationship between IoT, cloud computing, and DevOps.
5 To Identify how IoT differs from traditional data collection systems.
6 To Explore the interconnection and integration of th e physical world and able to design & develop IOT
Devices.

Lab Outcomes:
Sr. No. Lab Outcomes Cognitive levels of
attainment as per
Bloom’s Taxonomy
On successful completion, of lab, learner/student will be able to:
1 Adapt different techniques for data acquisition using various IoT sensors for
different applications. L6
2 Demonstrate the working of actuators based on the collected data. L2
3 Use different IoT simulators and correlate working of IoT protocols. L3
4 Adapt different techniques for I ntegrating IoT services to other third -party Clouds. L6
5 Execute DevOps methodologies for continuous integration and continuous
deployment of IoT application. L3
6 Implement IoT protocols like MQTT for communication to realize the revolution of
internet in mobile devices, cloud and sensor networks. L3

Prerequisite:

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IoT introduction course: Basics of IoT, Introduction to Embedded systems
Hardware & Software Requirements:

Hardware Requirements Software Requirements Other Requirements
PC With Following Configuration
1. Intel PIV Processor
2. 4 GB RAM
3. 500 GB Harddisk
4. Network interface card
5. Sensors
6. IoT Kit (Arduino/ARM/Raspberry Pi) 1. Windows or Linux Desktop OS
2. DeVops
3.Python
4. IoT Simulator/Emulator (open
source) 1. Internet Connection for
installing additional packages if
required

This lab will describe the market around the Internet of Things (IoT), the technology used to build these kinds of
devices, how they communicate, how they store data, and the kinds of distributed systems needed to support
them. Divided into four main modules, we will learn by doing. We will start with simple examples and integrate
the techniques we learn into a class project in which we design and build an actual IoT system. The client will run
in an emulated ARM environment, communicating using common IoT protocols with a cloud enabled backend
system with DevOps integration.
Suggested List of Experiments
Sr. No. Detailed Content Hours LO
Mapping
1 To study and implement interfacing of different IoT sensors wi th Raspberry
Pi/Arduino/ModeMCU 4 LO1
2 To study and implement interfacing of actuators based on the data
collected using IoT sensors. (like led switch ON/OFF, stepper word) 4 LO2
3 To study and demonstrate Contiki OS for RPL (like Create 2 border router
and 10 REST clients, Access border router from other network (Simulator)) 4 LO3
4 To study and demonstrate use of IoT simulators (like Beviswise) on any real
time device (LED/stepper motor) 4 LO3
5 Select any one case study (in a group of 2-3) and perform the experiments
5 to 10. The sample case studies can be as follows:
1. Smart home automation system
2. Healthcare management system
3. Smart traffic management system & so on…
Write a program on Raspberry Pi to push and retrieve the data from cloud
like thingspeak, thingsboard, AWS, Azure etc. 8 LO4
6 To install MySQL database on Raspberry Pi and perform basic SQL queries
for analysis data collected. 6 LO4
7 To study and implement IoT Data processing using Pandas.
4 LO4

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8 To study and implement Continuous Integration using Jenkins on IoT data
and also perform interfacing of Raspberry Pi into Jenkins. 6 LO6
9 To study and implement Continuous Deployment (Infrastructure as a code)
for IoT using Ansible. 6 LO6
10 To study MQTT Mosquitto server and write a program on
Arduino/Raspberry Pi to publish sensor data to MQTT broker. 6 LO5

Books / References:
1. Jake VanderPlas,“ Python Data Science Handbook”, O’Reilly publication,2016
2. Joakim Verona,” Practical DevOps”, PACKT publishing, 2016
3.Honbo Zhou,” The internet of things in the cloud”, CRC press, Taylor and Francis group, 2012
4. Perry Lea,” Internet of thi ngs for architects”, PACKT publishing, 2018

Online Resources:
Sr. No. Website Name
1. https://spoken -tutorial.org/watch/Arduino/Introduction+to+Arduino/English/
2. https://pythonprogramming.net/introduction -raspberry -pi-tutorials/
3. https://iotbytes.wordpress.com/basic -iot-actuators/
4. http://www.contiki -os.org/
5. https://www.bevywise.com/iot -simulator/
6. https://mqtt.org/

Term Work:
The Term work shall consist of at least 10 practical based on the above list. The term work Journal must include at
least 2 assignments. The assignments should be based on real world applications which cover concepts from all above
list.

Term Work Marks: 50 Marks (Total marks) = 40 Marks (Experiment) + 5 Marks (Assignments/tutorial/write up) + 5
Marks (Attendance)

Oral Exam: An Oral exam will be held based on the above syllabus.







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225
Internet of Things: Sem V III
Course Code Course Title Theory Practical Tutorial Theory Practical/Oral Tutorial Total
HIoTC801 Industrial IoT 04 -- -- 04 -- -- 04

Course
Code
Course Title Examination Scheme
Theory Marks
Term
Work Practical Oral Total Internal assessment End
Sem.
Exam Test1 Test 2 Avg. of 2
Tests
HIoTC801 Industrial IoT 20 20 20 80 -- -- -- 100
Course Objectives:
Sr. No. Course Objectives
The course aims:
1 To learn the concepts of Industry 4.0 and IIOT.
2 To learn reference Architecture of IIOT.
3 To learn Industrial Data Transmission and Industrial Data Acquisition.
4 To learn middleware and WAN technologies.
5 To learn IIOT Block chain and Security.
6 To learn different applications and securities in IIOT.

Course Outcomes:
Sr. No. Course Outcomes Cognitive levels of
attainment as per
Bloom’s Taxonomy
On successful completion, of course, learner/student will be able to:
1 Understand the concepts of Industry 4.0 and IIOT. L1,L2
2 Understand reference Architecture of IIOT. L1,L2
3 Understand Industrial Data Transmission and Industrial Data Acquisition. L1,L2
4 Understand middleware and WAN technologies in IIOT. L1,L2
5 Understand the concepts of Blockchain and Security in IIOT. L1,L2
6 Apply security in IIOT applications. L3

DETAILED SYLLABUS:
Sr. No. Module Detailed Content Hours CO
Mapping
0 Prerequisite IOT Concepts, Sensor Technology, IOT Stack and Protocols, Design
IoT systems, WSN etc. 02 --

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226
I Introduction Overview of Industry 4.0 and Industrial Internet of Things, Industry
4.0: Industrial Revolution: Phases of Development, Evolution of
Industry 4.0, Environment impacts of industrial revolution,
Industrial Internet, Basics of CPS, CPS and IIOT, Design
requirements of Industry 4.0, Drivers of Industry 4.0, Sustainability
Assessment of Industries, Smart Business Perspective, Cyber
security, Impacts of Industry 4.0, Industrial Internet of Things:
Basics, IIOT and Industry 4.0, Industrial Internet Systems, Industrial
Sensing, Industrial Processes, IIOT Challenges – Identifying Things
within the internet, Discovering Things and the Data they possess,
Managing massive amount of data, Navigating Connectivity
Outages, IIOT Edge - Leveraging the Power of Cloud Computing,
Communicating with Devices on the Edge, Determining a
Request/Response Model
Self-learning Topics: Study real time IIoT challenges in industry. 06 CO1

II IIOT
Reference
Architecture The IIC Industrial Internet Reference Architecture - Industrial
Internet Architecture Framework (IIAF),Industrial Internet
Viewpoints -Functional, Operational, Information Application and
Business Domain of IIAF.
The Three -Tier Topology, Key Functional Characteristics of
Connectivity.
Software Architectural Style for the Industrial Internet of Things -
Software Architecture Practice, Adv anced Architectural Styles,
Systems of Systems, Challenges of Software Engineering in IIoT,
Principles for Software Architecture design in IIoT, The Principled
Decomposition, The Architectural Style

Self-learning Topics: Study IIoT Architecture. 08 CO2

III Industrial
Data
Transmission
and Industrial
Data
Acquisition Introduction, (Features and Components of - Foundation Fieldbus,
Profibus, HART,Interbus, Bitbus, CC -Link, Modbus, Batibus,
DigitalSTROM, Controller Area Network, DeviceNet, LonWorks, ISA
100.11a, Wireless HART, LoRa and LoRaWAN) NB -IoT, IEEE
802.11AH,
Distributed Control System, PLC, SCADA

Self-learning Topics: Study SCADA, PLC in detail. 10 CO3

IV
IIOT
Middleware
and WAN
Technologies (From Industrial Application Perspective)
Examining Middleware Transport Protocols (TCP/IP, UDP, RTP,
CoAP), Middleware Software Patterns (Publish Subscribe Pattern,
Delay Tolerant Networks),
Software Design Concepts – Application Programming Interface –
A Technical Perspective, Why Are APIs I mportant for Business?
Web Services,
IIOT Middleware Platforms – Middleware Architecture 10 CO4

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227
IIOT WAN Technologies and Protocols - IIoT Device Low -Power
WAN Optimized Technologies for M2M, SigFox,LoRaWAN,nWave,
Dash7 Protocol, Ingénue RPMA, Low Pow er Wi -Fi, LTE
Category -M, Weightless, Millimeter Radio
Self-learning Topics: Study different IIoT Middleware and WAN
Technologies.
V
IIOT
Blockchain
and Security Blockchains and cryptocurrencies in IoT, Bitcoin (blockchain -
based), IOTA - distributed ledger (directed a cyclical graph -based),
Government regulations and intervention, US Congressional Bill –
Internet of Things (IoT) Cyber security Improvement Act of 2017,
Other governmental bodies, IoT security best practices, Holistic
security.
Self-learning Topics: Case study on IIoT Block chain and Security. 08 CO5

VI IIOT
Applications
and Securities The IoT Security Lifecycle -
The secure IoT system implementation lifecycle, Implementation
and integration, IoT security CONOPS document, Network and
security integration, System security verification and validation
(V&V), Security training, Secure configurations, Operations and
maintenance, Managing identities, roles, and attributes, Security
monitoring, Penetration testing, Compl iance monitoring, Asset
and configuration management, Incident management, Forensics,
Dispose, Secure device disposal and zeroization, Data purging,
Inventory control, Data archiving and records management
Securing the Industrial Internet - Security in Man ufacturing, PLCs
and DCS, Securing the OT (Operation Technology), Network,
System Level: Potential Security Issues, Identity Access
Management
Develop New Business Models –
Adopt Smart Architectures and Technologies, Sensor -Driven
Computing, Industrial An alytics, Intelligent Machine Applications,
Transform the Workforce
Case Studies –
Healthcare Applications in Industries – Challenges associated with
Healthcare, Introduction, Smart Devices, Advanced technologies
used in Healthcare.
Inventory Management an d Quality Control – Introduction,
Inventory Management and IIOT, Quality Control
Manufacturing Industry, Automotive Industry and Mining Industry
Self-learning Topics: Study real time IIoT application. 08 CO6

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228
Text Books:
1. “Industry 4.0: The Industrial Internet of Things”, by Alasdair Gilchrist (Apress)
2. “Introduction to Industrial Internet of Things and Industry 4.0”,by Sudip Misra, Chandana Roy And Anandarup
Mukherjee, CRC Press (Taylor & Francis Group)
3. “Internet of Things Principles and Paradigms”, by Rajkumar Buyya, Amir Vahid Dastjerdi, ELSEVIER Inc.
4. Internet of things For Architects, Perry Lea Packt Publication,2018
References:
1. “Practical Internet of Things Security”, by Brian Russell, Drew Van Duren (Packt Publishing)
2. “Industrial Internet of Things and Communications at the Edge”, by Tony Paine, CEO, Kepware Technologies
3. “Architectural Design Principles For Industrial Inter net of Things”, Hasan Derhamy, Luleå University of Technology,
Graphic Production
Online References:
Sr. No. Website Name
1. https://onlinecourses.nptel.ac.in/noc20_cs69/preview
2. https://www.coursera.org/specializations/developing -industrial -iot
3. https://www.coursera.org/lecture/advanced -manufacturing -enterprise/the -industrial -
internet -of-things -iiot-59EvI
4. https://www.coursera.org/lectu re/industrial -iot-markets -security/segment -12-
blockchains -l4aG9
Assessment:
Internal Assessment (IA) for 20 marks:
 IA will consist of Two Compulsory Internal Assessment Tests. Approximately 40% to 50% of syllabus
content must be covered in First IA Test and remaining 40% to 50% of syllabus content must be
covered in Second IA Test
 Question paper format
 Question Paper will comprise of a total of six questions each carrying 20 marks Q.1 will be
compulsory and should cover maximum contents of the syllabus
 Remaining questions will be mixed in nature (part (a) and part (b) of each question must be from
different modules. For example, if Q.2 has part (a) from Module 3 then part (b) must be from any
other Module randomly selected from all the modules)
 A total o f four questions need to be answered


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229


University of Mumbai




Syllabus

Honours /Minor Degree Program
In
Waste Technology




FACULTY OF SCIENCE & TECHNOLOGY
(As per AICTE guidelines with effect from the academic year 2022 -2023)




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230

University of Mumbai
Waste Technology
(With effect from 2022 -23)

Year
and
Sem Course Code and
Course Title Teaching Scheme Hours/
Week Examination Scheme and Marks Credit
Scheme
Theory Seminar/
Tutorial. Pract. Internal
Assess
ment End
Sem
Exam Term
Work Oral
Total Credits
TE
Sem V HCWC 501: Solid
And Hazardous
Waste
Management 4 – – 20 80 – – 100 4
Total 4 – – 100 – – 100 4
Total Credits=04
TE
Sem
VI HCWC601: Liquid
Effluent
Management 4 – – 20 80 – – 100 4
Total 4 – – 100 – – 100 4
Total Credits=04
BE
Sem
VII HCWC701: Waste
Volorization I 4 – – 20 80 – – 100 4
HCWSBL701:
Waste Technology
.Skill Based Lab -1 – – 2 – – 50 50 100 2
Total 4 – 2 100 50 50 200 6
Total Credits=06
BE
Sem
VIII HCWC801:
Sustainable Waste
Volorization II 4 – – 20 80 – – 100 4
Total 4 – – 100 – – 100 4
Total Credits=04
Total Credit for Semester V+VI+VII+VIII=18


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231
Waste Technology: Semester V
Course Code Course Name Credits
HCWC501 SOLID AND HAZARDOUS WASTE MANAGEMENT 04


Theory Term Work / Practical/Oral Total
Internal Assessment End
Sem
Exam Duration of End
Sem
Exam TW PR OR
Test -I Test -II Average
20 20 20 80 03 Hrs -- -- 100

Course Objectives:

1. To recognize the relevant, regulations that apply for facilities used for disposal and destruction of
waste.
2. To provide in depth knowledge of municipal solid waste management
3. To provide in -depth knowledge of hazardous waste management
4. To provide in -depth knowledge of Physico -chemical processes useful for the treatment of
municipal and solid wastes
5. To provide in -depth knowledge of biological processes useful for the treatment of municipal and
solid wastes.
6. Know the necessity of environment risk assessment.

Module Content Hours
1 Rules and Regulations
Municipal solid waste (management and handling) rules, hazardous waste (management
and handling) rules, biomedical waste handling rules, fly ash rules, recycled plastics usage
rules, batteries (management and hand ling) rules 4
2 Municipal Solid Waste Management
Need for management, sources, composition, generation rates, collection of waste,
separation, transfer and transport of waste, treatment and disposal options , source
reduction of wastes, recycling and reuse. 9
3 Hazardous Waste Management
Need for management, hazardous characterization of waste, compatibility and
flammability of chemicals, waste sampling, TCLP tests, fate and transport of chemicals,
health effects 9
4 Physicochemical Treatment of Solid and Hazardous Waste
Chemical treatment processes for MSW (combustion, stabilization and solidification of
hazardous wastes), physicochemical processes for hazardous wastes (soil vapour
extraction, air stripping, chemical oxidation), ground water contamination and
remediation 9 Course Hours Credits Assigned
Theory Practical Tutorial Theory Tutorial Total
04 - - 04 - - 04

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232
5 Biological Treatment of Solid and Hazardous Waste
Composting, bioreactors, anaerobic decomposition of solid waste, principles of
biodegradation of toxic waste, inhibition, co -metabolism, oxidative and reductive
processes, slurry phase bioreactor, in -situ remediation. Landfill design for solid and
hazardou s wastes, leachate collection and removal, landfill covers, incineration 14
6 Environmental Risk Assessment
Defining risk and environmental risk, methods of risk assessment, case studies 7

Course Outcome:
On completion of the course the students will:
1 understand rules and regulations for handling solid waste.
2 understand principals of municipal solid waste management.
3 understand hazardous waste management.
4 learn physicochemical treatment of solid and hazardous waste.
5 understand biological treatment of solid and hazardous waste.
6 understand environment risk assessment.

Assessment
Internal Assessment (20 Marks):
Consisting Two Compulsory Class Tests.
First test based on approximately 40% of contents and second test based on remaining contents (approximately
40% but excluding contents covered in Test I).

End Semester Examination (80 marks):
1. Weightage of each module in end semester examination will be proportional to number of respective lectures.
2. Question paper will comprise of total six questions, each carrying 20 marks.
3. Question 1 will be compulsory and should cover maximum contents of the curriculum.
4. Remaining questions will be mixed in nature (for example if Q.2 has part (a) from module 3 then part (b) will
be from any module other than module 3).
5. Only Four questions need to be solved.

Test Books/Reference Books:
1 Tchobanoglous G., Theisen H. and Vigil S.A., "Integrated Solid Waste Management",
McGraw -Hill International editions.
2 Bhide A.D. and Sundaresan B.B., "Solid Waste Management, Collection, Processing and
Disposal", Nagpur.
3 "Manual on Municipal Solid Waste Management", CPHEEO, Ministry of Urban
Development, Government of India.
4

5 Management and Handling Rules for: municipal solid waste, biomedical waste,
hazardous waste and radioactive wastes, Government of India Publications.
Solid Waste Management Hand Book – Pavoni

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233
Waste Technology : Semester V I
Course Code Course Name Credits
HCWC601 LIQUID EFFLUENT MANAGEMENT 04


Theory Term Work / Practical/Oral Total
Internal Assessment End
Sem
Exam Duration of End
Sem
Exam TW PR OR
Test -I Test -II Average
20 20 20 80 03 Hrs -- -- 100

Course Objectives:
1 To learn how to minimize waste and study available treatment options.
2 To know concept of pollution control.
3 To learn ion exchange process and various adsorption techniques.
4 To study advanced methods for effluent management.
5 To know methods of waste reduction and how to recover byproducts.
6 To learn concepts and design of natural treatment system.

Module Contents Hours
1 Waste Minimization and Treatment options
Methods of waste volume and strength reductions, Wast e minimization - 4 R concepts, Waste
audit, Classification of treatment and development of treatment flow sheets. 9
2 Pollution control
Zero discharge concept. Concept of common effluent treatment plant - objectives, types of
CETP, technical and financial aspects. Rural wastewater systems – septic tanks, two -pit latrines,
ecotoilet, soak pits. 8
3 Ion Exchange and Adsorption
Ion exchange process, ion exchange resins, exchange capacity, ion exchange, chemistry and
reactions, Design of ion exchange units, Disposal of concentrate waste streams. Types of
adsorption, adsorption isotherms, activated carbon adsorption kinetics, analysis and desi gn of
adsorption column. 9
4 Advanced methods for effluent management
Ozonation, photocatalysis, wet air oxidation, evaporation, reverse osmosis, biological
treatment for toxic waste 9
5 Waste Reduction/Byproduct recovery
Waste reduction/ byproduct recovery for sugar, paper mill, petroleum and oil refineries,
steel and engineering industries, fertilizer and pesticide industries, organic & inorganic
manufacturing industries 9 Course Hours Credits Assigned
Theory Practical Tutorial Theory Tutorial Total
04 - - 04 - - 04

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234
6 Natural Treatment Systems
Constructed wetland and aquatic treatment systems; Types - free water surface and subsurface
constructed wetlands, selection of plants, removal mechanisms, applications, design procedure
for constructed wetlands, management of constructed wetlands 8

Course Outcomes:
1 Understand minimizing the waste and available treatment options.
2 Understand concept of pollution control.
3 Understand ion exchange process/design and adsorption techniques.
4 Advanced methods for effluent management.
5 Waste reduction/byproducts recovery for manufacturing industries.
6 Concepts and design of natural treatment system.

Assessment
Internal Assessment (20 Marks):
Consisting Two Compulsory Class Tests. First test based on approximately 40% of contents and second test based
on remaining contents (approximately 40% but excluding contents covered in Test I).

End Semester Examination (80 marks):
1. Weightage of each module in end semester examination will be proportional to number of respective
lectures.
2. Question paper will comprise of total six questions, each carrying 20 marks.
3. Question 1 will be compulsory and should cover maximum contents of the curriculum.
4. Remaining questions will be mixed in nature (for example if Q.2 has part (a) from module 3 then part (b)
will be from any module other than module 3).
5. Only Four questions need to be solved.

Text Books and References:
1 Eckenfelder, W.W., Industrial Water Pollution Control, McGraw -Hill, 1999.
2 Arceivala, S.J., Wastewater Treatment for Pollution Control, McGraw -Hill, 1998.
3 Frank Woodard, Industrial waste treatment Handbook, Butterworth Heinemann, New Delhi,
2001








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235
Waste Technology : Semester V II
Course Code Course Name Credits
HCWC701 WASTE VALORIZATION I 04


Theory Term Work / Practical/Oral Total
Internal Assessment End
Sem
Exam Duration of End
Sem
Exam TW PR OR
Test -I Test -II Average
20 20 20 80 03 Hrs -- -- 100

Course Outcomes:
1. To know waste valorization process used for reduce, reuse and recycle.
2. To learn biovalorization of industrial waste.
3. To know concept of biorefineries and related factors.
4. To learn recent trends and vermiculture.
5. To know biovalorisation of agriculture biomass.
6. To study case studies based on waste recycling.

Module Contents Hours
1 Wastes valorization processes:
Preparation for reuse, recycling, and other valorisation processes. Analysis of advantages and
limitations. 5
2 Bio-valorisation of industrial wastes:
Anaerobic bio -valorisation of leather industry solid waste and production of high value -added
biomolecules and biofuels, Anaerobic bio -valorisation of pulp and paper mill waste, Bio -
valorisation of winery industry waste to produce value -added products, Conversion of textile
effluent wastewater into fertilizer using m arine cyanobacteria along with different
agricultural waste. 12
3 Biorefineries:
Biorefinery for hydrocarbons and emerging contaminants, Biodesulfurization of petroleum
wastes, Microbial leaching of heavy metals from e - waste, opportunities and challenges. 8
4 Biovalorisation of agricultural biomass:
Recent trends in biorefinery -based valorisation of lignocellulosic biomass, Protein engineering
approaches for lignocellulosic ethanol biorefinery, Biovalorization potential of agro
forestry/industry biomass for optically pure lactic acid fermentation, Opportunities and
challenges, Agro -based sugarcane industry wastes for production of high -value bioproducts 11
5 Recent trends and vermiculture
Recent trends and challenges in bioleaching technologies, membrane separation technologies
for downstream processing. Definition, scope and importance – common species for culture 8 Course Hours Credits Assigned
Theory Practical Tutorial Theory Tutorial Total
04 - - 04 - - 04

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236
– environmental requirements – culture methods - applications of vermiculture -Potentials
and constraints for composting in India -large scale and decentralized plants.
6 Case studies on waste recycling
Recycling technologies for paper, glass, metal, plastic, used lead acid battery, end of life
vehicle recycling, electronic waste recycling, waste oil, recycling solvent recovery, drivers
and barriers for material recycling, social, legal and economic factors, environmental impacts
of waste recycling, design for the environment the life cy cle approach. 8

Course Outcomes:
On completion of this course students will
1 understand the waste valorization process to reduce, reuse and recycle.
2 understand Biovalorization of industrial waste
3 understand concept of biorefineries, their opportunities and challenges
4 understand recent trends and vermiculture.
5 understand biovalorisation of agriculture biomass.
6 understand waste recycling using case studies.

Assessment

Internal Assessment (20 Marks):
Consisting Two Compulsory Class Tests. First test based on approximately 40% of contents and second test based
on remaining contents (approximately 40% but excluding contents covered in Test I).

End Semester Examination (80 marks):
1. Weightage of each module in end semester examination will be proportional to number of respective
lectures.
2. Question paper will comprise of total six questions, each carrying 20 marks.
3. Question 1 will be compulsory and should cover maximum contents of the curriculum.
4. Remaining questions will be mixed in nature (for example if Q.2 has part (a) from module 3 then part (b)
will be from any module other than module 3).
5. Only Four questions need to be solved.
Text Books/ Reference Books
1 Aarne Veslind and Alan E Rimer (1981), Unit operations i n Resource Recovery
Engineering , Prentice Hall Inc., London
2 Manser A G R, Keeling A A (1996). Practical handbook of processing and recycling
on municipal waste. Pub CRC Lewis London, ISBN 1 -56670 -164
3 Chiumenti, Chiumenti, Diaz, S avage, Eggerth, and Goldstein , Modern Composting
Technologies JG Press October 2005
4 Charles R Rhyner (1995),Waste Management and Resource Recovery, Lewis


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237



Course Objectives: -
Students will able to
1 Understand analyze properties of MSW
2 Understand vermicomposting on a lab scale.
3 Understand aerobic and anaerobic digesting of solid waste.
4 Will know of incineration process and handling of HSW.
5 Understand ecology baseline and impact of waste on environment.
6 Understand process of project report preparation based on case studies.

List of Experiments (minimum eight)

Waste Technology based experiments should be conducted.
1. Determination of pH of MSW
2. Determination of Total Solids, fixed solids and volatile solids
3. Determination of nutrient value (NPK)
4. Lab scale study on vermicomposting
5. Lab scale study of aerobic and anaerobic digesting of solid wastes (Both industrial & Municipal)
6. A Visit to the Hazardous waste Generation or disposal site.
7. Practical knowledge and working of incinerators
8. Visit to Industrial area, especially the handling of Hazardous materials
9. Ecology baseline and impact of waste – disposal on vegetation Waste Technology : Semester V II
Course Code Course Name Credits
HCWSBL701 WASTE TECHNOLOGY SKILL BASED LAB 02
Course Hours Credits Assigned
Theory Practical Tutorial Theory Practical Tutorial Total
- 04 - -- 02 - 02
Theory Term Work / Practical/Oral Total
Internal Assessment End
Sem
Exam Duration of End Sem
Exam
TW
Oral Test -I Test -II Average
- - - - -------------- 50 50 100

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238
10. Preparation of Project report based on a case study of one hospital Study of the source, generation rates and
characteristics of hazardous wastes and their regulation, handling, treatment, and disposal. Special emphasis is
placed o n process design of waste handling, treatment and disposal systems.
Course Outcomes:
At the end of the course the student will be able to:
1 Learn to analyze properties of MSW.
2 To study vermicomposting on a lab scale.
3 To carry out aerobic and anaerobic digesting of s olid waste.
4 To acquire knowledge of incineration process and handling of HSW.
5 Learn to analyze ecology baseline and impact of waste.
6 Learn about project report preparation based on case studies.

Term work (25 marks)
Term work should be evaluated based on performance in practical/Assignments.
Practical Journal/Assignments: 45 marks
Attendance: 05 marks
Total: 50 marks

End Semester Oral Examination ( 50 marks)
 A student will become eligible for Oral examination after completing 8 out of 10 experiments/Assignments

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239
Waste Technology : Semester V III
Course Code Course Name Credits
HCWC801 WASTE VALORIZATION II 04

Course Hours Credits Assigned
Theory Practical Tutorial Theory Tutorial Total
04 - - 04 - - 04

Theory Term Work/ Practical/Oral Total
Internal Assessment End
Sem
Exam Duration of End
Sem
Exam
TW
PR
OR
Test -I Test
-II Aver
age
20 20 20 80 03 Hrs -- - -- 100

Course Objective:
1 To know concept of energy from waste.
2 To study devices for converting waste into energy.
3 To undertake case studies based on impact of pollution on environmental and health.
4 To learn biohydrogen processes its applications and briquetting techniques.
5 To know microalgal biovalorization.
6 To learn process of converting biomass to energy.

Module Content s Hours
1 Introduction to Energy from waste
Present status of technologies for conversion of waste into energy, design of waste to
energy plants for cities, small townships and villages. Sources of energy generation,
Classification of waste as fuel – agro based, forest residue, industrial waste 8
2 MSW –conversion devices
Incinerators, gasifiers, digestors. , land fill gas generation and utilization, ,Anaerobic
Digestion: Biogas production 9
3 Environmental and health impacts -case studies
Environmental and health impacts of waste to energy conversion, case studies of
commercial waste to energy plant s, waste to energy - potentials and constraints in India,
eco-technological alternatives for waste to energy conversions. 10
4 Briquetting
Industrial Application of Gasifiers -Utilization and Advantages of Briquetting, environmental
and health impacts of incineration; strategies for reducing environmental impacts. 9
5 Biohydrogen : Overview on Processes involved, and from Biohydrogen and applications. 8
6 Microalgal biovalorization:
Conventional and nonconventional approach, Integration of wastewater valorization with
microalgae for biofuel production, 8

Course Outcome:
Students will be able to
1 understand the concept of energy from waste.

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240
2 understand various devices to convert energy from waste.
3 understand environmental and health impacts using case studies.
4 understand biohydrogen processes, applications and briquetting techniques.
5 understand concept of microalgal biovalorization.
6 understand process for biomass to energy.

Assessment

Internal Assessment (20 Marks):
Consisting Two Compulsory Class Tests. First test based on approximately 40% of contents and second test based
on remaining contents (approximately 40% but excluding contents covered in Test I).

End Semester Examination (80 marks):

1. Weightage of each module in end semester examination will be proportional to number of respective lectures.
2. Question paper will comprise of total six questions, each carrying 20 marks.
3. Question 1 will be compulsory and should cover maximum contents of the curriculum.
4. Remaining questions will be mixed in nature (for example if Q.2 has part (a) from module 3 then part (b) will
be from any module other than module 3).
5. Only Four questions need to be solved.
Textbooks /References

1 Rada E.C. Waste Management and Valorization: Alternative Technologies., CRC Press, Taylor and
Francis Group, 2016.
2 Rathinam N.K. and Sani, R.K. Biovalorisation of Wastes to Renewable Chemicals and Biofuels.
Elsevier Inc. 2020.




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241


University of Mumbai




Syllabus

Honours /Minor Degree Program
In
Electric Vehicles




FACULTY OF SCIENCE & TECHNOLOGY

(As per AICTE guidelines with effect from the academic year 2022 -2023)




Page 245


242







University of Mumbai
Electric Vehicles
(With effect from 2022 -23)
Year
&
Sem
Course Code and
Course Title Teaching
Scheme Hours / Week Examination Scheme and Marks Credit
Scheme
Theory Seminar/
Tutorial Pract Internal
Assess
ment End
Sem
Exam Term
Work Oral Total Credits

TE
Sem
V HEV C501:
Vehicular Systems
and Dynamics 04 -- -- 20 80 -- -- 100 04
Total 04 - -- 100 - - 100 04
Total Credits = 04

TE
Sem.
VI HEVC601:
EV Drive and
Energy Sources 04 -- -- 20 80 -- -- 100 04
Total 04 - - 100 - - 100 04
Total Credits = 04


BE
Sem.
VII HEVC701:
Automotive
Controllers and
Auxiliary Systems 04 -- -- 20 80 -- -- 100 04
HEVSBL701:
Electric Vehicles
Lab -- -- 04 -- -- 50 50 100 02
Total 04 - 04 100 50 50 200 06
Total Credits = 06

BE
Sem.
VIII
HEVC801:
Electric Vehicle
System Design 04 - -- 20 80 -- -- 100 04
Total 04 - - 100 - - 100 04
Total Credits = 04

Total Credits for Semesters V,VI, VII &VIII = 04+04+06+04 = 18

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243

‘Electric Vehicle’ - SEM -V
Course
Code
Course Name Teaching Scheme (Contact Hours) Credits Assigned
Theory Tutorial Theory Tutorial Total
HEVC501 Vehicular Systems and Dynamics 04 - 04 - 04


Course
code

Course Name Examination Scheme
Theory
Term
Work
Total Internal Assessment End
Sem.
Exam Exam
Duration
(Hrs.) Test 1 Test 2 Avg.
HEVC501 Vehicular Systems and Dynamics 20 20 20 80 03 - 100

Course
Objectives 1. To study different automotive components and subsystems
2. To explore and compare the transition of automotive domain from ICE to electric vehicles
Course
Outcomes Upon successful completion of this cou rse, the learner will be able :
1. To Illustrate the general configuration and identify various components of automobile.
2. To define the functionality and working principles of different types of Automotive Powertrains
3. To illustrate the working of various automotive transmission systems
4. To identify and illustrate the various hybrid electric powertrains and their different modes of
operations
5. To explain the basic and state of the art of Electric vehicles and its major parts.
6. To compare and contrast the performance of ICE vehicles, HEVs and EVs.

Module Contents Hours
1. Vehicle Mechanics:
History of Vehicle Development, General Configuration of Automobile, Body and Chassis
Fundamentals: General Packaging, Types of Structural System, Backbone Construction; Body
and Chassis Materials.
Automotive Powertrain , Mechanical Suspensions system, Steering System , NVH, Control
System Integration and Implementation.
Front -Wheel Drive (FWD) Powertrains, Rear -Wheel Drive Powertrains (RWD), Multi -Wheel
Drive Powertrains (AWD and 4WD) 10
2. Transmission Systems:
Transmission gears, Manual Transmission (MT), Automatic Transmission (AT), Automated
Manual Transmissions (AMT) and Continuously Variable Transmissions (CVT);
Manual Transmissions Powertrain Layout and Manual Transmission Structure, Power Flows
and Gear Ratios, Manual Transmission Clutch and its structure. Drivetrain and Differential 10
3. Automotive Subsystems:
Automotive Aero -dynamics , Vehicle Power Demand Analysis; Types of suspension and drive,
Braking systems; Tyre Mechanics: Tyres and wheels, Tyre characteristics; Vehicle handling &
stability; Automotive instrumentation 06
4. ICE Performance Characteristics:
Power and torque generat ion, specific fuel consumption; Engine emissions , control and
norms; Efficiencies - fuel conversion efficiency, mechanical efficiency, volumetric efficiency 06

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5. Hybrid Powertrain:
Series HEVs, Parallel HEVs, Series –Parallel HEVs, Complex HEVs, Operating Modes, Degree
of Hybridization, Comparison of HEVs, Plug -in Hybrid Ele ctric Vehicles (PHEVs) ; Real Life
examples of HEVs 10
6. Electric Vehicles:
Basics of Electric Vehicles, Current Status and Trends for EVs , Battery Electric Vehicles (BEVs),
Fuel -Cell Electric Vehicles (FCEVs), Electric Machines for EV applications, EV Transmission:
Single -Speed EV Transmission, Multiple Ratio EV Transmissions.
Comparison of ICE vehicle with HEVs and EVs. National Policy for adoption of EVs 10

Text Books: -
1. Vehicle Powertrain Systems by Behrooz Mashadi and David Crolla, Wiley, 2012
2. Automotive Aerodynamics by Joseph Katz, Wiley, 2016
3. Automotive Chassis Engi neering, by David C. Barton and John D. Fieldhouse, Springer, 2018
4. Automotive Engineering Powertrain, Chassis System and Vehicle Body Edited by David A. Crolla, Elsevier,
2009
5. Automotive Power Transmission Systems by Yi Zhang and Chris Mi, Wiley, 2018
6. Linear Electric Machines, Drives, and MAGLEVs Handbook, by Ion Boldea, CRC Press. 2013
7. Modern Electric, Hybrid Elect ric, and Fuel Cell Vehicles b y Mehrdad Ehsani, Yimin Gao, Sebastien E. Gay, and
Ali Emadi, CRC Press 2005
8. Electric Vehi cle Technology Explained by James Larminie and John Lowry, John Wiley, 2003
9. Electric and Hybrid Vehicles - Design Fundamentals by Iqbal Husain, CRC Press, 2005
Referen ce Books: -
1. Encyclopaedia of Automotive Engineering edited by David Crolla et al, Wiley, 2014
2. Design and Control o f Automotive Propulsion Systems by Zongxuan Sun and Guoming Zhu, CRC Press, 2015
3. The Automotive Transmission Book by Robert Fischer , Ferit Küçü kay, Gunter Jürgens , Rolf Najork, and
Burkhard Pollak, Springer, 2015
4. Noise and Vibration C ontrol in Automotive Bodies by Jian Pang, Wiley, 2019

Website Reference / Video Courses:
1. NPTEL Web course: Fundamentals of Automotive Systems, by Prof. C.S. Shankar Ram,
IIT Madras, https://nptel.ac.in/courses/107/106/107106088/

Assessment:
Internal Assessment consists of two tests out of which; one should be compulsory class test (on minimum 02
Modules) and the other is either a class test or assignment on live problems or course project

Theory Examination :
1. Question paper will comprise of 6 questions, each carrying 20 marks.
2. Total four questions need to be solved.
3. Q.1 will be compulsory, based on entire syllabus wherein sub questions of 2 to 5 marks will be asked.
4. Remaining question will be randomly selected from all the modules.




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245
‘Electric Vehicle’ - SEM -VI
Course
Code
Course Name Teaching Scheme (Contact
Hours) Credits Assigned
Theory Tutorial Theory Tutorial Total
HEVC601 EV Drive and
Energy Sources 04 - 04 - 04


Course
code

Course Name Examination Scheme
Theory
Term
Work
Total Internal Assessment End
Sem.
Exam Exam
Duration
(Hrs.) Test 1 Test 2 Avg.
HEVC601 EV Drive and
Energy Sources 20 20 20 80 03 - 100

Course
Objectives 1. To explore and understand various traction motors, power drives and control strategies used in
EVs.
2. To get conversant with the energy sources used in EVs and their state of the art.
3. To understand the various battery charging and management systems
Course
Outcomes Upon successful completion of this course, the learner will be able to:
1. To identify and assess various traction motors along with their suitability in various EV segments
2. To describe and differentiate various power c onverters and their control used in EV drives
3. To evaluate the battery specifications using various design considerations for EVs
4. To illustrate different battery charging methods and protocols
5. To explain the impact of large scale integration of EV charging infra in existing grid and its mitigation
techniques.
6. To illustrate the need and importance of drive cycles used in testing of automobiles.

Module Contents Hours
1. Introduction to Traction M otors :
DC Machines - Brushed and Brushless DC motors (BLDC); AC Motors: Induction motors (IM),
permanent -magnet ac synchronous motor -surface -permanent -magnet (SPM) motors and
interior -permanent -magnet (IPM) motors; PM Materials; Switched Reluctance Motor
(SRM); Basic construction details and working principles of each of the machine. In -Wheel
Motors
Comparison of Traction Machines; Specifications of the motors, Characteristic Curves of a
Machines: Constant -Torque Mode, Constant -Power Mode; Efficiency Map;
Suitability of each machine in Electric vehicle domain for 2W, 3W , 4 wheeler and large size
vehicles. Real life examples; Review of advancement in EV Motors and Drives. 10
2. Power Converters for EV drive:
Power Conversion –Basic Principle, review of DC -DC converters, DC -AC Converters used in
EV applications; Power topo logies for IM, BLDC, PMSM and SRM motors.
Traction Drives, Modulation schemes: Sinusoidal Pulse Width Modulation, SPWM with
third harmonic injection, Space vector modulation, comparison of modulation techniques.
Converter / Inverter Loss calculation, Heat -sinking: passive and active cooling. 08

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3. Control of Power converters and Motors:
Induction Motor Control: Variable -Voltage Variable -Frequency Control (VVVF), Field -
Oriented Control (FOC), Direct Torque Control (DTC);
PM Synchronous Motor Control: Field -Oriented Control of PMSM, Flux -Weakening Control
of PMSM, Position Sensorless Control of PMSM.
SRM motor control: Current chopping control (CCC), Torque -Ripple Minimization Control
BLDC Motor Control : Trapezoidal back EM F BLDC motor control 10
4. Energy Sources for EV:
Overview of energy sources for electric vehicle: Batteries, Fuel Cell, Ultra -capacitor and
flywheel energy storage; Hybridization of energy sources for electric and hybrid vehicles ;
Comparison of sources.
Batteries : Lead -acid battery, Nickel -based batteries, Sodium based batteries, lithium
batteries Metal/air batteries;
Battery parameters, Battery pack formation and testing, SoC & SoH, Estimation of SoC.
Battery cell balancing, Battery management System (BM S), Thermal and safety
considerations in battery pack design.
Voltage and AHr/ kWhr ratings of ES for EV applications: Major design considerations 10
5. Battery charging Infrastructure:
AC and DC charging, CC -CV charging, Pulse charging; On -board and off -board charging;
Stand ards and protocols for charging;
Fast DC chargers, Home and Public charging infrastructure; Wireless power transfer (WPT)
technologies for EVs, Move -and-charge technology.
Charging Infrastructure -standardization and connectivity issue s; SAE J1772, CHAdeMo,
GB/T, CCS2 battery charging protocols. OCPP protocol
Impact on existing power grid, G2V and V2X - Vehicle -to-home (V2H), vehicle -to-vehicle
(V2V), and vehicle -to-grid (V2G) energy systems. Renewable Energy Based Charging infra. 10
6. EV Drive Cycle Testing :
Need for a driving cycle , different Drive Cycles: NEDC, EUDC, EPA, WLTP, and FTP -75;
Testing of EV for rang e per charge for a given drive cy cle 04

Text/Reference Books: -
1. Fundamentals And Applications Of Lithium -Ion Batteries In Electric Drive Vehicles by Jiuchun Jiang and
Caiping Zhang, Wiley, 2015
2. Battery Management Systems for Large Lithium -Ion Battery Packs, by Davide Andrea, Artech House
Publication, 2010
3. Electric Vehi cle Battery Systems by Sandeep Dhameja, Newens, 2002
4. Fundamentals And Applications Of Lithium -Ion Batteries In Electric by Jiuchun Jiang and Caiping Zhang, Wiley,
2015
5. Optimal Charging Control of Electric Vehicles in Smart Grids by Wanrong Tang and Ying J un Zhang, Springer,
2017
6. Plug In Electric Vehicles in Smart Grids Charging Strategies Edited by Sumedha Rajakaruna, Farhad Shahnia
and Arindam Ghosh, Springer 2015
7. Technologies and Applications for Smart Charging of Electric and Plug -in Hybrid Vehicles ed ited by Ottorino
Veneri, Springer, 2017
8. Solar Powered Charging Infrastructure for Electric Vehicles A Sustainable Development Edited by Larry E.
Erickson, Jessica Robinson, Gary Brase, and Jackson Cutsor, CRC Press, 2017
9. Energy Systems for Electric and Hy brid Vehicles Edited by K.T. Chau, IET, 2016

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10. Handbook of Automotive Power Electronics and Motor Drive Edited by Ali Emadi, CRC Press, 2005
11. Electric And Hybrid Vehicles Power Sources, Models, Sustainability, Infrastructure And The Market by
Gianfranco Pist oia, Elsevier, 2013
12. AC Motor Control and Electrical Vehicle Applications, Second Edition by Kwang Hee Nam CRC Press, 2019
Website Reference / Video Courses:
1. NPTEL Web Course: Electric Vehicles - Part 1 by PROF. AMIT KUMAR JAIN Department of Electrical Engineering
IIT Delhi; https://nptel.ac.in/courses/108/102/108102121/
2. NPTEL Web Course: Fundamentals of Electric vehicles: Technology & Economics : by Prof. Ashok Jhunjhunwala,
Prof. Prabhjot Kaur, Prof. Kaushal Kumar Jha and Prof. L Kannan, IIT Madras,
https://nptel.ac.in/courses/108/106/108106170/
3. NPTEL Web Course: Introduction to Hybrid and Electric Vehicles by Dr. Praveen Kumar and Prof. S. Majhi, IIT
Guwahati, https://nptel.ac .in/courses/108/103/108103009/

Assessment:
Internal Assessment consists of two tests out of which; one should be compulsory class test (on minimum 02
Modules) and the other is either a class test or assignment on live problems or course project

Theory Examination :
1. Question paper will comprise of 6 questions, each carrying 20 marks.
2. Total four questions need to be solved.
3. Q.1 will be compulsory, based on entire syllabus wherein sub questions of 2 to 5 marks will be asked.
4. Remaining question will be randomly selected from all the modules.

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‘Electric Vehicle’ - SEM -VII
Course
Code
Course Name Teaching Scheme
(Contact Hours) Credits Assigned
Theory Tutorial Theory Tutorial Total
HEVC701 Automotive Controllers and
Auxiliary Systems 04 - 04 - 04


Course
code

Course Name Examination Scheme
Theory
Term
Work
Total Internal Assessment End
Sem.
Exam Exam
Duration
(Hrs.) Test 1 Test 2 Avg.
HEVC701 Automotive Controllers and
Auxiliary Systems 20 20 20 80 03 - 100

Course
Objectives 1. To Identify functionalities of various automotive controllers and auxiliary s ystems
2. To study various automotive sensors and actuators
3. To explore details of energy sources management system, thermal management system and overall
system integrati on in EVs/ HEVs
Course
Outcomes Upon successful completion of this cou rse, the learner will be able :
1. To illustrate functionality of various auxiliary subsystems used EVs
2. To demonstrate the use of VCUS and ECUS in automobile
3. To describe the need and functionality of a utomotive sensors / actuators and networking
4. To illustrate the design and management aspects of EV energy sources
5. To describe the various heat losses, and thermal management systems incorporated in EVs
6. To elaborate on System Integration and resource optimization in EVs

Module Contents Hours
1. Introduction:
Review of Automotive electrical, electronic, communication and thermal subsystems ;
Review of Energy Storage (Power Plant) system, Main Traction Inverter, On -Board Charger
(OBC), LV Auxiliary Power Source, HV Batt ery Disconnect; Vehicle Control Unit (VCU) and ECUs .
Braking Systems: Energy Consumption in Braking, Braking Power and Energy on Front and Rear
Wheels, Brake System of EVs and HEVs, Series Brake -Optimal Feel, Series Brake -Optimal
Energy Recovery; Parallel Brake; Antilock Brake System (ABS); Fundamentals of Regenerative
Braking.
Steering System: In -car system networking, Steering ratio characteristic, St eering Stabilization ,
Over -steer, understeer, Electric -Power -Assisted Steer ing (EPAS); Autonomous vehicles,
Principle of object detection. 12
2. Vehicle Control Unit and Electronic Control Unit:
VCU functionality: Inverter control, battery management, charging control, vehicle functions
in transmission and engine control ; Advanced Driver Assistance System (ADAS) ;
Electronic control units (ECUs): Various Section ECUs and their networking; Body and Lighting
ECU (Key -less Entry, Sonar, HID, LED Lamps), Body ECU (Airbag). 08
3. Automotive sensors / actuators and networking :
Radar Sensor Detectors for Vehicle Safety Systems; Airborne Ultrasonic Imaging: SONAR Based
Image Generation for Autonomous Vehicles, Motor angle sensor, Steering angle sensor, Tyre
Pressure Monitoring Systems (TPMS); 10

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In Vehicle communication system: CAN, LIN, Ethernet, Flexray
4. Energy Storage (Power Plant) Management system:
Battery cell packaging, Battery Management System (BMS) , Design of battery pack and safety
considerations; High voltage cabling and cut -outs; Battery pack installation. Use of Battery -UC
Hybrid source; Fuel Cell (FC): FC management and Hydrogen storage in EV . 10
5. Thermal Management System:
Heat Calculation in various subsystems; HVAC system: HVAC compressor drive; Liquid cooling
system for Battery, Electric drive and On board charger. Design considerations for thermal
management system 06
6. System Integration and Implementation:
Vehicular Po wer Control Strategy and Energy Management: A Generic Framework, Definition,
and Needs, Methodologies for Optimization, Cost Function Optimization, Benefits of Energy
Management. 06

Text/Reference Books: -
1. Electric Powertrain Energy Systems, Power Electronics and Drives for Hybrid, Electric and Fuel Cell Vehicles by
John G. Hayes and G. Abas Goodarzi, Wiley, 2018.
2. Handbook of Automotive Power Electronics and Motor Drive Edited by Ali Emadi, CRC Press, 2005
3. Encyclopaedia of Automotive Engineering edited by David Crolla et al. , Wiley, 2014
4. Electric and Hybrid Vehicles Technologies, Modeling and Control: A Mechatronic Approach by Amir Khajepour,
Saber Fallah and Avesta Goodarzi, Wiley, 2014.
5. Hybrid Electric Ve hicles Principles and Applications with Practical Perspectives, Second Edition Chris Mi and M.
Abul Masrur, Wiley 2018.
6. Autonomous Vehicles Intelligent Transport Systems And Smart Technologies edited by Nicu Bizon, Lucian
Dascalescu and Naser Mahdavi Tabat abaei, Nova Publishers, 2014
7. Energy Management Strategies for Electric and Plug -in Hybrid Electric Vehicles by Sheldon S. Williamson,
Springer, 2013
8. Electric and Hybrid Buses for Urban Transport Energy Efficiency Strategies, by Bogdan Ovidiu Varga, Calin
Iclodean and Florin Mariasiu, Springer, 2016
Website Reference / Video Courses:
1. NPTEL Web Course: Electric Vehicles - Part 1 by PROF. AMIT KUMAR JAIN Department of Electrical Engineering
IIT Delhi; https://nptel.ac.in/courses/108/102/108102121/
2. NPTEL Web C ourse: by Fundamentals of Electric vehicles: Technology & Economics: Prof. Ashok Jhunjhunwala,
Prof. Prabhjot Kaur,Prof. Kaushal Kumar Jha andProf. L Kannan, IIT Madras,
https://nptel.ac.in/courses/108/106/108106170/
3. NPTEL Web Course: Introduction to Hybri d and Electric Vehicles by Dr. Praveen Kumar and Prof. S. Majhi, IIT
Guwahati, https://nptel.ac.in/courses/108/103/108103009/

Assessment:
Internal Assessment consists of two tests out of which; one should be compulsory class test (on minimum 02
Modules) and the other is either a class test or assignment on live problems or course project

Theory Examination :
1. Question paper will comprise of 6 questions, each carrying 20 marks.
2. Total four questions need to be solved.
3. Q.1 will be compulsory, based on entire syllabus wherein sub questions of 2 to 5 marks will be asked.
4. Remaining question will be randomly selected from all the modules.




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250
‘Electric Vehicle’ - SEM -VII
Course Code
Course Name Teaching Scheme (Contact Hours) Credits Assigned
Theory Practical Theory Practical Total
HEVSBL701 Electric Vehicles Lab 04 -- 02 02


Course code

Course Name Examination
Scheme
Theory
Term
Work
Oral
Total Internal Assessment End
Sem.
Exam Exam
Duration
(Hrs.) Test 1 Test 2 Avg.
HEVSBL701 Electric Vehicles Lab - - - - - 50 50 100

Course
Objectives 1. To provide hands -on with various major components used in EV/HEVs
2. To explore EV drives & control implementation along with analysis using simulation tool
or with hardware.
3. To study various auxiliary systems commonly used in EV.
Course
Outcomes Upon successful completion of this course, the learner will be able to:
1. Compare and contrast conventional vehicles and EV/HEVs.
2. Illustrate operations and features of Conventional, hybrid elect ric vehicle and electrical
vehicle Powertrains .
3. Describe the working of EV drives used for different kinds of electric motors.
4. Illustrate battery characteristics and working of BMS.
5. Describe the operation of On-board and Off -board EV charger s
6. Demonstrate the use of simulations tools along with hardware implementation for
evaluation of EV subsystems.

Contents
Electric Vehicles Lab: Experimental study based on the following topics
1. Conventional and electrical vehicle sub -systems and components
2. Conventional , hybrid electric vehicle and electrical v ehicle Powertrains
3. Motor performance test - for BLDC /PMSM/ IM/SRM motors ;
4. EV drive for BLDC/PMSM/IM /SRM motors
5. Battery cell and module - characterization
6. Battery Management System (BMS)
7. On-board and Off -board charger for EV
8. Study of Automotive Electronics -HVAC control, Steering Cont rol, VCU; 2/3 or 4 Wheeler EV.
(or any other experiment s based on EV/HEV related systems/ subsystems )

Use of software tools:
Use of tools like ADVISOR, MATLAB, SEMIKRON SEMISEL, P ython, C, Java platforms (or similar) etc. for the
following
1. Simulation/ Emulation of Vehicle performance analysis for Conventional and Electrical Vehicle
2. Design simulation of a battery pack with given specifications and constraints.
3. Simulation/ Em ulation of BLDC motor drive for performance analysis

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4. Simulation/ Em ulation of PMSM motor drive for performance analysis
5. Simulation/ Em ulation of IM motor drive for performance analysis
6. Simulation/ Em ulation of SRM motor drive for performance analysis
7. Simulation/ Em ulation of On board and Off board charger .
8. Simulation/ Em ulation of regenerative breaking.
(or any other simulation based on EV/HEV related systems/ subsystems )

Visit to industrial/ manufacturing facility:
1. Visit to EV manufacturing facility.
2. Visit to Battery pack /BMS design facility
3. Visit to battery Charger facility
4. Visit to Automotive Research Association of India (ARAI), Pune EV COE
(or a visit to any facility / industry / research institute carrying out work in the domain of EV)

Course Project
Course project to be carried out to design /fabricate/ program one of the vehicular sub -systems used in EV

Note: Students and teachers are encouraged to use the virtual labs whose links are as given below . The
remote -access to Labs in various disciplines of Science and Engineering is available. Students can conduct
online experiments which would help them in learning basic and advanced concepts through remote
experimentation.

Virtual Lab Website Reference
1. http://vlab.co.in/broad -area -electrical -engineering
2. https://www.vlab.co.in/broad -area -mechanical -engineering - Energy Storage Labs, Solar Energy lab,
Wind Energy Lab


Term work:
Term work shall consist of minimum eight experiments , at least one plant vi sit, and one course project . The
distribution of marks shall be as follows:
Journal / Experiment s Performance : 25 marks
Attendance : 05 marks
Plant Visit report : 10 marks
Course Project report : 10 Marks
The final certification and acceptance of term work ensures the minimum passing in the term work.

Oral Examination:
Oral examination will be based on entire lab work of HCEVSBL701 -Electric Vehicles Lab

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‘Electric Vehicle’ - SEM -VIII
Course
Code
Course Name Teaching Scheme (Contact Hours) Credits Assigned
Theory Tutorial Theory Tutorial Total
HEVC801 Electric Vehicle System Design 04 - 04 - 04


Course
code

Course Name Examination Scheme
Theory
Term
Work
Total Internal Assessment End
Sem.
Exam Exam
Duration
(Hrs.) Test 1 Test 2 Avg.
HEVC801 Electric Vehicle System Design 20 20 20 80 03 - 100

Course
Objectives 1. To illustrate the design philosophies used in the EV domain.
2. To explore the selection of power and control architecture of EV drives
3. To study the design aspects of EV battery packs and other auxiliary systems
Course
Outcomes Upon successful completion of this course, the learner will be able to:
1. To select and size the electric motor for a particular EV application and performance criteria
2. To select and size the battery pack to meet desired EV performance and
3. To design the EV drive system with functional safety considerations.
4. To illustrate the use of hybrid energy source for EV performance improvement
5. To illustrate the design aspects of A utomotive Subsystem
6. To design the EV chargers and charging infrastructure

Module Contents Hours
1. Selection/ Sizing of EV Electric Motors:
Electric Vehicle modelling, Tractive force calculations, Design considerations for 2W, 3W and
4W EVs; Torque, power and Speed requirement, Traction Limit, Maximum Acceleration
Limit, Maximum Grade Limit, Vehicle Power Demand Vehicle Performance Envelope, and
Vehicle Power Envelope; Vehicle Power Demand during Driving Cycles.
Design considerations for EV motors an d their cooling system. Application Examples of EV
/HEV motors with vehicles and motor specifications. 08
2. Selection/ Sizing of Battery pack and other Energy Resource:
Selection of type of Battery pack for 2W, 3W and 4W EVs ; Battery pack sizing: Design
considerations: Range per charge, range anxiety, EV motor power requirement; Impact of
road conditions, environmental conditions and traffic conditions.
High -Voltage Cabling and Disconnects, Safety in Battery Design, Testing fo r safety.
Accelerated Reliability Testing of Electric Vehicles, Battery Cycle Life versus Peak Power and
Rest Period.
Selection and sizing of Fuel cell for FCEV, design considerations; Battery -ultra -capacitor hybrid
combination sizing, performance analysis .
Design considerations for Ultra -capacitor based EV, requirement of charging infra.
Flywheel selection and sizing for EV/HEV applications. 12
3. Automotive Subsystem Design:
Electronic Control Unit (ECU) and its Control Features, Communications between ECUs,
Control Software Development: Software -in-the-Loop (SIL) Simulation and Hardware -in-the-
Loop (HIL) Simulation.
Acceleration and braking control, regenerative braking; Automotive Steering Systems. 06

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Design considerations of HVAC controller
4. EV System integration:
EMC design on ECU level, EMC design on system level and in special subsystems, Radiated
emissions and Conducted emissions, EMI EMC measurements. 06
5. Design of Charging Infrastructure:
Design considerations for AC charger: vehicle inter face and charging protocol design.
applicable charging standards
Design of On -Board Charger (OBC) -Schematic, power topology and control, Power
capacities, regenerative braking control.
Design considerations of DC fast charger: vehicle interface and charging pro tocol design.
Connectivity and applicable charging standards
Installation guidelines and grid requirement for charger installations. 12
6. Design with Functional Safety of Automotive Electronics:
Functional Safety requirements of Automotive El ectronics; ASIL identification and safety goal
finalization, ISO 26262.
Energy Storage integrity / protection: rupture and toxic gas management; low energy
stranding, Unintended vehicle movement, shock protection, and Elimination of potential
thermal/ expl osive event.
Hazard and Risk Analysis (HARA) for different situations, Testing of vehicles for compliance
of safety norms 08

Text/Reference Books: -
1. Design and Control of Automotive Propulsion Systems by Zongxuan Sun and Guoming Zhu, CRC Press, 2015
2. Electric Vehicle Machines a nd Drives Design, Analysis and Application by K. T. Chau, IEEE Press, and Wiley, 2015
3. EMC and Functional Safety of Automotive Electronics by Kai Borgeest, IET, 2018

Website Reference / Video Courses:
1. NPTEL Web Course: Electric Vehicles - Part 1 by PROF. AMIT KUMAR JAIN Department of Electrical Engineering
IIT Delhi; https://nptel.ac.in/courses/108/102/108102121/
2. NPTEL Web Course: Fundamentals of Electric vehicles: Technology & Economics , by Prof. Ashok Jhunjhunwala,
Prof. Prabhjot Kaur, Prof. Kaushal Kumar Jha and Prof. L Kannan, IIT Madras,
https://nptel.ac.in/courses/108/106/108106170/
3. NPTEL Web Course: Introduction to Hybrid and Electric Vehicles by Dr. Praveen Kumar and Prof. S. Majhi, IIT
Guwahati, https://nptel.ac. in/courses/108/103/108103009/

Assessment:
Internal Assessment consists of two tests out of which; one should be compulsory class test (on minimum 02
Modules) and the other is either a class test or assignment on live problems or course project

Theory Examination :
1. Question paper will comprise of 6 questions, each carrying 20 marks.
2. Total four questions need to be solved.
3. Q.1 will be compulsory, based on entire syllabus wherein sub questions of 2 to 5 marks will be asked.
4. Remaining question will be rando mly selected from all the modules.

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University of Mumbai




Syllabus

Honours /Minor Degree Program
In
Microgrid Technology




FACULTY OF SCIENCE & TECHNOLOGY
(As per AICTE guidelines with effect from the academic year 2022 -2023)

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University of Mumbai
Microgrid Technology
(With effect from 2022 -23)
Year
&
Sem
Course Code and
Course Title Teaching
Scheme Hours / Week Examination Scheme and Marks Credit
Scheme
Theory Seminar/
Tutorial Pract Internal
Assess
ment End
Sem
Exam Term
Work Oral Total Credits

TE
Sem
V HMTC501:
Futuristic Power
Systems 04 -- -- 20 80 -- -- 100 04
Total 04 - -- 100 - - 100 04
Total Credits = 04

TE
Sem.
VI HMTC601:
Power Electronic
Converters for
Energy Sources 04 -- -- 20 80 -- -- 100 04
Total 04 - - 100 - - 100 04
Total Credits = 04


BE
Sem.
VII HMTC701:
Microgrid Power
and Control
Architecture 04 -- -- 20 80 -- -- 100 04
HMTSBL701:
Microgrid and RES
Lab -- -- 04 -- -- 50 50 100 02
Total 04 - 04 100 50 50 200 06
Total Credits = 06

BE
Sem.
VIII
HMTC801:
Microgrid System
Design 04 - -- 20 80 -- -- 100 04
Total 04 - - 100 - - 100 04
Total Credits = 04

Total Credits for Semesters V,VI, VII &VIII = 04+04+06+04 = 18

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‘Microgrid Technology - SEM -V
Course
Code
Course Name Teaching Scheme (Contact Hours) Credits Assigned
Theory Tutorial Theory Tutorial Total
HMTC501 Futuristic Power Systems 04 - 04 - 04


Course
code

Course Name Examination Scheme
Theory
Term
Work
Total Internal Assessment End
Sem.
Exam Exam
Duration
(Hrs.) Test 1 Test 2 Avg.
HMTC501 Futuristic Power Systems 20 20 20 80 03 - 100

Course
Objectives 1. To explore the state of the art and future trends in power systems .
2. To understand the technical, economic and social challenges in power system e volution .
3. To realize the role and importance of Microgrids if futuristic power systems .
Course
Outcomes Upon successful completion of this cou rse, the learner will be able :
1. To solicit the importance of large scale renewable energy integration with existing grid infrastructure .
2. To underst and the importance and utility of Energy storage systems in futuristic power systems .
3. To explore large scale micro -grid deployment with RES and ESS integration .
4. To understand the role of communication and IT Infrastructure in power system and related
chall enges.
5. To explore the potential of Microgrids and its importance in Indian context.

Module Contents Hours
1. Introduction:
Present status of worldwide scenario of electricity generation, transmission and distribution;
Energy infrastructure -Resilience and Security; Social, Technical and economic challenges;
Major trends driving power system evolution; State of the art technologies in power system. 06
2. Renewable Energy Integration :
Review of renewable energy (RE) resources and systems : Solar - PV, Solar Thermal, Wind,
Biomass , Micro -hydro and Fuel Cell, comparison of various RE resources; Renewable Energy
Policies and present status of integration with existing grid; Large scale integration of
renewable energy -Technical challenges, enabli ng technologies, International requirements;
Renewable energy forecasting 12
3. Energy Storage Systems (ESS):
Review of energy storage compo nents: Battery, VRB, Ultra -capacitor, Fuel Cells, Pumped
Hydro -Storage and flywheels, comparison of ESS technologies; Importance of ESS in futuristic
power systems; Aggregated ESS, Distributed ESS; Applications of ESS: Energy Management
(Load Leveling and Peak Shifting), Fluctuation Suppression (Intermittency Mitigation),
Uninterruptible Power System Low -Voltage Ride Through; Placement of the ESS to Improve
Power Quality, Voltage Regulation Using ESS, ESS as Spinning Reserve. 12
4. Micro -grid and Smart -grid
Micro-grid evolution : Micro -grid c oncept, impo rtance in futuristic power system, basic
architectures and control , objectives and state of the art technologies; Microgrid as a building
block of Smart -grid; Smart -grid concept, Smart Grid versus conventional electrical networks,
Smart -grid infrastructure, Smart Grid communication system and its cyber security,
International standard IEC 61850 and its application to Smart -grid; 12

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Microgrids /smart grid and Electric Vehicles integration. Technical, Economic, Envi ronmental
and Social Benefits of Microgrid Operation.
5. Communication and IT infrastructure:
Requirements of Communication and IT infrastructure in futuristic power systems: various
communication protocols , comparison of performance; IEEE standard: IEEE 802.11 Mesh
Networking, IEEE 802.15.4 -Wireless Sensor Networks ; Communicatio ns Technologies for
Smart m etering ; Cyber security issues and mitigation techniques. 05
6. Microgrids in India:
Microgrids for Rural Electrification, Review of Microgrid Best P ractices through Case Studies:
Strategic Planning, Operations: Commercial and Financial Considerations; Technical and Social
Context. 05

Text Books: -
1. Microgrids Architectures and Control Edited by Nikos Hatziargyriou, IEEE and Wiley, 2014
2. Energy Storage for Sustainable Microgrid by David Wenzhong Gao, Elsevier, 2015
3. Introduction to the Smart Grid - Concepts, Technologies and Evolution by Salman K. Salman, IET, 2017
4. Energy Storage Systems and Components by Alfred Rufer, CRC Press, 2018
Refere nce Books: -
1. Energy Efficie ncy a nd Renewable Energy Handbook Edited by D. Yogi Goswami and Frank Kreith, 2nd Edition -
2016, CRC
2. Clean Energy Microgrids, Edited by Shin'ya Obara and Jorge Morel IET, 2017
3. Hybrid -Renewable Energy Systems in Microgrids - Integration, Developments and Control edited by Hina
Fathimaby et al ., Elsevier WoodHead Publishing, 2018
4. Smart Microgrids: Lessons from Campus Microgrid Design and Implementation edited by Hassan Farhangi, CR C
Press 2017
Website Reference / Video Courses:
1. NPTEL Web Course on: DC Microgrid And Control System Prof. Avik Bhattacharya, IIT Roorkee
2. NPTEL Web Course on Electronics and Distributed Generation Dr. Vinod John Department of Electrical
Engineering IISc Ba ngalore
3. NPTEL Web Course on Introduction to Smart Grid, PROF. N.P. PADHY Department of Electrical Engineering IIT
Roorkee PROF. PREMALATA JENA Department of Electrical Engineering
4. NPTEL Web Course on Electric vehicles and Renewable energy, Prof. Ashok Jhun jhunwala, Prof. Prabhjot Kaur ,
Prof. Kaushal Kumar Jha and Prof. L Kannan, IIT Madras

Assessment:
Internal Assessment consists of two tests out of which; one should be compulsory class test (on minimum 02
Modules) and the other is either a class test or assignment on live problems or course project

Theory Examination :
1. Question paper will comprise of 6 questions, each carrying 20 marks.
2. Total four questions need to be solved.
3. Q.1 will be compulsory, based on entire syllabus wherein sub questions of 2 to 5 marks will be asked.
4. Remaining question will be randomly selected from all the modules.


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‘Microgrid Technology - SEM -VI
Course
Code
Course Name Teaching Scheme (Contact
Hours) Credits Assigned
Theory Tutorial Theory Tutorial Total
HMTC601 Power Electronic Converters
for Energy Sources 04 - 04 - 04


Course
code

Course Name Examination Scheme
Theory
Term
Work
Total Internal Assessment End
Sem.
Exam Exam
Duration
(Hrs.) Test 1 Test 2 Avg.
HMTC601 Power Electronic Converters
for Energy Sources 20 20 20 80 03 - 100

Course
Objectives 1. To illustrate the design philosophies used in the domain of microgrid p ower converters .
2. To explore the control implementations in power converters for voltage, current and power
regulation for various DC and AC energy sources
Course
Outcomes Upon successful completion of this course, the learner will be able to:
1. Select and size various passive and active components for power converters
2. Design power converters used with DC energy resources wi th their control implementation
3. Design power converters used with AC energy resources with their control implementation
4. Understand the design considerations of power conditioning unit for ESS, SPV and Wind applications.
5. Understand t he design and selection aspects of various auxiliary systems and components used in
PCUs

Module Contents Hours
1. Selection of components for Power Electronics Converter s (PEC) :
Selection and Sizing of capacitors and magnetic components for PECs, design of Magnetic
Components; Selection and sizing of Power Devices, Commonly used software tools for
selection and sizing; Heatsink - selection and sizing. 06
2. Design and Control of DC -DC C onverters :
Design of Buck and Boost converter s, Design examples; Design of Bidirectional Converters.
Design of gate driver circuits; Review of DC -DC converter modelling; Closed loop PI controller
design for buck and boost converters; Current control mode and voltage control mode. 10
3. Design and C ontrol of DC -AC converters :
Design of Inverter for standalone application s; Design of grid connected Inverter with
different grid synchronization strategies - ZCD, PLL; Strategies for Control of voltage, current
and power output. 10
4. Design of PCU for SPV and Wind A pplication :
Various topologies of Power Converter Unit (PCU) for SPV and Wind energy systems. Design
considerations of PCU for SPV and Wind energy Systems and Design Examples. 10
5. Design of PCU for ESS A pplications :
Design consideration for BDC convert er based PCU for batteries and Ultra -capacitors. 08
6. Design of Auxiliary System and Interfaces : 08

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Design of current and voltage sensor interfaces; Design considerations for auxiliary power
supplies; Design of protection and snubber components: Introduction t o Digital Signal
Processors (DSP) and microcontroller interfaces

Text Books: -
1. Microgrids Design and Implementation edited by A ntonio Carlos Zambroni de Souza and Miguel Castilla,
Springer, 2019
2. Power Elect ronic Converters for Microgrids by Suleiman M. Sharkh, Mohammad A. Abusara, Georgios I.
Orfanoudakis Babar Hussain, IEEE and Wiley, 2014
3. Microgr ids Architectures a nd Control Edited by Nikos Hatziargyriou, IEEE and Wiley, 2014
4. Energy Storage for Sustainable Microgrid by David Wenzhong Ga o, Elsevier, 2015
5. Control Circuits In Power Electronics Practical Issues In Design And Implementation Edited by Miguel Castilla,
IET, 2016
6. Control and Dynamics in Power Systems and Microgrids by Lingling Fan, CRC Press, 2017
7. Integrated Power Electronic Con verters and Digital Control, by Ali Emadi, Alireza Khaligh, Zhong Nie, and Young
Joo, Lee 2009, CRC Press.

Reference Books: -
1. Cooperative Synchronization in Distributed Microgrid Control by Ali Bidram, Vahidreza Nasirian Ali Davoudi,
and Frank L. Lewis, Sp ringer, 2017
2. Hybrid -Renewable Energy Systems in Microgrids - Integration, Dev elopments and Control edited by Hina
Fathimaby et al., Elseiver WoodHead Publishing, 2018
3. Smart Microgrids - Lessons from Campus Microgrid Design and Implementation edited by Hassan Farhangi, CRC
Press 2017
4. Energy Storage Systems and Components by Alfred Rufer, CRC Press, 2018

Assessment:
Internal Assessment consists of two tests out of which; one should be compulsory class test (on minimum 02
Modules) and the other is either a class test or assignment on live problems or course project

Theory Examination :
1. Question paper will comprise of 6 questions, each carrying 20 marks.
2. Total four questions need to be solved.
3. Q.1 will be compulsory, based on entire syllabus wherein sub questions of 2 to 5 marks will be asked.
4. Remaining question will be randomly selected from all the modules.

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‘Microgrid Technology - SEM -VII
Course
Code
Course Name Teaching Scheme
(Contact Hours) Credits Assigned
Theory Tutorial Theory Tutorial Total
HMTC701 Microgrid Power and Control
Architecture 04 - 04 - 04


Course
code

Course Name Examination Scheme
Theory
Term
Work
Total Internal Assessment End
Sem.
Exam Exam
Duration
(Hrs.) Test 1 Test 2 Avg.
HMTC701 Microgrid Power and Control
Architecture 20 20 20 80 03 - 100

Course
Objectives 1. To study various power and control architectures adopted in DC and AC Microgrids.
2. To explore various control strategies used in power control
3. To take insight into operations stability and protection issues related to Microgrids
Course
Outcomes Upon successful completion of this course, the learner will be able to:
1. Understand various types Microgrids based on applications, power and control architecture.
2. Illustrate various power control strategies adopted in DC, AC and Hybrid Microgrids
3. Compare and contrast various control architectures used DC, AC and Hybrid Microgrids
4. Illustrate the various operational challenges in Microgrids
5. Comprehend the various aspects related to the stability in Microgrids
6. Understand the protection challenges in Microgrids along with various protection methods to
overcome these challenges,

Module Contents Hours
1. Microgrid Power Architecture:
Types of Microgrid system, AC and DC and Hybrids Microgrids, Application based Suitability
of Microgrid type; Review of power architecture of various Microgrids deployed world -wide.
Comparison of various Microgrid power architectures. 08
2. AC Microgrid and Control Architecture :
Black -start operation, Grid Synchronisation - various Grid synchronization methods, Grid
forming and grid following operations; Power Control - Real and reactive power control in AC
Microgrid, simple droop control and other variants of droop control, Unit Power Flow
Control, Feeder power flow control and Mixed mode control, source optimization;
Centralized, decentralised, distributed and hierarchical control architecture, Local and
system / supervisory level control st rategies, Multi Agent System (MAS) Based Control ;
Control approaches used in AC M icrogrids deployed worldwide . Microgrid standards IEEE
1547 series. Communication in AC Microgrids 12
3. DC Microgrid and Control Architecture:
Power sharing in DC Microgrids, source optimization; Control approaches: Centralized,
decentralised, distributed and hierarchical control architecture. Control approaches used in
hybrid Microgrids. Communication in DC/Hybrid Microgrids 08

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4. Operational Control in Microgrids:
Energy management in Microgrids, coordinated control, load management, grid
synchronisation and islanding, Anti -islanding schemes; Various Architectural and
Operational Challenges in Microgrid , Optimal operation of Microgrids. 08
5. Microgrid Stability
Steady -state an d dynamic stability in AC and DC Micr ogrids , Methods to improve the stability
in Microgrids; introduction to small signal and large signal stability analysis in Microgrids. 06
6. Protection in Microgrids
Fault scenarios in DC and AC Microgrids, Protection in DC and AC Microgrids, adaptive
protection, Fault current source (FCS) based protection; Protection challenges in islanded and
autonomous modes of operation and ways to mitigate. 10

Text/Reference Books: -
1. Microgrids Design and Implementation edited by Anton io Carlos Zambroni de Souza and Miguel Castilla,
Springer, 2019
2. Microgrids Architectures a nd Control Edited by Nikos Hatziargyriou, IEEE and Wiley, 2014
3. Cooperative Synchronization in Distributed Microgrid Control by Ali Bidram, Vahidreza Nasirian Ali Davoudi,
and Frank L. Lewis, Springer, 2017
4. Control Circuits In Power Electronics Practical Issues In Design And Implementation Edited by Miguel Castilla,
IET, 2016
5. Control and Dynamics in Power Syste ms and Microgrids by Lingling Fan, CRC Press, 2017
6. Hybrid -Renewable Energy Systems in Microgrids - Integration, Deve lopments and Control edited by Hina
Fathimaby et al., Elseiver WoodHead Publishing, 2018
7. Urban DC Microgrid Intelligent Control and Power Flo w Opti mization by Manuela Sechilariu a nd Fabrice
Locment, 2016 Elsevier
8. Integrated Power Electronic Converters and Digital Control, by Ali Emadi, Alireza Khaligh, Zhong Nie, and
Young Joo, Lee 2009, CRC Press.
9. Island Power Systems by Lukas Sigrist, Enrique Lobato, Francisco M. Echavarren Ignacio Egido, and Luis
Rouco, CRC Press, 2016
Website Reference / Video Courses:
1. NPTEL Web Course on: DC Microgrid a nd Control System Prof. Avik Bhattacharya, IIT Roorkee
2. NPTEL Web Course on Electronics and Distributed Generation Dr. Vinod John Department of Electrical
Engineering IISc Bangalore
3. NPTEL Web Course on Introduction to Smart Grid, PROF. N.P. PADHY Department of Electrical Engineering
IIT Roorkee PROF. PREMALATA JENA Department of Electrical Engineering
4. NPTEL Web Course on Electric vehicles and Renewable energy, Prof. Ashok Jhunjhunwala, Prof. Prabhjot
Kaur , Prof. Kaushal Kumar Jha and Prof. L Kannan, IIT Madras

Assessment:
Internal Assessment consists of two tests out of which; one should be compulsory class test (on minimum 02
Modules) and the other is either a class test or assignment on live problems or course project

Theory Examination :
1. Question paper will comprise of 6 questions, each carrying 20 marks.
2. Total four questions need to be solved.
3. Q.1 will be compulsory, based on entire syllabus wherein sub questions of 2 to 5 marks will be asked.
4. Remaining question will be randomly selected from all the modules.

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Microgrid Technology - SEM -VII
Course Code
Course Name Teaching Scheme (Contact Hours) Credits Assigned
Theory Practical Theory Practical Total
HMTSBL701 Microgrid and RES Lab -- 04 -- 02 02


Course
code

Course Name Examination Scheme
Theory
Term
Work
Oral
Total Internal Assessment End
Sem.
Exam Exam
Duration
(Hrs.) Test 1 Test 2 Avg
.
HMTSBL701 Microgrid and RES Lab -- -- -- -- -- 50 50 100

Course
Objectives 1. To provide hands -on with power converters used in AC, DC Microgrids
2. To explore various control implementation incorporated in Microgrids in simulation or with
hardware
3. To study various auxiliary systems commonly used in Microgrids.
Course
Outcomes Upon successful completion of this course, the learner will be able to:
1. Test the various power converters used AC, DC Microgrids
2. Illustrate various operational modes of power converters
3. Illustrate various operational modes of Microgrid.
4. Describe the working of various auxiliary system interfaces (communication / sensors)
5. Analyse the steady -state and transient behaviour of Microgrid
6. Demonstrate the design the Microgrid and its sub -systems.

Contents
Microgrid / RES Lab : Experimental Setups (Any Five of the following)
1. Testing of Power Conversion Unit for DC Microgrid
2. Testing of Power Conversion Unit for AC Microgrid
3. DC Microgrid: Power Sharing between the sources
4. AC Microgrid: Power Sharing between the sources
5. Grid Connected Inverter
6. Grid Forming Inverter
7. Grid Interactive Inverter
8. Solar MPPT Control
9. Islanding detec tion
10. Island mode of operation of DC or AC Microgrid
11. Data transfer through Microgrid Communication Interfaces
12. Standalone Microgrid operation
13. Voltage and current sensing circuits
14. DSP / Microcontroller interface circuits
15. DSP / Microcontroller programming for converter control.
(or any other experiment s based on Microgrid related systems/ subsystems )

Use of software tools: (Any three of the following)
Use of tools like MATLAB, Scilab, PSIM , LTSPice, python, C, Java platforms etc. for the following

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1. Simulation/ Emulation of DC Microgrid with steady state performance analysis.
2. Simulation/ Emulation of AC Microgrid with steady state performance analysis.
3. Simulation/ Emulation of DC Microgrid ith transient performance analysis.
4. Simulation/ Emulation of A C Microgrid with transient performance analysis.
5. Microgrid Stability analysis with study of impact of ESS on stability
(or any other simulation s based on Microgrid related systems / subsystems )
Plant Visit:
Visit to existing Microgrid facility or a Solar PV/ Wind Installation or a power converters manufacturing / research
facility.
Course Project
Course project to be carried out to design /fabricate/ program one of the PCU used in Microgrid.

Note: Students and teachers are encouraged to use the virtual labs whose links are as given below . The remote -access
to Labs in various disciplines of Science and Engineering is available. Students can conduct online experiments which
would help them in learning basic and advanced concepts through remote experimentat ion.

Virtual Lab Website Reference
1. http://vlab.co.in/broad -area -electrical -engineering
2. https://www.vlab.co.in/broad -area -mechanical -engineering - Energy Storage Labs, Solar Energy lab, Wind
Energy Lab

Term work:
Term work shall consist of minimum eight experiments , at least one plant visit, and one course project . The
distribution of marks shall be as follows:
Journal / Experiment s Performance : 25 marks
Attendance : 05 marks
Plant Visit report : 10 marks
Course Project report : 10 Marks
The final certification and acceptance of term work ensures the minimum passing in the term work.

Oral Examination:
Oral examination will be based on entire lab work of HCMTSBL701 -Microgrid and RES Lab

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264
‘Microgrid Technology - SEM -VIII
Course
Code
Course Name Teaching Scheme (Contact Hours) Credits Assigned
Theory Tutorial Theory Tutorial Total
HMTC801 Microgrid System Design 04 - 04 - 04


Course
code

Course Name Examination Scheme
Theory
Term
Work
Total Internal Assessment End
Sem.
Exam Exam
Duration
(Hrs.) Test 1 Test 2 Avg.
HMT C801 Microgrid System Design 20 20 20 80 03 - 100

Course
Objectives 1. To illustrate the design philosophies used in the domain of Microgrid.
2. To explore the selection of power and control architecture of Microgrids
3. To study the design aspects of AC Microgrid, DC Microgrid and their auxiliary systems
Course
Outcomes Upon successful completion of this course, the learner will be able to:
1. Select and size various Microgrid energy resources
2. Select the power and control architecture of the Microgrid
3. Select and design the Microgrid’s communication architecture.
4. Illustrate the design aspects DC Microgrids with their control strategies.
5. Illustra te the design aspects AC Microgrids with their control strategies.
6. Illustrate the implementation of the Microgrid islanding detection and anti -islanding scheme/
blackstart operation

Module Contents Hours
1. Selection/ Sizing of Microgrid Energy Resources
Factors affecting the selection and sizing of energy resources for Microgrid applications,
dependency on type of loads connected, Selection/ Sizing: Renewable energy
resources, Energy Storage components. Hybrid combination of RES and ESS.

07
2. Selection of Power and Control Architecture:
Factors affecting the selection of Microgrid power and control architecture; Design
Consideration for control implementation; Sensors: Selection of sensors and design of
sensor Interfaces, design of control Interfaces. D esign considerations for DSP/
Microcontroller interfaces

07
3. Selection and Design of Communication Architecture
Design considerations for selection of communication network for Microgrid
applications; Design and implementation of communication links/ interfaces.
Microg4controller programming for Data transfer on communication network. Practical
design considerations for Communication networks.

08
4. Design of DC Microgrid
Design DC Power Conditioning Units for RES and ESS , Unidirectional and Bidirectional
Converter design, implementation of Control loop with DSP; Programming for Power
sharing and Energy Management algorithms; Design of Protection system for DC
Microgrid

12

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5. Design of AC Microgrid
Design AC Power Conditioning Units for RES and ESS , Unidirectional and Bidirectional
Converter design, implementation of Control loop with DSP; Grid Synchronization.
Programming for Power sharing and Energy Management algorithms; Design of
Protection system for AC Microg rid.

12
6. Islanding in Microgrids
Selection and implementation of Islanding detection and anti-islanding scheme; Black -
start and Autonomous operations in Microgrids;
06

Text Books: -
1. Microgrids Design and Implementation edited by Antonio Carlos Zambroni de Souza and Miguel Castilla,
Springer, 2019
2. Microgrids Architectures and Control Edited by Nikos Hatziargyriou, IEEE and Wiley, 2014
3. Power Electronic Converters For Microgrids by Suleiman M. Sharkh, Mohammad A. Abusara, Georgios I.
Orfanoudakis B abar Hussain, IEEE and Wiley, 2014
Reference Books: -
1. Energy Storage for Sustainable Microgrid by David Wenzhong Gao, Elsevier, 2015
2. Cooperative Synchronization in Distributed Microgrid Control by Ali Bidram, Vahidreza Nasirian Ali Davoudi,
and Frank L. Lew is, Springer, 2017
3. Energy Efficiency a nd Renewable Energy Handbook Edited by D. Yogi Goswami and Frank Kreith, 2nd Edition -
2016, CRC
4. Control Circuits In Power Electronics Practical Issues In Design And Implementation Edited by Miguel Castilla,
IET, 2016
5. Hybrid-Renewable Energy Systems in Microgrids - Integration, Developments and Control edited by Hina
Fathimaby et al., Elseiver WoodHead Publishing, 2018
6. Urban DC Microgrid Intelligent Control and Power Flow Optimization by Manuela Sechilariu and Fabrice
Locment, 2016 Elsevier
7. Integrated Power Electronic Converters and Digital Control, by Ali Emadi, Alireza Khaligh, Zhong Nie, and
Young Joo, Lee 2009, CRC Press.

Assessment:
Internal Assessment consists of two tests out of which; one should be compulsory c lass test (on minimum 02
Modules) and the other is either a class test or assignment on live problems or course project

Theory Examination :
1. Question paper will comprise of 6 questions, each carrying 20 marks.
2. Total four questions need to be solved.
3. Q.1 will be compulsory, based on entire syllabus wherein sub questions of 2 to 5 marks will be asked.
4. Remaining question will be randomly selected from all the modules.

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University of Mumbai




Syllabus

Honours /Minor Degree Program
In
Robotics




FACULTY OF SCIENCE & TECHNOLOGY

(As per AICTE guidelines with effect from the academic year 2022 -2023)


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University of Mumbai
Robotics
(With effect from 2022 -23)

Year
&
Sem
Course Code
and Course
Title Teaching
Scheme Hours / Week Examination Scheme and Marks Credit
Scheme

Theor
y Seminar
/Tutoria l
Pract Internal
Assess
ment End
Sem
Exa
m
Term
Work
Oral
Total
Credits

TE
Sem
V HRBC501:
Industrial
Robotics
04
--
--
20
80
--
--
100
04
Total 04 - -- 100 - - 100 04
Tota l Credits = 04

TE
Sem
VI HRB C601:
Mechatronics
&IoT
04
--
--
20
80
--
--
100
04
Total 04 - - 100 - - 100 04
Total Credits = 04


BE
Sem
VII HRB C701:
Artificial
Intelligence &
Data Analysis
04
--
--
20
80
--
--
100
04
HRBSBL701:
Robotics and
Automation Lab -- -- 04 -- -- 50 50 100 02
Total 04 - 04 100 50 50 200 06
Total Credits = 06

BE
Sem
VIII HRB C801:
Autonomous
Vehicle
04
-
--
20
80
--
--
100
04
Total 04 - - 100 - - 100 04
Total Credits = 04

Total Credits for Semesters V,VI, VII &VIII = 04+04+06+04 = 18

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Robotics - SEM -VI
Course Code Course Name Credits
HRBC501 Industrial Robotics 4

Course Objectives:
1. To acquaint with significance of robotic system in agile and automated manufacturing processes.
2. To make conversant with robotic elements/ peripherals, their selection and interface with
manufacturing equipment’s.
3. To study the basics of robot kinematics
Course Outcomes: Upon successful completion the course, learner will be able to

1. Acquire skills in understanding robot language and programming.
2. Acquire skill in robot task planning for problem solving.
3. Develop skills in understanding various sensors, robot peripherals and their use &
deployment in manufacturing system.
4. Develop skills in identifying areas in manufacturing where robotics can be deployed for
enhancing productivity.

Module Details Hours
1
. Introduction Automation, robotics, Robotic system & Anatomy, Classification and Future
Prospects 2
2
. Drives Control Loops, Basic Control System Concepts & Models, Control System Analysis,
Robot Activation & Feedback Components, Position & Velocity Sensors, Actuators and
Power Transmission system.
Robot & its Peripherals
End Effecters: Type mechanical and other grippers, Tool as end effecter.
Sensors: Sensors in Robotics, Tactile Sensors, Proximity & Range Sensors, Sensor Based
Systems, Vision systems and Equipment 10
3
. Machine vision Introduction, Low level & High level Vision, Sensing & Digitizing, Image
Processing & analysis, Segmentation, Edge detection, Object Description & recognition,
interpretation and Applications.
Programming for Robots Method, Robot Programme as a path in space, Motion
interpolation, motion & task level Languages, Robot languages, Programming in suitable
languages a nd characteristics of robot. 10
4
. Robot Kinematics Forward, reverse & Homogeneous Transformations, Manipulator
Path control and Robot Dynamics.
Introduction to wheeled and legged robots including humanoids 10
5
. Robot Intelligence & Task Planning Introduction, State space search, Problem
reduction, use of predictive logic, Means. Ends
Analysis, Problem solving, Robot learning and Robot task planning. 10

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6
. Robot application in manufacturing Material transfer, machine loading & un
loading, processing operation, Assembly & inspectors, robotic Cell design & control,
Social issues & Economics of Robotics. 10

Assessment :

Internal Assessment for 20 marks:
Consisting Two Compulsory Class Tests
First test based on approximately 40% of contents and second test based on remaining contents
(approximately 40% but excluding contents covered in Test I)

End Semester Examination:
1. Weightage of each module in end semester examination will be proportional to the number of
respective lecture hours mentioned in the curriculum.
2. Question paper will comprise of total six questions, each carrying 20 marks
3. Question 1 will be compulsory and should cover maximum contents of the curriculum
4. Remaining questions will be mixed in nature (for example if Q.2 has part (a) from module 3 then
part (b) will be from any module other than module 3)
5. Only four questions need to be solved

Text/References
1. Industrial Robotics, Technology, Programming & Applications, Grover, Weiss, Nagel, Ordey, Mc Graw
Hill.
2. Robotics: Control, Sensing, Vision & Intelligence, Fu, Gonzalex, Lee, Mc Graw Hill.
3. Robotic technology & Flexible Automation, S R Deb. TMH.
4. Robotics for Engineers, Yoram Koren , Mc Graw hill.
5. Fundamentals of Robotics, Larry Health.
6. Robot Analysis & Control, H Asada, JJE Slotine.
7. Robot Technology, Ed. A Pugh, Peter Peregrinus Ltd. IEE, UK. 8. Handbook of Industrial Robotics, Ed.
Shimon. John Wiley
8. Roland Siegwart, Illah Reza Nourbakhsh, and Davide Scaramuzza, “Introduction to Autonomous Mobile
Robots”, Bradford Company Scituate, USA

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Course Objectives:
1. To associate a mechatronic System with IOT
2. To relate data analytics with IOT
3. To understand Cloud Computing in IOT

Course Outcomes: Upon successful completion of this course, the learner will be able to

1. Describe a Mechatronic System
2. Demonstrate the use of a Micro -controller
3. Understand an IOT System
4. Identify Wireless Technologies Supporting IOT
5. Use Data Analytics in conjunction with IOT &Cloud

Module Details Hours
1. Introduction to Mechatronics: Traditional and Mechatronics Design, Mechatronics Key
Elements, Basic Components of Mechatronic Systems , Integrated Design issues in
Mechatronics, Mechatronics Design Process, Mechatronics System in Factory, Home and
Business Applications, Objectives, Advantages and Disadvantages of Mechatronics 6
2. Overview of Micro -processor ad Micro -controller: 8051 Micro -controllers, Functional Block
Diagram and Architecture, Instruction set and Assembly Language Programming, Analog
and Data Acquisition , Digital I/O interfacing, Special Function interfacing, Signal
Conditioning, Special Utility Support hardware Interfacing of HEX – Keyboards, LCD Display,
ADC, DAC and Stepper Motor with 8051 Micro -controller 10
3. Introduction and application to Internet of Things: Need of IoT, history of IOT, Objects of
IOT, Level of IOT, Technologies in IOT, Introduction to Arduino and Raspberry Pi,
understanding its components, recognizing the Input/Output, GPIO Connectivity 10
4. Wireless Technologies Supporting IoT: Protocol Standardization for IoT, Machine to
machine (M2M) and WSN protocols, Basics of RFID , RFID Protocols, Issues with IOT
Saudization, Protocols – IEEE 802.15.4, Zigbee, IPv6 Technologies for IOT
10
5. Data Analytics for IOT: Introduction Apache Hadoop, Using Hadoop MapReduce for Batch
Data Analysis, Apache Oozie, Apache Spark, Apache Storm, Using Apache Storm for Real
Tie Data Analysis, Structural Health Monitoring, Case Study: Chef Case Study, puppet Case
Study 10
6. Introduction to Cloud Computing, Differenc e between Cloud Computing and FOG
Computing: The Next Evolution of Cloud Computing, Role of Cloud Computing in IOT,
Connecting IoT to Cloud, Cloud Storage for IoT Challenge in Integration of IoT with Cloud 8 Robotics - SEM -VI
Course Code Course Name Credits
HRBC601 Mechatronics & IoT 4

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Assessment :
Internal Assessment for 20 marks:
Consisting Two Compulsory Class Tests
First test based on approximately 40% of contents and second test based on remaining contents
(approximately 40% but excluding contents covered in Test I)
End Semester Examination:
1. Weightage of each module in end semester examination will be proportional to the number of
respective lecture hours mentioned in the curriculum.
2. Question paper will comprise of total six questions, each carrying 20 marks
3. Question 1 will be compulsory and should cover maximum contents of the curriculum
4. Remaining questions will be mixed in nature (for example if Q.2 has part (a) from module 3 then
part (b) will be from any module other than module 3)
5. Only four questions need to be solved

Text/Reference Books:
1. Bolton, William. Mechatronics: electronic control systems in mechanical and electrical engineering.
Pearson Education, 2003.
2. De Silva, Clarence W. Mechatronics: an integrated approach. CRC press, 2004.
3. Ayala, Kenneth J. The 8051 microcontrollers. Thomson Delmar Learning, 2005.
4. Zhang, Dan, and Bin Wei, eds. Mechatronics and Robotics Engineering for Advanced and Intelligent
Manufacturing. Springer International Publishing, 2017.
5. Greengard, Samuel. The internet of things. MIT press, 2021.
6. Chaouchi, Hakima, ed. The internet of things: Connecting objects to the web. John Wiley & Sons,
2013.
7. Hintz, Kenneth, and Daniel Tabak. Microcontrollers: architecture, implementation, and programming.
McGraw -Hill, Inc., 1992.

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Robotics - SEM -VII
Course Code Course Name Credits
HRBC701 Artificial Intelligence and Data Analytics 04
Course Objectives:
1. To gain perspective of AI, its foundations, agent architectures and properties of the environment.
2. To understand the basic principles of AI towards problem solving, inference, perception, knowledge
representation, and learning.
3. To investigate probabilistic reasoning under uncertain and incomplete information.
4. To gain the perspective of the concepts of data Mining, modelling and visualization, data
warehousing.
5. To understand various machine learning algorithms.

Course Outcomes: Upon successfully completion of this course, learner will able to...
1. Demonstrate knowledge of the building blocks of AI, intelligent agents and knowledge presentation
systems.
2. Explain artificial intelligence planning, reasoning, uncertainty handing and expert systems.
3. Describe the concept of data mining, big data, data analytics, business intelligence.
4. Comprehend and implement data mining and machine learning algorithms.

Module Contents Hours.
01 Introduction to Artificial Intelligence (AI): A. I. Representation, Representation of
knowledge, knowledge base systems, state space search, production systems,
problem characteristics, types of production systems, Intelligent Agents and
Environments, nature of environments, structure of agents
Knowledge and Reasoning: Knowledge Representation Systems, Properties of Knowledge
Representation Systems, Propositional Logic (PL), First Order Logic: Syntax and
Semantic, Inference in FOL, Forward v/s Backward Chaining 6
02 Planning: Introduction to Planning, Planning with State Space Search, Partial Ordered
planning, Hierarchical Planning, Conditional Planning, Brief introduction to single layer and
multiplayer networks Reasoning Under Uncertainty: Handling Uncertain Knowledge,
Random Variables, Prior and Posterior Probability, Inference using Full Joint Distribution,
Bayes' Rule and its use, Bayesian Belief Networks, Reasoning in Belief Networks
Introduction to Expert Systems: Components of Expert System: Knowledge base, Inference
engine, user interface, working memory, Development of Expert Systems
10

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03 Introduction to Data Mining: What is Data Mining; Kind of patterns to be mined;
Technologies used; Major issues in Data Mining, associative Rule Mining
Introduction to Big Data: Big Data characteristics, types of Big Data, Traditional vs.
Big Data business approach, Case Studies of Big Data Solutions, Introduction to
parallel Processing (MPP) architecture, Hadoop/HDFS and cloud based
solutions
Introduction to Business Intelligence: Business intelligence (BI): Managers and
Decision Making, BI for Data analysis and Presenting Results
8
04 Data Pre -processing: Notion of data quality. Typical pre -processing operations:
combining values into one, handling incomplete/ incorrect / missing values,
recoding values, sub setting, sorting, transforming scale, determining
percentiles, removing noise, removing inconsistencies, transformations,
standardizing, normalizing - min-max normalization, z-score standardization.
Data Modeling and visualization: Logic driven modeling, data driven modeling,
basic what -if spreadsheet models
Data Warehousing: What is a data warehouse, need for a data warehouse,
architecture, data marts, OLTP vs OLAP 10
05 Machine Learning: Supervised and Unsupervised Learning,
Concepts of Classification, Clustering and prediction
Performance Measures: Measuring Quality of model - Confusion Matrix, Accuracy,
Recall, Precision, Specificity, F1 Score, RMSE 8
06 Classification: Rule based classification, classification by Bayesian Belief
networks, Hidden Markov Models.
Clustering: Hebbian Learning rule, Expectation -Maximization algorithm for
clustering
Dimensionality Reduction: Principal Component Analysis Feature Selection and
Feature Extraction
Time Series Analysis and Forecasting: Time series patterns, forecast accuracy,
moving averages and exponential smoothing 10

Assessment:
Internal Assessment for 20 marks:
Consisting Two Compulsory Class Tests
First test based on approximately 40% of contents and second test based on remaining contents
(approximately 40% but excluding contents covered in Test I)
End Semester Examination:
1. Weightage of each module in end semester examination will be proportional to the number of

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respective lecture hours mentioned in the curriculum.
2. Question paper will comprise of total six questions, each carrying 20 marks
3. Question 1 will be compulsory and should cover maximum contents of the curriculum
4. Remaining questions will be mixed in nature (for example if Q.2 has part (a) from module 3 then
part (b) will be from any module other than module 3)
5. Only four questions need to be solved

Text Books:
1. Stuart J. Russell and Peter Norvig, "Artificial Intelligence A Modern Approach ―Second Edition" Pearson
Education.
2. Elaine Rich and Kevin Knight ―Artificial Intelligenceǁ Third Edition, Tata McGraw -Hill Education Pvt.
Ltd., 2008.
3. George F Luger “Artificial Intelligence” Low Price Edition, Pearson Education, Fourth edition.
4. Deepak Khemani, A first course in Artificial Intelligence, Mc GrawHill
5. P. N. Tan, M. Steinbach, Vipin Kumar, “Introduction to Data Mining”, Pearson Education.
6. G. Shmueli, N.R. Patel, P.C. Bruce, “Data Mining for Business Intelligence: Concepts, Techniques, and
Applications in Microsoft Office Excel with XLMiner”, 2nd Edition, Wiley India.
7. Ethem Alpaydın, “Introduction to Machine Learning”, MIT Press
8. Peter Flach, “Machine Learning”, Cambridge University Press

Reference Books:
1. Tom M. Mitchell, “Machine Learning”, McGraw Hill
2. Kevin P. Murphy, “Machine Learning ― A Probabilistic Perspective”, MIT Press
3. Stephen Marsland, “Machine Learning an Algorithmic Perspective”, CRC Press
4. Shai Shalev -Shwartz, Shai Ben-David, “Understanding Machine Learning”, Cambridge University Press
5. Peter Harrington, “Machine Learning in Action”, DreamTech Press
6. D. W. Patterson, Artificial Intelligence and Expert Systems, Prentice Hall.
7. Saroj Kaushik “Artificial Intelligence”, Cengage Learning.

Links for online NPTEL/SWAYAM courses:
https://onlinecourses.nptel.ac.in/noc19_me71/preview https://onlinecourses.nptel.ac.in/noc22_cs56/preview
https://onlinecourses.nptel.ac.in/noc22_cs29/preview https://onlinecourses.nptel.ac.in/noc22_cs08/preview

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Robotics - SEM -VII
Course Code Course Name Credits
HRBSBL701 Robotics and Automation Lab 2

Course Objectives:
1. To learn the implementation of image processing algorithms.
2. To acquaint with programming of robots.
3. To acquaint with data acquisition over cloud environment
4. To demonstrate the working of machine learning algorithms for data prediction.

Course Outcomes: learner will able to...
1. Develop simple image processing algorithms.
2. Program robots for simple and inverse kinematics and trajectory planning.
3. Acquire sensor data over cloud using microcontroller.
4. Perform predictive data analysis using clustering, classification and regression models.
List of Experiments:
1. Edge detection / segmentation using image processing
2. programming the robots to solve direct and inverse kinematics problems
3. Trajectory planning for Robots
4. Acquisition of sensor data over cloud using microcontroller
5. Implementation of Clustering algorithm (K-means / K-medoids)
6. Data Classification using data prediction tool (classification tree / artificial neural networks, Support
Vector Machines etc.) (Any One)
7. Linear Regression using data predictive tool (multiple regression / artificial neural networks etc.)
(Any One)
8. PLC to operate actuators for automation application

Assessment:
Term Work
Term work shall consist of the experiments as mentioned above. The distribution of marks for term work shall
be as follows:
1. Laboratory work (Experiments): 40 marks
2. Attendance: 10 marks

Oral Examination:
Oral examination will be based on entire lab work of Robotics and Automation Lab

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Robotics - SEM -VIII
Course Code Course Name Credits
HRBC801 Autonomous Vehicle Systems 4
Course Objectives:
1. To comprehend fundamental aspects of Autonomous Vehicles.
2. To Acquire knowledge of levels of automation of autonomous systems.
3. To Understand the Connectivity Aspects of autonomous automobiles

Course Outcomes: The student will be able to
1. Gain perspective of autonomous systems
2. Understand Automotive Electronics and the operation of ECUs.
3. Discuss about the use of computer vision and learning algorithms in vehicles.
4. Learn Localization, Perception, Prediction planning and control.
5. Summarize the aspects of connectivity
6. Understand cloud platform and ROS.

Module Details Hours
1 An over view of autonomous driving technologies : Algorithms, client systems,
cloud Platforms 6
2 Overview of Automotive Electronics : Control Systems for
Autonomous vehicles, Electronic Engine control, Chassis and
Powertrain Electronics, Vehicle motion control, Instrumentation and Telematics &
ADAS 8
3 Sensing Technologies
Radar & Sonar, Camera, Lidar, GNSS.GPS/IMU
Use of Sensor Data, Sensor Fusion and Kalman Filters 8
4 Computer Vision and Deep Learning
Computer Vision Fundamentals -Advanced Computer Vision , Neural Networks for
Image Processing , TensorFlow ,Convolutional Neural Networks 10
5 Levels of Automation
Localization - GNSS, LiDAR, Wheel and Visual Odometry, sensor fusion Perception –
Detection and Tracking, DrivingPerception and deep learning
Prediction and Routing - Trffic prediction and Lane level routing Decision,
Planning and Control - Motion Planning,Feed back control Cloud System -
Operating systems -ROS, Cloud Platforms 12
6 Connected Car Technology:
Connectivity Fundamentals - DSRC (Direct Short Range
Communication), Connectivity types -Vehicle -to-Vehicle, Vehicle -to- Roadside and
Vehicle -to-Infrastructure, Vehicle -to-pedestrian, Vehicle - to-clous, Vehicle -to-
everything, Applications -Security Issues Technical Issues, Security Issues, Moral and
Legal Issues. 8

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Text Books:
1. Shaoshan Liu, Liyun Li, “Creating Autonomous Vehicle Systems”, Morgan and Claypool
Publishers,2017.
2. Liu, Shaoshan. Engineering autonomous vehicles and robots: the DragonFly modular - based
approach. John Wiley & Sons, 2020.
3. Hong Cheng, “Autonomous Intelligent Vehicles: Theory, Algorithms and
Implementation”, Springer,2011.
4. Williams. B. Ribbens: “Understanding Automotive Electronics”, 7th Edition, Elsevier Inc, 2012.
Reference Books:
1. Marcus Maurer, J.Christian Gerdes, “Autonomous Driving: Technical, Legal and Social
Aspects”Springer, 2016.
2. Ronald.K.Jurgen, “Autonomous Vehicles for Safer Driving”, SAE International, 2013.
3. James Anderson, KalraNidhi, Karlyn Stanly, “Autonomous Vehicle Technology: A Guide
forPolicymakers”, Rand Co, 2014.
4. Lawrence. D. Burns, Chrostopher Shulgan, “Autonomy – The quest to build the driverless car
andhow it will reshape our world”, Harper Collins Publishers, 2018

Assessment:
Internal Assessment consists of two tests out of which; one should be compulsory class test (on
minimum 02 Modules) and the other is either a class test or assignment on l ive problems or course
project

Theory Examination :
1. Question paper will comprise of 6 questions, each carrying 20 marks.
2. Total four questions need to be solved.
3. Q.1 will be compulsory, based on entire syllabus wherein sub questions of 2 to 5 marks will
be asked.
4. Remaining question will be randomly selected from all the modules.


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University of Mumbai




Syllabus

Honours /Minor Degree Program
In
3D Printing




FACULTY OF SCIENCE & TECHNOLOGY
(As per AICTE guidelines with effect from the academic year 2022 -2023)





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University of Mumbai
3D Printing
(With effect from 2022 -23)

Year &
Sem
Course Code
and Course
Title Teaching
Scheme Hours / Week Examination Scheme and Marks Credit
Scheme

Theory Seminar/
Tutorial
Pract Internal
Assess
ment End
Sem
Exam Term
Work Oral
Total
Credits

TE
Sem V H3DP C501:
Introduction to
CAD
04
--
--
20
80
--
--
100
04
Total 04 - -- 100 - - 100 04
Total Credits = 04


TE
Sem. VI H3DPC601:
3D Printing:
Introduction &
Processes
04
--
--
20
80
--
--
100
04
Total 04 - - 100 - - 100 04
Total Credits = 04


BE
Sem. VII H3DPC701:
Applications of
3D Printing
04
--
--
20
80
--
--
100
04
H3DPSBL7 01:
Skill Based Lab
– Digital
Fabrication
--
--
04
--
--
50
50
100
02
Total 04 - 04 100 50 50 200 06
Total Credits = 06


BE
Sem. VIII H3DPC801:
3D Printing in
Medical
Technology
04
-
--
20
80
--
--
100
04
Total 04 - - 100 - - 100 04
Total Credits = 04

Total Credits for Semesters V, VI, VII &VIII = 04+04+04+06 = 18

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‘3D Printing’ :SEM -V
Course
Code Course Name Teaching Scheme (Contact Hours) Credits Assigned
Theory Tutorial Theory Tutorial Total
H3DPC501 Introduction to CAD 04 - 04 - 04


Course
code

Course Name Examination Scheme
Theory
Term
Work
Total Internal Assessment End
Sem.
Exam Exam
Duration
(Hrs.) Test 1 Test 2 Avg.
H3DPC501 Introduction to CAD 20 20 20 80 03 - 100


Course
Objectives 1. To impart the 3D modelling skills for development of 3D models of basic engineering
components.
2. To familiarize with basic concepts of computer graphics.
3. To familiarize with basic concepts of additive and subtractive manufacturing process.


Course
Outcomes Upon successful completion of this course, the learner will be able:
1. Illustrate basic understanding of design.
2. Create the CAM Toolpath for specific given operations.
3. Illustrate basic understanding of types of CAD model creation.
4. Generate assembly models of given objects using assembly tools of a modelling software.
5. Identify suitable computer graphics techniques for 3D modelling.
6. Transform, manipulate objects & store and manage data.

Module Contents Hours
1. Design thinking:
Identification of need, Embodiment of design, Generation of ideas and research topics 5


2. Subtractive Manufacturing:
Introduction to NC/CNC/DNC machines
Additive Manufacturing:
Introduction to 3D Printing, Limitations of Subtractive manufacturing, Digital
fabrication

8

3. CAD Introduction:
History & Scope of CAD, CAD hardware and software, Advantages, Disadvantages and
Applications of CAD
7


4. Introduction to 2D modelling:
CAD models Creation, Types and uses of models from different perspectives
Introduction to assembly drawing:
Types of assembly drawings, part drawings, drawings for catalogues and instruction
manuals, patent drawings, drawing standards

12

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5. Computer Graphics:
Overview of 2D and 3D Computer Graphics, Parametric representation of curves:
Synthetic Curves - Bezier curves, Hermite Curves, B -spline curves
Geometric Modelling:
Wire Frame Modelling, Solid Modelling, Surface Modelling, Parametric Modelling,
Feature based Modelling, Constraint Based Modelling.

12

6. Geometric Transformation:
2D & 3D Transformations (Translation, Rotation, & Scaling & Reflection),
Concatenations
8
Text/Reference Books: -
1. Machine Drawing by N.D. Bhatt.
2. A textbook of Machine Drawing by Laxminarayan and M.L.Mathur, Jain brothers Delhi
3. CAD/ CAM, Theory & Practice, Ibrahim Zeid, R. Sivasubramanian, Tata McGraw Hill
Publications
4. CAD/CAM Principles and Applications, P. N. Rao, Tata McGraw Hill Publications
5. CAD/CAM Computer Aided and Manufacturing, Mikell P. Groover and Emory W. Zimmers, Jr.,
Eastern Economy Edition
6. CNC Technology and Programming, Krar, S., and Gill, A., McGraw Hill Publishers.
7. Medical Modelling The Application of Advanced Design and Rapid Prototyping Techniques in
Medicine, Richard Bibb, Dominic Eggbeer and Abby Paterson, Woodhead Publishing Series in
Biomaterials: Number 91, Elsevier Ltd.
8. Additive Manufacturing Technologies: Rapid Prototyping to Direct Digital Manufacturing, I.
Gibson l D. W. Rosen l B. Stucker, Springer Publication.
Website Reference / Video Courses:
1. https://nptel.ac.in/courses/112/102/112102101/
2. https://npt el.ac.in/courses/106/102/106102065/
3. https://nptel.ac.in/courses/106/102/106102065/
4. https://nptel.ac.in/courses/112/102/112102103/
5. https://nptel.ac.in/courses/112/105/112105211/
6. https://nptel.ac.in/courses/112/104/112104265/
7. https:// www.youtube.com/watch?v=2cCMty9v3Tg
8. https:// www.youtube.com/watch?v=2zPh26Q1BT8
Assessment:
Internal Assessment consists of two tests out of which; one should be compulsory class test (on
minimum 02 Modules) and the other is either a class test or assignment on live problems or course
project
Theory Examination :
1. Question paper will comprise of 6 questions, each carrying 20 marks.
2. Total four questions need to be solved.
3. Q.1 will be compulsory, based on entire syllabus wherein sub questions of 2 to 5 marks will
be asked.
4. Remaining question will be randomly selected from all the modules.

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‘3D Printing’ - SEM -VI

Course
Code
Course Name Teaching Scheme
(Contact Hours)
Credits Assigned
Theory Tutorial Theory Tutorial Total
H3DPC601 3D Printing: Introduction
&
Processes 04 - 04 - 04



Course
code

Course Name Examination Scheme
Theory
Term
Work

Total Internal Assessment End
Sem.
Exam Exam
Duration
(Hrs.) Test 1 Test 2 Avg.
H3DPC601 3D Printing: Introduction
&
Processes 20 20 20 80 03 - 100

Course
Objectives 1. To familiarise with importance of Rapid Prototyping.
2. To study programming aspects of subtractive manufacturing process.
3. To familiarize with basic process of additive manufacturing in particularly 3D printing.




Course
Outcomes Upon successful completion of this course, the learner will be able to:
1. Illustrate understanding of various cost-effective alternatives for manufacturing
products and select the feasible RP process for specific technical applications
2. Build and create data for 3D printing of any given object using liquid based rapid
prototyping and tooling processes
3. Build and create data for 3D printing of any given object using solid based rapid
prototyping and tooling processes
4. Build and create data for 3D printing of any given object using powder based rapid
prototyping and tooling processes
5. Select an appropriate material and tools to develop a given product using rapid
prototyping machine
6. Select proper rapid prototyping and reverse engineering techniques for specific technical
applications.
7. Demonstrate basics of virtual reality

Module Contents Hours


1. Additive Manufacturing:
Introduction to AM, Classification of AM Processes, Advantages & disadvantages, AM
Applications; in Design, Concept Models, Form & fit checking, Functional testing, CAD
data verification, Rapid Tooling, and bio fabrication.

9

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2. Liquid based systems:
Stereo lithography apparatus (SLA): Models and specifications, process, working
principle, photopolymers, photo polymerization, layering technology, laser and laser
scanning, applications, advantages and disadvantages, case studies.
Solid g round curing (SGC): Models and specifications, process, working, principle,
applications, advantages and disadvantages, case studies.


9


3. Solid based systems:
Laminated object manufacturing (LOM): Models and specifications, Process, Working
principle, Applications, Advantages and disadvantages, Case studies.
Fused Deposition Modeling (FDM): Models and specifications, Process, Working
principle, Applications, Advantages and disadvantages, Case studies.

8




4. Powder Based Systems:
Selective laser sintering (SLS): Models and specifications, process, working principle,
applications, advantages and disadvantages, case studies.
Three -dimensional printing (3DP): Models and specification, process, working
principle, applications, advantages and disadvantages, case studies.
Electron Beam Melting (EBM): Models and specification, process, working principle,
applications, advantages and disadvantages, case studies.



8



5. Materials for Additive manufacturing
Types of material: polymers, metals, ceramics and composites, liquid -based materials,
photo polymer development, solid based materials, powder -based materials.
Material properties
Colour, dimensional accuracy, stability, surface finish, machinability, environmental
resistanc e, operational properties.


10


6. Reverse Engineering
Introduction to Digitizing Methods, Contact type and Non -contact type, Brief
introduction to the types of medical imaging.
Virtual reality: Definition, features of VR, Technologies used in VR, Introduction to
Augmented reality

8

Text/Reference Books: -
1. Rapid Prototyping, Principles and Applications by Rafiq I. Noorani, Wiley & Sons
2. Rapid Prototyping: Principles and Applications by Chua C.K, Leong K.F and Lim C.S, 2nd Edition,
World Scientific
3. Rapid Manufacturing – An Industrial revolution for the digital age by N.Hopkinson, R.J. M. Hauge,
P M, Dickens, Wiley

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284
4. Advanced Manufacturing Technology for Medical applications: Reverse Engineering, Software
conversion and Rapid Prototyping by Ian Gibson, Wiley
5. Rapid Prototyping and Manufacturing: Fundamentals of Stereolithography by Paul F. Jacobs,
McGraw Hill
6. Rapid Manufacturing by Pham D T and Dimov S S, Springer Verlog
7. “Rapid Prototyping” Chee Kai Chua, World Scientific Publishing
Website Reference / Video Courses:
NPTEL Web Course:
1. Rapid Manufacturing, By Prof. J. Ramkumar, Prof. Amandeep Singh, IIT Kanpur,
https://onlinecourses.nptel.ac.in/noc20_me50/preview
2. Fundamentals of Additive Manufacturing Technologies, By Prof. Sajan Kapil, IIT Guwahati,
https://onlinecourses.nptel.ac.in/noc21_me115/preview

Assessment:
Internal Assessment consists of two tests out of which; one should be compulsory class test (on
mini mum 02 Modules) and the other is either a class test or assignment on live problems or course
project

Theory Examination :
5. Question paper will comprise of 6 questions, each carrying 20 marks.
6. Total four questions need to be solved.
7. Q.1 will be compulsory, based on entire syllabus wherein sub questions of 2 to 5 marks will
be asked.
8. Remaining question will be randomly selected from all the modules.

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285
‘3D Printing’ - SEM -VII

Course
Code
Course Name Teaching Scheme
(Contact Hours) Credits Assigned
Theory Tutorial Theory Tutorial Total
H3DPC701 Applications of 3D Printing 04 - 04 - 04


Course
code

Course Name Examination Scheme
Theory
Term
Work
Total Internal Assessment End
Sem.
Exam Exam
Duration
(Hrs.) Test 1 Test 2 Avg.
H3DPC701 Applications of 3D Printing 20 20 20 80 03 - 100

Course
Objectives 1. To familiarise with applications of 3D Printing technologies.
2. To acquaint with the process of using biomedical data for 3D modelling.
3. To familiarize with basic process of additive manufacturing in different industries.





Course
Outcomes Upon successful completion of this course, the learner will be able:
1. To understand the perspectives for 3D printing in Jewellery industries for selection of an
appropriate material and tools to develop a given product using rapid prototyping
techniques.
2. Develop 3D model using various types of available biomedical data.
3. To understand the perspectives for 3D printing in Aerospace industries for selection of an
appropriate material and tools to develop a given product using rapid prototyping
techniques.
4. Illustrate understanding of various cost-effective alternatives for manufacturing products.
5. Use rapid prototyping and tooling concepts in any real-life applications.
6. Contribute towards the Product Development at the respective domain in the industry

Module Contents Hours



1. Applications in Jewellery Industries
Introduction to 3D Printing Jewellery : Steps Involved in Jewellery 3D Printing , Why
3D Printing for Jewellery Making, Techniques Involved in Jewellery 3D Printing, 3D
Printing Processes for Jewellery Designing , Challenges with Jewellery 3D Printing , 3D
Printing vs Traditional Methods, Types of Jewellery can be 3D Printed,
3D Printers for Jewellery Making – How They Work & Which to Choose


10
2. Medical Applications in Additive manufacturing
Presurgical Planning Models, Mechanical Bone Replicas, Teaching Aids and
Simulators, Customized Surgical Implants, Prosthetics and Orthotics’, Anthropology,
Forensics 8

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3. Applications in Aerospace Industries
Use of AM in Aerospace, Metal AM in Aerospace, Super alloys, Non-Destructive
Evaluation, Space technology
8

4. Applications in Tooling
Methods of Rapid tooling: Direct Soft Tooling, Indirect Soft Tooling, Direct Hard
Tooling, Indirect Hard Tooling.
9

5. Applications in various industries
Automotive, Défense, Coin industries, Household appliance, Toy industry, Ship
building, Un-manned Aerial Vehicles (UAV), Furniture, Construction and food
9

6. Applications in Design
Design for Additive Manufacturing (DFAM), Topology optimization for AM, Generative
design
Applications in Engineering, Analysis and Planning
8

Text/ Reference Books: -
1. Makers: The New Industrial Revolution (Telord 1403), by Chris Anderson
2. Medical Modelling The Application of Advanced Design and Rapid Prototyping Techniques in
Medicine, Richard Bibb, Dominic Eggbeer and Abby Paterson, Woodhead Publishing Series in
Biomaterials: Number 91, Elsevier Ltd.
3. 3D Printing in Aerospace and Defense Standard Requirements, by Gerardus Blokdyk
4. Additive Manufacturing for the Aerospace Industr y, by Francis Froes, Rodney Boyer
5. 3D Printing in Medicine, 1st Edition - April 1, 2017, by Deepak Kalaskar
6. An Update on Medical 3D Printing Hardcover – 1 January 2019, by Dr Raju Vaishya, Dr Abid
Haleem, Dr Lalit Maini
7. 3D Printing in Medicine: A Practical Guide for Medical Professionals Hardcover – Import, 12
October 2017, by Frank J. Rybicki, Gerald T. Grant
8. Rapid Prototyping, Principles and Applications by Rafiq I. Noorani, Wiley & Sons
9. Rapid Prototyping: Principles and Applications by Chua C.K, Leong K.F and Lim C.S, 2nd Edition,
World Scientific
10. Rapid Manufacturing – An Industrial revolution for the digital age by N.Hopkinson, R.J. M. Hauge,
P M, Dickens, Wiley
11. Advanced Manufacturing Technology for Medical applications: Reverse Engineering, Software
conversion and Rapid Prototyping by Ian Gibson, Wiley
Website Reference / Video Courses:
NPTEL Web Course:
1. Rapid Manufacturing, By Prof. J. Ramkumar, Prof. Amandeep Singh, IIT Kanpur,
https://onlinecourses.nptel.ac.in/noc20_me50/preview
2. Fundamentals of Additive Manufacturing Technologies, By Prof. Sajan Kapil, IIT Guwahati,
https://onlinecourses.nptel.ac.in/noc21_me115/preview
Assessment:

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287
Internal Assessment consists of two tests out of which; one should be compulsory class test (on
minimum 02 Modules) and the other is either a class test or assignment on live problems or course
project
Theory Examination :
1. Question paper will comprise of 6 questions, each carrying 20 marks.
2. Total four questions need to be solved.
3. Q.1 will be compulsory, based on entire syllabus wherein sub questions of 2 to 5 marks will
be asked.
4. Remaining question will be randomly selected from all the modules.

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‘3D Printing’ - SEM -VIII
Course
Code
Course Name Teaching Scheme (Contact Hours) Credits Assigned
Theory Tutorial Theory Tutorial Total
H3DPC801 3D Printing in Medical
Technology 04 - 04 - 04


Course
code

Course Name Examination Scheme
Theory
Term
Work
Total Internal Assessment End
Sem.
Exam Exam
Duration
(Hrs.) Test 1 Test 2 Avg.
H3DPC801 3D Printing in Medical
Technology 20 20 20 80 03 - 100

Course
Objectives 1. To acquaint with the process of using biomedical data for 3D modeling.
2. To familiarize with basic process of additive manufacturing in particularly 3D printing



Course
Outcomes Upon successful completion of this course, the learner will be able to:
1. Describe the creation of highly accurate physical models of human anatomy
2. Identify medical imaging for human body
3. Understand the modelling based on Biomedical data
4. Build and create data for 3D printing of any given object using rapid prototyping and tooling
processes.
5. Illustrate the understanding of different manufacturing processes
6. To Identify the processes and tooling concepts in Biomedical

Module Contents Hours

1. Introduction
Stages of the medical modelling process, The human form, Basic anatomical
terminology, technical terminology
8

2. Introduction to medical imaging
Computed tomography (CT), Cone beam CT (CBCT), Magnetic resonance (MR),
Noncontact surface scanning, Medical scan data, Point cloud data
10


3. Working with medical scan data
Pixel data operations, Using CT data: a worked example, Point cloud data operations,
Two -dimensional formats, Pseudo 3D formats, True 3D formats, File management and
exchange

12

4. Physical reproduction
Basic principles of medical modelling: orientation, sectioning, separating and joining,
trapped volumes
8

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289

5. Introduction to Additive manufacturing processes used for Bio-Modelling, Computer
numerical controlled machining, Cleaning and Sterilizing medical models
8
6. Case Studies based on Bio-Modelling & Future Development 6
Text/Reference Books: -
1. Medical Modelling The Application of Advanced Design and Rapid Prototyping Techniques in
Medicine, Richard Bibb, Dominic Eggbeer and Abby Paterson, Woodhead Publishing Series in
Biomaterials: Number 91, Elsevier Ltd.
2. 3D Printing in Medicine, 1st Edition - April 1, 2017, by Deepak Kalaskar
3. An Update on Medical 3D Printing Hardcover – 1 January 2019, by Dr Raju Vaishya, Dr Abid
Haleem, Dr Lalit Maini
4. 3D Printing in Medicine: A Practical Guide for Medical Professionals Hardcover – Import, 12
October 2017, by Frank J. Rybicki, Gerald T. Grant
5. Rapid Prototyping, Principles and Applications by Rafiq I. Noorani, Wiley & Sons
6. Rapid Prototyping: Principles and Applications by Chua C.K, Leong K.F and Lim C.S, 2nd Edition,
World Scientific
7. Advanced Manufacturing Technology for Medical applications: Reverse Engineering, Software
conversion and Rapid Prototyping by Ian Gibson, Wiley
Website Reference / Video Courses:
NPTEL Web Course:
1. Rapid Manufacturing, By Prof. J. Ramkumar, Prof. Amandeep Singh, IIT Kanpur,
https://onlinecourses.nptel.ac.in/noc20_me50/preview
2. Fundamentals of Additive Manufacturing Technologies, By Prof. Sajan Kapil, IIT Guwahati,
https://onlinecourses.nptel.ac.in/noc21_me11 5/preview

Assessment:
Internal Assessment consists of two tests out of which; one should be compulsory class test (on
minimum 02 Modules) and the other is either a class test or assignment on live problems or course
project
Theory Examination :
1. Question paper will comprise of 6 questions, each carrying 20 marks.
2. Total four questions need to be solved.
3. Q.1 will be compulsory, based on entire syllabus wherein sub questions of 2 to 5 marks will
be asked.
4. Remaining question will be randomly selected from all the modules.






Page 293


290
‘3D Printing’ - SEM -VII

Course Code
Course Name Teaching Scheme (Contact Hours) Credits Assigned
Theory Practical/
Tutorial Theory Practical/
Tutorial Total
H3DPSBL701 Skill Based Lab –
Digital Fabrication 04 -- 02 02



Course code

Course Name Examination Scheme
Theory
Term
Work

Oral

Total Internal Assessment End
Sem.
Exam Exam
Duration
(Hrs.) Test 1 Test 2 Avg.
H3DPSBL701 Skill Based Lab –
Digital Fabrication - - - - - 50 50 100



Course
Objectives 1. To impart the geometric modeling skills for development of 3D models of engineering
components.
2. To familiarize with production drawings with important features like GD &T, surface finish,
heat treatments etc.
3. To familiarize with additive manufacturing process
4. To acquaint with basic process of 3D modeling using biomedical data.



Course
Outcomes Upon successful completion of this course, the learner will be able to:
1. Illustrate basic understanding of types of CAD model creation.
2. Build geometric model of a given object using 3D modeling software
3. Generate assembly models of given objects using assembly tools of a modeling software
4. Demonstrate CAM Tool path and prepare NC - G code
5. Develop 3D model using available biomedical data
6. Build any given real life object using 3D printing process

Module Contents Hours

1. Geometric modeling of an Engineering component, demonstrating skills in sketching
commands of creation (line, arc, circle etc.) modification (Trim, move, rotate etc.) and
viewing using (Pan, Zoom, Rotate etc.)
06

2. Demonstrating modeling skills using commands like Extrude, Revolve, Sweep, Blend,
Loft etc. Mesh of curves, free form surfaces etc. Feature manipulation using Copy,
Edit, Pattern, Suppress, History operations etc.
04
3. Assembly: Constraints, Exploded views, interference check. Drafting (Layouts,
Standard & Sectional Views, Detailing & Plotting). 04
4. Solid modeling of any engineering component using any 3D modeling software. 04
5. Non - Contact Scanning – Generation of CAD model using 3D scanning equipment. 04
6. Reverse Engineering of a legacy component – Selection of components, 3D scanning,
CAD model verification, 3D print of CAD model. 04

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291
7. Modeling of a component using 3D modelling software and development of G – Code
output using Fractal Software. 06
8. Design an object with free form surface using Autodesk Fusion 360 and development
of G – Code output using Fractal Software. 04
9. Segmentation in Slicer’s Segment Editor module for the purpose of 3D printing. 04

10. Creation of 3D model from 2D images using any image processing software and
printing it. (3D Slicer open source) (Application: Any body organ like Heart,
Gallbladder etc. as per available Dicom files)
04
11. Development of physical 3D mechanical structure using any one of the Additive
manufacturing processes – Material to be used Metal 06
12. Development of physical 3D mechanical structure using any one of the Additive
manufacturing processes - Material to be used Plastic 04

Text/Reference Books: -
1. Machine Drawing by N.D. Bhatt.
2. A textbook of Machine Drawing by Laxminarayan and M.L.Mathur, Jain brothers Delhi
3. Machine Drawing by K.I. Narayana, P. Kannaiah, K.Venkata Reddy
4. Medical Modelling - The Application of Advanced Design and Rapid Prototyping Techniques in
Medicine, Richard Bibb, Dominic Eggbeer and Abby Paterson, Woodhead Publishing Series in
Biomaterials: Number 91, Elsevier Ltd
5. Biomaterials, artificial organs and tissue engineering, Edited by Larry L. Hench and Julian R. Jones,
Woodhead Publishing and Maney Publishing, CRC Press 2005
6. Additive Manufacturing Technologies: Rapid Prototyping to Direct Digital Manufacturing, I.
Gibson l D. W. Rosen l B. Stucker, Springer Publication.
Website Reference / Video Courses:
1. https:// www.autodesk.in/products/fusion -360/learn -support
2. https://knowledge.autodesk.com/support/inventor
3. https:// www.slicer.org/wiki/Documentation/4.10/Training
Term work:
Term work shall consist of all twelve experiments.
The distribution of marks shall be as follows:
Experiments Performance : 20 marks
Course Project : 20 marks
Attendance : 10 marks
The final certification and acceptance of term work ensures the minimum passing in the term work.
Oral Examination:
Oral examination will be based on entire lab work of H3DPSBL701 - Skill Based Lab – Digital
Fabrication

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292

University of Mumbai




Syllabus for

Honours /Minor Degree Program
In
Industrial Automation




FACULTY OF SCIENCE & TECHNOLOGY

(As per AICTE guidelines with effect from the academic year 2022 -2023)




Page 296


293
University of Mumbai
Industrial Automation
(With effect from 2022 -23)


Year
& Sem
Course Code and
Course Title Teaching Scheme
Hours / Week Examination Scheme and Marks Credit
Scheme

Theory Seminar
/Tutoria
l
Pract Internal
Assess
ment End
Sem
Exam Term
Work Oral
Total
Credits

TE
Sem
V HIAC501:
Fundamentals of
Industrial
Automation 04 -- -- 20 80 -- -- 100 04
Total 04 ‐ ‐‐ 100 ‐ ‐ 100 04
Total Credits = 04

TE
Sem.
VI HIAC601:
Industrial Internet
of Thing (IIOT)
04
--
--
20
80
--
--
100
04
Total 04 ‐ ‐ 100 ‐ ‐ 100 04
Total Credits = 04

BE
Sem
VII HIAC701:
AI and ML for
Automation 04 -- -- 20 80 - - 100 04
HIASBL 701:
AI and ML for
Automation -Lab - ‐ 04 ‐ ‐ 50 50 100 02
Total 04 ‐ 04 100 100 200 06
Total Credits = 06

BE
Sem
VIII HIAC801:
Applied Predictive
Analytics 04 -- -- 20 80 - - 100 04
Total 04 ‐ ‐ 100 ‐ 100 04
Total Credits = 04

Total Credits for Semesters V, VI, VII &VIII = 04+04+06+04 = 18

Page 297


294
Industrial Automation : Sem. V
Course
code Course Name Teaching scheme Credit assigned

HIAC 501 Fundamentals of
Industrial
Automation Theory Pract. Tut. Theory
Pract Tut. Total
4 - - 4 - - 4


Course
Code

Course Name Examination scheme
Theory (out of 100)
Term
work Pract.
and
Oral
Oral
Total Internal Assessment End
sem
Exam Test1 Test2 Avg.
HIAC501 Fundamentals
of Industrial
Automation
20
20
20
80
-
-
-
100



Course
objective 1. To impart knowledge of Industrial Automation.
2. To make the students learn industrial sensors.
3. To make the students learn various actuators.
4. To make the students learn about controller strategy and various automation tools like
PLC.
5. To give the students an overview of DCS and HMI.
6. To give students an overview of communication protocols.

Course
Outcome The students will able to
1. Recognize Industrial automation .
2. Select and configure industrial sensors.
3. Comprehend and work with various actuators.
4. Know various automation tools.
5. Work with DCS and HMI.
6. Select various communication protocols.

Pre requisites: Sensors and Transducers basic s
Module Content s Hours. CO
1 Introduction
Introduction - Automation in production system, Principles and strategies of
automation, Basic elements of an automated system, types of Automation,
Hierarchical level in automation, Advanced automation functions, Automated flow
lines and transfer mechanisms.
Material handling and identification technologies, Conveyor system, Automated
guided vehicle system, Automated storage systems, Automatic Identification
Methods.

6

CO1

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295
2 Sensors
Introduction to Industrial Measurement, overview of sensors, classification, sensor
characteristics, physical principles of sensing, sensor Materials and Technologies.
Inductive sensors, capacitive sensors, vision sensors, ultrasonic sensors, Elect ronic
SMART Digital remote sensor , Robotic sensors, Tactile sensing, Proximity sensors,
Range sensor, Position sensors, Fibre optic sensors, Guided microwave sensor,
wireless sensors, Electrical characteristics of sensors,
specifications of sensors, performance testing, selection guidelines.



8



CO2
3 Actuators
Pneumatic and hydraulic -directional and pressure control valves, cylinders, servo
proportional control valves, rotary actuators.
Electrical actuation: A.C and DC motors, stepper motors, mechanical switches and
solid state switches.
Mechanical Actuation: types of motion, kinematic chain, cams, gears, ratchets and
pawl, belt and chain drives, bearings, mechanical aspects of motor selection,
piezoelectric actuators, magneto -strictive actuators, memory metal
actuators. Selection Criteria of Actuators



8



CO3
4 Controller strategy / Automation Tools. PLC
Overview and Features, Types, specifications, PLC Architecture, PLC working, PLC
SCAN, new trends in PLC, PLC programming Languages, PLC instructions set,
Development of Ladder programme, case study Example, PLC Applications,
Overview of Motion con trol.PLC Installation and wiring.
SCADA
Overview, SCADA Architecture, SCADA -Hardware functions, New trends in scada
systems, applications, case study examples.

10

CO4
5 DCS & HMI
DCS: Overview and Features of DCS, DCS Architecture, Hardware elements, working
of DCS, DCS displays, DCS interfacing with PLC , DCS wiring diagr am. Applications
and suppliers.
HMI : Overview, need, Types, wiring practice, Data Handling , configuration and
interfacing with PLC & PC, Communication standards. ASM Graphics 10

CO5
6 Communication protocols
Overview of sensor networks, AS interface,CAN, HART, FF, Profibus, Interbus, Mbus,
Wireless sensor network, networks -IEEE, Zigbee, sensor interfaces. 6
CO6
Internal Assessment:
Internal Assessment consists of two tests out of which, one should be a compulsory class test
(on minimum 02 Modules) and the other is either a class test or assignment on live problems or
course project.

Page 299


296
Theory Examination:
1. Question paper will consist of 6 questions, each carrying 20 Marks.
2. Total 4 questions need to be solved.
3. Question No. 1 will be compulsory and based on entire syllabus wherein sub questions of 4
or 5 marks will be asked.
4. Remaining questions will be mixed in nature.
5. In question paper weight age of each module will be proportional to number of respective
Lecture hours as mentioned in the syllabus.
Text Books Recommended:
1. Jacob K Freden; Handbook of Modern sensors, Springer, 5th Edition
2. Tony Kuphaldt; Lessons in industrial instrumentation, version 4
3. Walt Boyes; Instrumentation Reference book, Fourth Edition.
4. William C Dunn; Fundamentals of Industrial Instrumentation and process control, McGraw Hill.
5. C.L. Albert and D.A. Coggan, Fundamentals of Industrial Control, ISA, 1992.
6. Bela G. Liptak, Instrument Engineer’s HandBook – Proces s Measurement and Analysis, ISA CRC Press
, 4th Edition, 2003.
7. Andrew Williams, Applied instrumentation in the process industries, 2nd Edition, Vol. 1 & 3, Gulf
publishing company.
8. Douglas. M.Considine; Process Instruments & Control Handbook, McGraw -Hill
9. S C Mukhopadhyay; Intelligent sensing, Instrumentation and Measurement, Springer.


Page 300


297
Industrial Automation : Sem. VI
Course
code Course
Name Teaching scheme Credit assigned
HIAC601 Industrial
Internet of
Thing (IIOT) Theory Pract. Tut. Theory Pract. Tut. Total
4 - - 4 - - 4


Course
Code
Course Name Examination scheme
Theory (out of 100)
Term
work Pract.
and
Oral
Oral
Total Internal Assessment End
sem
Exam Test1 Test2 Avg.
HIAC601 Industrial
Internet of
Thing (IIOT) 20 20 20 80 - - - 100


Course
objective 1. Introduce how IoT has become a game chang er in the new economy where
the c ustomers are looking for integrated value
2. Bring the IoT perspective in thinking and building solutions
3. Introduce the tools and techniques that enable IoT solution and
Security aspects.


Course
Outcome The students will able to
1. Describe IOT, IIOT
2. Design and develop the real -life IoT applications using off the shelf hardware and
software
3. Know various IoT Layers and their relative importance
4. Recognize various IoT platforms and Security
5. Realize the importance of Data Analytics in IoT
6. Design and thinking concepts of IIoT

Prerequisites: Microcontroller based Architecture and Programming
Module Content Hours CO


1 Introduction:
Introduction of Industry 4.0, Elements of industry 4.0, Introduction to IOT,
what is IIOT? IOT Vs. IIOT, History of IIOT, Components of IIOT - Sensors,
Interface, Networks, People &Process, Hype cycle, IOT Market, Trends& future
Real -life examples, Key terms – IOT Plat form, Interfaces, API, clouds, Role of
IIOT in Manufacturing Processes
Use of IIOT in plant maintenance practices, Sustainability through Business
excellence tools Challenges & Benefits in implementing IIOT


6

CO1

Page 301


298


2 Architectures:
Overview of IOT components; Various Architectures of IOT and IIOT,
Advantages & disadvantages, Industrial Internet - Reference Architecture; IIOT
System components: Sensors, Gateways, Routers, Modem, Cloud brokers,
servers and its integration, WSN,
WSN network design for IOT

8

CO2

3 Sensor and Interfacing:
Introduction to sensors, Transducers, Classification, Roles of sensors in IIOT,
Various types of sensors, Design of sensors, sensor architecture, special
requirements for IIOT sensors, Role of actuators, types of actuators, IT and OT
Integration.
10
CO3


4 Protocols and Cloud:
Need of protocols; Types of Protocols, Wi -Fi, Wi -Fi direct, Zigbee, Z wave,
BACnet, BLE, Modbus, SPI , I2C, IIOT protocols –COAP, MQTT,6lowpan, lwm2m,
AMPQ
IIOT cloud platforms: Overview of cots cloud platforms, Predix, thingworks,
azure etc. Data analytics, cloud services, Business models: Saas, Paas, Iaas.
8
CO4



5 Cyber security for industry, Privacy, and Governance
Cyber physical system, cyber security life cycle, cyber security guidelines,
standard IEC 62443
Introduction to web security, Conventional web technology and relationship
with IIOT, Vulnerabilities of IoT, Privacy, Security requirements, Threat
analysis, Trust, IoT security tomography and layered attacker model, Identity
establishment, Access control, Message integrity, non -repudiation and
availability, Security model for IoT.

8

CO5



6 IOT Analytics and CASE study:
Role of Analytics in IOT, Data visualization Techniques, Introduction to R
Programming, Statistical Methods.
Internet of Things Applications: Smart Metering, e -Health Body Area Networks,
City Automation, Automotive Applications, Home Automation, Smart Cards,
Plant Automation,
Real life examples of IIOT in Manufacturing Sector.

8

CO6

Internal Assessment:
Internal Assessment consists of two tests out of which, one should be a compulsory class test (on
minimum 02 Modules) and the other is either a class test or assignment on live problems or course
project.
Theory Examination:
1. Question paper will consist of 6 questions, each carrying 20 Marks.
2. Total 4 questions need to be solved.
3. Question No. 1 will be compulsory and based on entire syllabus wherein sub questions of 4 or 5
marks will be asked.

Page 302


299
4. Remaining questions will be mixed in nature.
5. In question paper weight age of each module will be proportional to number of
respective Lecture hours as mentioned in the syllabus.

Text Books:
1. Daniel Minoli, Building the Internet of Things with IPv6 and MIPv6: The Evolving World of M2M
Communications, ISBN: 978 -1-118-47347 -4, Willy Publications 2. Bernd Scholz -Reiter, Florian
2. Michahelles, Architecting the Internet of Things, ISBN 978 -3- 642-19156 -5 e-ISBN 978 -3-
642-19157 -2,Springer

Reference Books:
1. Hakima Chaouchi, The Internet of Things Connecting Objects to the Web, ISBN : 978 -1-
84821 -140-7, Willy Publications
2. Olivier Hersent, David Boswarthick, Omar Elloumi, The Internet of Things: Key Applications
and Protocols, ISBN: 978 -1-119-99435 -0, 2nd Edit ion, Willy Publications
3. Inside the Internet of Things (IoT), Deloitte University Press
4. Internet of Things - From Research and Innovation to Market Deployment; By Ovidiu & Peter;
River Publishers Series
5. Five thoughts from the Father of the Internet of Things ; by ByPhil Wainewright - Kevin
Ashton
6. How Protocol Conversion Addresses IIoT Challenges: White Paper By Red Lion.

















Page 303


300
Industrial Automation: Sem. VII
Subject
Code Subject Name Teaching Scheme
Credit Assigned
Th Pract. Tut. Th Pract. Tut. Total
HIAC701 Artificial Intelligence and
Machine Learning for
Automation 4 - - 4 - - 4

Sub
Code Subject Name Examination scheme
Theory
Term
work Pract.
and
Oral Oral Total Internal Assessment End
sem
Exam Test1 Test2 Avg.
HIAC701 Artificial Intelligence
and Machine Learning
for Automation 20 20 20 80 - - - 100


Course
Objectives 1. To familiarize student with basic concepts of Artificial Intelligence and Machine learning.
2. To provide understanding of the concepts of regression, classification, clustering and
deep learning algorithms.
3. To introduce the students to various applications of Artificial Intelligence and Machine
learning for industrial automation

Course
Outcomes Students will be able to:
1. Introduce concepts of Artificial Intelligence and Machine learning
2. Explicate statistical tools and development of database for AI/ML.
3. Analyze the various algorithms for Regression, Classification and Clustering.
4. Evaluate metrics for ML/AI algorithms.
5. Examine the algorithms for deep learning.
6. Explain examples of ML/AI algorithms for industrial automation.

Module Contents Hrs. CO
Mapping
1. Introduction to Artificial Intelligence:
Evolution, definition, types, application examples, benefits/advantages,
limitations/issues, comparison. 06 CO1
2. Review of statistical concepts:
Mean, variance, covariance, standard deviation, random variable, probability
distribution, probability distribution function, normal distribution, binomial
distribution, poisson distribution, central limit theorem, vector norms, principal
component analysi s.
Data collection and preparation:
Collecting, cleaning, normalization, standardization, missing data, underfitting
and overfitting, neglecting outliers, annotation, labelling. Data Splitting: Training,
Validation, and Test Datasets. Public datasets for m achine learning. 08 CO2

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301
3. Regression:
Simple Linear regression, Multiple Linear Regression, Polynomial Regression,
Logistic regression.
Classifiers:
k-Nearest Neighbours, Decision trees, naïve Bayes, SVM for Linearly separable
data, Kernel SVM for Non -Linearly separable data.
Clustering:
k-means clustering. 10 CO3
4. Evaluation Metrics :
True Positive, True Negative, False Positive, False Negative, accuracy, precision,
recall or True Positive Rate, False Positive Rate, Receiver Operating
Characteristic, Area Under the Curve, Confusion matrix, F -score . 04 CO4
5. Deep Learning:
Multilayer Perceptron (MLP), Convolutional Neural Network (CNN), Recurrent
Neural Network (RNN) 08 CO5
6. Application in Industrial Automation : Robotics, Factory automation, Process
control, Electrical Engineering
Challenges, Data Screening, Feature Engineering, Projected improvement,
Model Design, Limitations, Future scope, References. 12 CO6

Internal Assessment:
Internal Assessment consists of two tests out of which, one should be compulsory class test (on
Minimum 02 Modules) and the other is either a class test or assignment on live problems or Course
project.
Theory Examination:
1. Question paper will comprise of 6 questions, each carrying 20 Marks.
2. Total 4 questions need to be solved.
3. Question No. 1 will be compulsory and based on entire syllabus wherein sub questions of 4 or 5
marks will be asked.
4. Remaining questions will be mixed in nature.
5. In question paper weightage of each module will be proportional to number of respective lecture
hours as mentioned in the syllabus.
Text Books:
1. Harrington, Peter. Machine learning in action . Simon and Schuster, 2012.
2. Zheng, Alice, and Amanda Casari. Feature engineering for machine learning: principle s and
techniques for data scientists . " O'Reilly Media, Inc.", 2018.
3. Jiang, Hui. Machine Learning Fundamentals: A Concise Introduction . Cambridge University Press,
2021.
4. Huyen, C. “Designing Machine Learning Systems: An Iterative Process for Production -Ready
Applications” , O'Reilly Media, 2022.
5. Gupta, Itisha, and Garima Nagpal. Artificial Intelligence and Expert Systems . Stylus Publishing, LLC,
2020.
Reference Books:
1. Pandey, Yogendra Narayan, et al. Machine Learning in the Oil and Gas Industry . apress, Texas, 2020.
2. Bangert, Patrick, ed. Machine learning and data science in the oil and gas industry: Best practices,
tools, and case studies . Gulf Professional Publishing, 2021.
3. Das, Santosh Kumar, et al., eds. Machine learning algorithms for industrial appli cations . Cham:
Springer, 2021.

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302
Industrial Automation : SEM V II

Course Code
Course Name Teaching Scheme
(Contact Hours) Credits Assigned
Th Pract. Tut. Th Pract. Tut. Total
HIASBL701 Artificial Intelligence
and Machine
Learning for
Automation Lab - 4 - - 4 - 2

Subject
Code Subject Name Examination scheme
Theory (out of 100)
Term
work Oral Total Internal Assessment End
sem
Exam Test1 Test2 Avg.
HIASBL701 Artificial Intelligence
and Machine
Learning for
Automation Lab -- -- -- -- 50 50 100

Course
Objectives 1. To familiarize student with basic concepts of Artificial Intelligence and Machine
learning.
2. To provide understanding of the concepts of regression, classification, clustering
and deep learning algorithms.
3. To introduce the students to various applications of Artificial Intelligence and
Machine learning for industrial automation
Course
Outcomes Students will be able to
1. Write programs based on data compression and dimensionality reduction.
2. Write programs for regression, classification and clustering.
3. Calculate evaluation metrics for various algorithms.
4. Write programs based on deep learning algorithms.
5. Demonstrate working of AI/ML in Robotics and Factory automation.
6. Validate working of AI/ML in Process control and Electric al Engineering.

Syllabus: Same as that of Subject HIAC701 .
List of the Laboratory Experiments:
Sr.
No. Contents CO
Mapping
1. Write a python program to perform PCA for dimension reduction or data compression. CO1
2. Develop/download database of any industrial machine/system. Explain hardware
system used for data collection. Explain specifications/characteristics of collected
data.
CO2

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303
3. Write a python program to implement linear regression with one variable, two
variables for given dataset. CO2
4. Demonstrate the working of SVM classifier for a linearly separable data set . CO2
5. Demonstrate the working of Kernel SVM classifier for a non -linearly separable data
set. CO2
6. Demonstrate the working of the decision tree based ID3 algorithm. Use an appropriate
data set for building the decision tree and apply this knowledge to classify a new
sample. CO2
7. Calculate evaluation metrics such as accuracy, precision, recall, confusion matrix, F -
score, etc for regression, classification and clustering algorithms. CO3
8. Calculate evaluation metrics such as Receiver Operating Characteristic, Area Under the
Curve, etc for regression, classification and clustering algorithms. CO3
9. Implement multilayer Perceptr on (MLP) for predicting stock price. Time series
forecasting. CO4
10. Implement Convolutional Neural Network (CNN) to recognize hand -written digits
dataset. CO4
11. Implement Recurrent Neural Network (RNN) for speech recognition. CO4
12. Case study or mini project on application of AI/ML in Robotics. CO5
13. Case study or mini project on application of AI/ML in Factory automation. CO5
14. Case study or mini project on application of AI/ML in Process control. CO6
15. Case study or mini project on application of AI/ML in Electrical Engineering. CO6

Any other experiment based on syllabus which will help students to understand topic/concept.

Oral Examination:
Oral examination will be based on entire syllabus.

Term Work:
Term work shall consist of minimum 12 experiments.
The distribution of marks for term work shall be as follows:
Laboratory work (Experiments): : 20 Marks
Laboratory work (programs / journal): 20 Marks
Attendance: : 10 Marks

The final certification and acceptance of term work ensures the satisfactory performance of laboratory work and
minimum passing in the term work.






Page 307


304
Industrial Automation : SEM V III
Subject
code Subject Name Teaching scheme Credit assigned
HIAC801 Applied
Predictive
Analytics Theory Pract. Tut. Theory Pract. Tut. Total
4 - - 4 - - 4

Sub
Code Subject Name
Examination scheme
Theory (out of 100)
Term
work Pract.
and
Oral Oral Total Internal Assessment End sem
Exam Test1 Test2 Avg.
HIAC801 Applied Predictive
Analytics 20 20 20 80 - - - 100

Course
objective 1. To deliver Knowledge of core operations in Energy Vertical Solving complex issues analyzing
available data in Operations, Maintenance, Reliability, Safety, Procurement, Inventory etc.,
2. To introduce forecasting and predictive techniques.
Course
Outcome
The students will able to
1. Identify the use of analytics and its tools
2. Interpret data and preparation of data
3. Use descriptive modeling techniques
4. Practice predictive modeling techniques such as decision tree, logistic regression and neural
network
5. Apply and build models using clustering, regression and classification techniques and its
correspo nding algorithms
6. Discuss the case studies of Predictive Analytics and Predictive Maintenance

Pre requisites: Data Science concepts
Module Content Hours. CO
1
Overview of Predictive Analytics:
What and Why Analytics, Predictive Analytics? Supervised vs. Unsupervised Learning,
Parametric vs. Non -Parametric Models, Business Intelligence,
Predictive Analytics vs. Business Intelligence, Predictive Analytics vs. Statistics,
Statistics and Analytics, Predictive Analytics and Statistics Contrasted, Predictiv e
Analytics vs. Data Mining, Challenges in Using Predictive Analytics. Concep t of hb 06 CO1
2 Data Understanding and Data Preparation:
Single Variable Summaries, Applying Simple Statistics in Data Understanding,
Categorical Variable Assessment, Data Visualization in One Dimension, Two or Higher
Dimensions.
Data Preparation, Fixing Missing Data, Feature Creation, Simple Variable
Transformations, Fixing Skew, Binning Continuous Variables, Numeric Variable 08 CO2

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305
Scaling, Nominal Variable Transformation, Ordina l Variable Transformations, Date
and Time Variable Features, Multidimensional Features
3 Descriptive Modeling:
Data Preparation, Issues with Descriptive Modeling, Principal Component Analysis,
The PCA Algorithm, Applying PCA to New Data, PCA for Data Interpretation,
Additional Considerations before Using PCA, The Effect of Variable Magnitude on
PCA Models, Clustering Algorithms, The K -Means Algorithm, Data Preparation for K -
Means 07 CO3
4 Predictive Modeling: Decision Trees, The Decision Tree Landscape, Building Decision
Trees, Logistic Regression, Interpreting Logistic Regression Models, Other Practical
Considerations for Logistic Regression, Neural Networks,
Building Blocks: The Neuron, Neural Network Training, The Flexibility of Neural
Netwo rks, Neural Network Settings, Neural Network Pruning, Interpreting Neural
Networks, Neural Network Decision Boundaries, Other Practical Considerations for
Neural Networks 09 CO4
5 Predictive Modeling: K-Nearest Neighbor, the k -NN Learning Algorithm, Distance
Metrics for k -NN, Other Practical Considerations for k -NN,
Naïve Bayes, Bayes’ Theorem, The Naïve Bayes Classifier Interpreting Naïve Bayes
Classifiers, Other Practical Considerations for Naïve Bayes, Regression Models,
Linear Regression, Linear R egression Assumptions, Variable Selection in Linear
Regression, Interpreting Linear Regression Models, Using Linear Regression for
Classification, Other Regression Algorithms 09 CO5
6 Assessing Predictive Models: Batch Approach to Model Assessment, Percen t Correct
Classification, Rank -Ordered Approach to Model Assessment, Assessing Regression
Models.
Case studies: Quality Prediction in a Mining Process, predicting the consumption of
electricity in the coming future (refer Kaggle data set)
Predictive Maintenance: Find a defect in the production, Sensor Fault
Detection(refer Kaggle data set), Boiler Fault Detection ((refer https://ieee -
dataport.org/ ) 09 CO6

Internal Assessment:
Internal Assessment consists of two tests out of which, one should be compulsory class test (on
Minimum 02 Modules) and the other is either a class test or assignment on live problems or Course
project.
Theory Examination:
1. Question paper will comprise of 6 questions, each carrying 20 Marks.
2. Total 4 questions need to be solved.
3. Question No. 1 will be compulsory and based on entire syllabus wherein sub questions of 4 or 5
marks will be asked.
4. Remaining questions will be mixed in nature.
5. In question paper weightage of each module will be proportional to number of respective lecture
hours as mentioned in the syllabus.

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Text Books:
1. Dean Abbott, “Applied Predictive Analytics: Principles and Techniques for the Professional Data Analyst” ,
ISBN: 978 -1-118-72796 -6
2. P. Kaliraj, T. Devi, “Big Data Applications in Industry 4.0”, ISBN 9781032008110, Published February 10, 2022
by Auerbach Publications
3. Mahir Oner, Sultan Ceren Oner , “Data Analytics in Industry 4.0: In the Perspective of Big Data”.

Reference Books :
1. Gareth James, Daniela Witten, Trevor Hastie Robert Tibshirani. “An Introduction to Statistical Learning with
Applications in R”
2. Joel Grus , “Data science from scratch”, Orielly publication, ISBN: 9781492041139, May 2019
3. David Roi Hardoon, Galit Shmueli, “Ge tting Started with Business Analyti cs: Insightful Decision -Making” , CRC
Press, ISBN 9781498787413
4. James R Evans, “Business Analytics”, Pearson publication, ISBN: 9780135231678

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