N BE Internet of Things Sem V VI_1 Syllabus Mumbai University

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AC – 01/11/2023
Item No. – 6.7(N)





University of Mumbai







Syllabus for
B.E. (Internet of Things )
Semester – VII & VIII

Choice Based Credit System
REV- 2019 ‘C’ Scheme

(With effect from the academic year 202 3-24)

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University of Mumbai











Dr. Deven Shah Dr. Shivram Garje
Offg. Associate Dean Offg. Dean
Faculty of Science and Technology Faculty of Science and Technology Sr. No. Heading Particulars
1 Title of the Course B.E. (Internet of Things )
2 Eligibility for Admission
After Passing Third Year Engineering as per
the Ordinance 0.6243
3 Passing Marks 40%
4 Ordinances /
Regulations ( if any) Ordinance 0.6243
5 No. of Years / Semesters 4 Years/ 8 semesters
6 Level Under Graduation

7 Pattern Semester

8 Status New
REV-2019 ‘C’ Scheme

9 To be implemented from
Academic Year With effect from Academic Year: 2023 -2024 Syllabus for Approval

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Preamble

To meet the challenge of ensuring excellence in engineering education, the issue of
quality needs to be addressed, debated and taken forward in a systematic manner.
Accreditation is the principal means of quality assurance in higher education. The major
emphasis of accreditation process is to measure the outcomes of the program that is
being accredited. In line with this Faculty of Science and Technology (in particular
Engineering) of University of Mumbai has taken a lead in incorporating philosophy of
outcome based education in the process of curriculum development.
Faculty resolved that course objectives and course outcomes are to be clearly defined
for each course, so that all faculty members in affiliated institutes understand the depth
and approach of course to be taught, which will enhance learner’s learning process.
Choice based Credit and grading system enables a much -required shift in focus from
teacher -centric to learner -centric education since the workload estimated is based on the
investment of t ime in learning and not in teaching. It also focuses on continuous
evaluation which will enhance the quality of education. Credit assignment for courses is
based on 15 weeks teaching learning process, however content of courses is to be
taught in 13 weeks and remaining 2 weeks to be utilized for revision, guest lectures,
coverage of content beyond syllabus etc.
There was a concern that the earlier revised curriculum more focused on providing
information and knowledge across various domains of the said program, which led to
heavily loading of students in terms of direct contact hours. In this regard, faculty of
science and technology resolved that to minimize the burden of contact hours, total
credits of entire program will be of 170, wherein focus is not only on providing knowledge
but also on building skills, attitude and self learning. Therefore in the present c urriculum
skill based laboratories and mini projects are made mandatory across all disciplines of
engineering in second and third year of programs, which will definitely facilitate self
learning of students. The overall credits and approach of curriculum p roposed in the
present revision is in line with AICTE model curriculum.
The present curriculum will be implemented for Second Year of Engineering from the
academic year 2021 -22. Subsequently this will be carried forward for Third Year and
Final Year Engine ering in the academic years 2022 -23, 2023 -24, respectively.

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Incorporation and Implementation of Online Contents
from NPTEL/ Swayam Platform



The curriculum revision is mainly focused on knowledge component, skill based activities and
project based activities. Self-learning opportunities are provided to learners. In the revision process
this time in particular Revised syllabus of ‘C’ scheme wherever possible additional resource links
of platforms such as NPTEL, Swayam are appropriately provided. In an earlier revision of
curriculum in the year 2012 and 2016 in Revised scheme ‘A' and ‘B' respectively, efforts were
made to use online contents more appropriately as additional learning materials to enhance
learning of stude nts.
In the current revision based on the recommendation of AICTE model curriculum overall credits
are reduced to 171, to provide opportunity of self -learning to learner. Learners are now getting
sufficient time for self -learning either through online cour ses or additional projects for enhancing
their knowledge and skill sets.
The Principals/ HoD’s/ Faculties of all the institute are required to motivate and encourage learners
to use additional online resources available on platforms such as NPTEL/ Swayam. Learners can
be advised to take up online courses, on successful completion they are required to submit
certification for the same. This will definitely help learners to facilitate their enhanced learning
based on their interest.





Dr. Deven Shah
Associate Dean
Faculty of Science and Technology
University of Mumbai

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Prefac e by Board of Studies Team

It is our honor and a privilege to present the Rev -2019 ‘C’ scheme syllabus of the Bachelor of
Engineering in the Internet of Thing - IoT(effective from the year 2021 -22). AICTE has introduced
IoT as one of the nine emerging technology and hence many colleges affiliated with the University
of Mumbai has started four years UG program for IoT. As part of the policy decision from the
University end, the Board of IT got an opportunity to work on designing the syllabus for this new
branch. As the Internet of Things is comparatively a young branch among other emerging
engineering disciplines in the University of Mumbai, and hence while designing the syllabus
promotion of an interdisciplinary approach has been considered.

The branch also provides multi -faceted scope like better placement and promotion of
entrepreneurship culture among students and increased Industry Institute Interactions. Industries'
views are considered as stakeholders while the design of the syllabus. As per Indust ry views only
16 % of graduates are directly employable. One of the reasons is a syllabus that is not in line with
the latest emerging technologies. Our team of faculties has tried to include all the latest emerging
technologies in the Internet of Thing sy llabus. Also the first time we are giving skill -based labs
and Mini -project to students from the third semester onwards, which will help students to work
on the latest Internet of Thing technologies. Also the first time we are giving the choice of elective
from fifth semester such that students will be mastered in one of the Internet of Thing domain.
The syllabus is peer -reviewed by experts from reputed industries and as per their suggestions, it
covers future emerging trends in Internet of Thing technology and research opportunities available
due to these trends. .

We would like to thank senior faculties of IT, Computer and Electronics Department, of all
colleges affiliated to University of Mumbai for significant contribution in framing the syllabus.
Also on behalf of all faculties we thank all the industry experts for their valuable feedback and
suggestions. We sincerely hope that the revised syllabus will help all graduate engineers to face
the future challenges in the field of Emerging Areas of Internet of Thing.

Program Specific Outcome for graduate Program in Internet of Thing
1. Apply Core Internet of Thing knowledge to develop stable and secure Internet of Things
Application.
2. Identify, Design, Internet of Thing infrastructures for an enterprise using concepts and best
Practices in the area Internet of Thing Domain.
3. Ability to work in multidisciplinary projects and make it Internet of Thing enabled Applications.

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Program Structure for Fourth Year Engineering Semester VII & VIII
UNIVERSITY OF MUMBAI
(With Effect from 2023 -24)
Semester VII

Course
Code
Course Name Teaching Scheme
(Contact Hours)
Credits Assigned
Theory Pract.
Tut. Theory Pract. Total
IOTC701 Machine Learning &
IoT 3 -- 3 -- 3
IOTC702 Edge and Fog
Computing 3 -- 3 3
IOTDO70
1X Department Optional
Course – 3 3 -- 3 -- 3
IOTDO70
2X Department
Optional Course –4 3 -- 3 -- 3
IOTIO701
X Institute Optional
Course – 1 3 -- 3 -- 3
IOTL701 ML & IoT Lab -- 2 -- 1 1
IOTL702 Edge and Fog
Computing Lab -- 2 -- 1 1
IOTL703 DeVOPs Lab -- 2 -- 1 1
IOTL704 Linux administration
Lab -- 2 -- 1 1
IOTP701 Major Project I -- 6# -- 3 3
Total 15 14 15 7 22



Course
Code


Course Name Examination Scheme
Theory Term
Work Prac/
oral Total

Internal Assessment End
Sem
Exam Exam.
Duration
(in Hrs)
Test1 Test2 Avg
IOTC701 Machine Learning &
IoT 20 20 20 80 3 -- -- 100
IOTC702 Fog Computing 20 20 20 80 3 -- -- 100
IOTDO70
1X Department
Optional Course –3 20 20 20 80 3 -- -- 100
IOTDO70
2X Department
Optional Course –4 20 20 20 80 3 -- -- 100

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IOTIO701
X Institute Optional
Course – 1 20 20 20 80 3 -- -- 100
IOTL701 ML & IoT Lab -- -- -- -- -- 25 25 50
IOTL702 Edge and Fog
Computing Lab -- -- -- -- -- 25 25 50
IOTL703 DeVOPs Lab -- -- -- -- -- 25 25 50
IOTL704 Linux administration
Lab -- -- -- -- -- 25 25 50
IOTP701 Major Project I -- -- -- -- -- 25 25 50
Total -- -- 100 400 -- 125 125 750
# indicates work load of Learner (Not Faculty), for Major Project

IOTDO701X Department Optional Course –3
IOTDO701 1 IoT for Healthcare Application
IOTDO701 2 Wearable Computing & IoE
IOTDO701 3 Privacy & Security
IOTDO701 4 IoT for Smart Cities


IOTDO702X Department Optional Course –4
IOTDO702 1 SDN & NFV for IoT
IOTDO702 2 Blockchain for IoT
IOTDO702 3 Enterprise IoT Cyber Security
IOTDO702 4 Software Engineering & Testing Methodology for IoT
# Institute Level Optional Course (ILO)

Every student is required to take one Institute Elective Course for Semester VII, which is
not closely allied to their disciplines. Different sets of courses will run in the both the
semesters.
ILO701X Institute Optional Course – 1 ( Common for all branches will be
notified )
ILO7011 Product Lifecycle Management
ILO7012 Reliability Engineering
ILO7013 Management Information System
ILO7014 Design of Experiments
ILO7015 Operation Research
ILO7016 Cyber Security and Laws
ILO7017 Disaster Management and Mitigation
Measures
ILO7018 Energy Audit and Management
ILO7019 Development Engineering

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Program Structure for Fourth Year Engineering Semester VII & VIII
UNIVERSITY OFMUMBAI
(With Effect from 2023 -24)

Semester VIII


Course
Code
Course Name Teaching
Scheme
(Contact Hours)
Credits Assigned
Theory Pract.
Tut. Theory Pract. Total
IOTC801 Industrial IoT 3 -- 3 -- 3
IOTDO80
1X Department Optional Course – 5 3 -- 3 -- 3
IOTDO80
2X Department Optional Course – 6 3 -- 3 -- 3
IOTIO801
X Institute Optional Course – 2
3 -- 3 -- 3
IOTL801 IoT Automation Lab -- 2 -- 1 1
IOTL802 Cyber Security Lab -- 2 -- 1 1
IOTP801 Major Project II
-- 12# -- 6 6
Total 12 16 12 8 20



Course
Code



Course Name Examination Scheme
Theory Term
Work Prac
/oral Total

Internal Assessment End
Sem
Exam Exam.
Durati
o n
(in Hrs)
Test1 Test2 Avg
IOTC801 Industrial IoT 20 20 20 80 3 -- -- 100
IOTDO80
1X Department Optional Course – 5 20 20 20 80 3 -- -- 100
IOTDO80
2X Department Optional Course – 6 20 20 20 80 3 -- -- 100
IOTIO801
X Institute Optional Course – 2
20 20 20 80 3 -- -- 100
IOTL801 IoT Automation Lab -- -- -- -- -- 25 25 50
IOTL802 Cyber Security Lab -- -- -- -- -- 25 25 50
IOTP801 Major Project II
-- -- -- -- -- 100 50 150
Total -- -- 80 320 -- 150 100 650
# indicates work load of Learner (Not Faculty), for Major Project

Students group and load of faculty per week.

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Mini Project 1 and 2 :
Students can form groups with minimum 2 (Two) and not more than 4
(Four) Faculty Load : 1 hour per week per four groups



Major Project 1 and 2 :
Students can form groups with minimum 2 (Two) and not more than 4
(Four) Faculty Load : In Semester VII – ½ hour per week per project group
In Semester VIII – 1 hour per week per project group



IOTDO801X Department Optional Course – 5
IOTDO8011 User Interface Design for IoT
IOTDO8012 Energy Harvesting and Power Management for IoT Devices
IOTDO8013 Information Retrieval System
IOTDO8014 Next Generation IoT


IOTDO802X Department Optional Course –6
IOTDO8021 Business Process Management Cognitive IoT
IOTDO8022 RESTful Design for IoT Systems
IOTDO8023 Green IT
IOTDO8024 IoT for Smart Grids


# Institute Level Optional Course (ILO)

Every student is required to take one Institute Elective Course for Semester VI II, which is
not closely allied to their disciplines. Different sets of courses will run in the both the
semesters.

ILO801X Institute Optional Course – 2 ( Common for all branches will be notified
)
ILO8011 Project Management
ILO8012 Finance Management
ILO8013 Entrepreneurship Development
and Management
ILO8014 Human Resource Management
ILO8015 Professional Ethics and CSR
ILO8016 Research Methodology
ILO8017 IPR and Patenting
ILO8018 Digital Business Management
ILO8019 Environmental Management

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Subject Code Subject
Name Theor
y Practical Tutorial Theory Oral Tutorial Total

IOTC701 Machine
learning
and IoT 03 -- -- 03 -- -- 03

Subject
Code Subject
Name Examination Scheme
Theory Marks Term
Wor
k Practical Oral Total Internal assessment End
Sem.
Exam Test
1 Test 2 Avg. of 2
Tests
IOTC701
Machine
learning
and IoT 20 20 20 80 -- -- -- 100

Prerequisite: Engineering Mathematics, Data Structures, Algorithms
Course Objectives: The main objective of this course is to introduce the students to the basics of
Machine Learning Concepts applicable with the Internet of Things.
1 To introduce the basic concepts and techniques of Machine Learning and Deep Learning.
2 To learn and understand Machine learning and Deep Learning methods for IoT applications
3 To be able to apply various Machine Learning techniques for combining Machine learning
models.
4 To get acquainted with machine learning for IOT Data Analysis.
5 To design IoT applications using Machine Learning and Deep Learning methods.
6 To understand the social impact and benefits of IOT applications.


Course Outcomes: After the successful completion of course , learner should able to -


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 understand the fundamentals of Machine learning and IoT. L2

2. To acquire fundamental knowledge of developing Machine learning
models. L2
3. To apply an appropriate Machine learning model for the IoT data. L3
4. To evaluate Machine learning techniques to combine predictions from
different models. L5
5. To demonstrate various IoT applications using Machine learning and Deep
learning techniques using IoT data analysis. L3
6. To comprehend the benefits of IoT and Machine learning for society. L4


Module Content Hrs Co
mapping

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1 Introduction to Machine Learning and IoT 06 CO1

1.1 Machine Learning, Types of Machine Learning, Issues in Machine
Learning, Application of Machine Learning, Steps in developing a
Machine Learning Application.
1.2 Introduction of IoT: Definition and characteristics of IoT, Technical
Building blocks of IoT, Device, Communication Technologies, Data,
Physical design of IoT, IoT enabling technologies, IoT Issues and
Challenges - Planning, Costs and Quality, Security and Privacy, Risks
1.3 Introduction to Advanced ML - Deep Learning, Reinforcement Learning

Self Learning topics: AI and IoT
2 Learning with Regression and Trees 06 CO2

2.1 Learning with Regression: Linear Regression, Multivariate
Linear Regression, Logistic Regression.

2.2 Learning with Trees: Decision Trees, Constructing Decision Trees
using Gini Index (Regression), Classification and Regression Trees
(CART)

2.3 Performance Metrics: Confusion Matrix, [Kappa Statistics],
Sensitivity, Specificity, Precision, Recall, F -measure, ROC curve

Self Learning topic : Implementation of all above techniques
3 Learning with Classification 07 CO3

3.1 Support Vector Machine : Constrained Optimization, Optimal decision
boundary, Margins and support vectors, SVM as constrained
optimization problem, Quadratic Programming, SVM for linear and
nonlinear classification, Basics of Kernel trick.
4 Machine learning (ML) methods for IoT Application 08 CO4
4.1 Support Vector Machines (SVMs), Bayesian theorem -based algorithms,
kNearest neighbour (KNN), Random forest (RF), Association Rule (AR)
algorithms, Ensemble learning (EL), k -Means clustering, Principal component
analysis (PCA)
5 Deep learning (DL) methods for IoT Applications 07 CO5
Convolutional neural networks (CNNs), Recurrent neural networks (RNNs),
Deep autoencoders (AEs), Restricted Boltzmann machines (RBMs), Deep
belief networks (DBNs), Generative adversarial networks (GANs), Ensemble
of DL networks (EDLNs)

Self learning topic : NNFL and NP with IoT
6 Applications of ML and IOT 05 CO6
Case Studies: IOT for Agriculture, Remote Patient Monitoring, Smart City,
Smart Transportation, IOT Security using ML. etc.
Total 39

Text Books
1. Peter Harrington, ―Machine Learning n Action‖, DreamTech Press
2. Ethem Alpaydın, ―Introduction to Machine Learning‖, MIT Press
3. Tom M. Mitchell, ―Machine Learning‖ McGraw Hill

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4. Stephen Marsland, ―Machine Learning An Algorithmic Perspective‖,
CRC Press
5 : Neeraj Kumar, Aaisha Makkar, “ MACHINE LEARNING IN
COGNITIVE IOT”, https://www.routledge.com/Machine -Learning -in-
Cognitive -IoT/KumarMakkar/p/book/9780367359164 ISBN
9780367359164 Published June 1, 2020 by CRC Press
Reference Books

1.Puneet Mathur, “ IoT Machine Learning Applications in Telecom,
Energy, and Agriculture,
With Raspberry Pi and Arduino Using Python”, ISBN 978 -1-4842 -5549 -0
2. Nicolas Modrzyk, “ Real -Time IoT Imaging with Deep Neural
Networks - Using Java on the
Raspberry Pi 4” , Apress Publi cation , Year: 2020, ISBN:
9781484257210, 978148425722
3.Han Kamber, ―Data Mining Concepts and Techniques‖, Morgan
Kaufmann Publishers
4. Margaret. H. Dunham, ―Data Mining Introductory and Advanced
Topics, Pearson Education
5. Kevin P. Murphy , Machine Learning ― A Probabilistic Perspective‖
6. Samir Roy and Chakraborty, ―Introduction to soft computing‖,
Pearson Edition. 5 Richard Duda, Peter Hart, David G. Stork, ―Pattern
Classification‖, Second Edition, Wiley Publications.

Useful Digital Li nks
1 Data sets for Machine Learning algorithms:
tps://www.kaggle.com/datasets
2 Machine Learning repository - https://archive.ics.uci.edu/ml/index.php
3 Machine Learning from Coursera
4 https://towardsdatascience.com/machine -learning/home
5 https:/ /onlinecourses.nptel.ac.in/noc21_cs85/preview

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 questi ons 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 question s need to be answered.

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Course Code Course
Name Theory Practical Tutorial Theory Oral Tuto
rial Total
IoTCSBC70
2 Edge and
Fog
Computing 03 -- -- 03 -- -- 03

Course Code Course Name Examination Scheme
Theory Marks Term
Work Practical Oral Total
Internal assessment End
Sem.
Exam Test1 Test
2 Avg. of
2 Tests
IoTCSBC702 Edge and
Fog
Computing 20 20 20 80 -- -- -- 100

Course Objectives:

Sr. No. Course Objectives:
The course aims:
1 Understand the fundamentals of edge computing and its role in IoT systems.
2 Analyze and compare different edge computing architectures, platforms and frameworks.
3 Analyze and evaluate data processing at the edge and Edge analytics.
4 Understand the fundamentals of fog computing and its frameworks.
5 Demonstrate effective communication and collaboration skills in developing edge
computing projects.

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 basic concepts of Edge Computing and its
collaboration with Cloud Computing. L2

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2 Understand and identify edge computing architecture and various
platforms and frameworks and Demonstrate knowledge of
virtualization and containerization L3
3 To apply data processing capabilities along with edge analytics and
caching to process and extract insights from data at the edge L3
4 To understand the fundamentals of Fog computing and its
architecture. L3
5 To develop programming for fog computing -based applications and
frameworks. L4
6 To develop edge computing solutions for specific IoT use cases or
scenarios. L6

Prerequisite: Linear algebra, Probability theory and Basic statistics
Sr. No. Module Detailed Content Hours CO
Mapping
0 Prerequisite Basic concepts of Cloud Computing and
virtualization 02 --
I Introduction to
Edge Computing
and IoT Understanding Edge Computing: Evolution, Use
cases, advantages, disadvantages, Overview of edge
computing and its significance in IoT, Challenges
and opportunities in edge computing. Self-
Learning Topics: Edge devices and their
capabilities 07 CO1

II Edge Computing
Infrastructure
Edge computing architectures and components:
Requirements and views for Edge architecture,
Edge Computing Reference Architecture, critical
elements for Edge architecture, Challenges for Edge
application Development. Setting up Edge
computing environments: development tools,
python libraries. Edge computing platfo rms and
frameworks: AWS IoT Greengrass, Azure IoT
Edge, Google Cloud IoT Edge, IBM Edge
Application Manager, KubeEdge. Virtualization
and containerization for edge computing:
Introduction to Virtualization and containerization.
Advantages of Virtualization and Containerization
in Edge Computing. Resource Efficiency, Faster
Time to Market. Self-Learning Topics: Apache
Edgent, Eclipse ioFog. 09 CO2

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III Data Processing at
the Edge
Data Acquisition and Processing: Data handling,
python data handling, data storage and cloud
connectivity, Data Aggregation, Data
Timestamping and Synchronization, Data Security
and Privacy. Edge analytics and machine learning
at the edge: Introduction to Edge Analytics. Edge
Machine Learning. Model Selection and
Optimization. Co llaborative Edge Learning.
Resource management and task offloading
strategies: Task Offloading, Edge -Cloud
Collaboration, Dynamic Resource Provisioning.
Edge caching and data synchronization:
Introduction to Edge caching and data
synchronization, Benefits of Edge Caching and
Data Synchronization, Challenges in Edge Caching
and Data Synchronization. Self-Learning Topics:
Task Migration, Offline Operation, Bandwidth
Optimization . 07 CO3
IV Introduction to Fog
Computing Definition and basic concepts, Comparison with
cloud computing and IoT, Data Management in Fog
Computing. Comparison with cloud computing and
edge computing.
Fog Computing Architecture. Fog node and
infrastructure components. Hierarchical and
distributed models. Programming Models and T ools
for Fog Computing Self-Learning Topics:
Applications and integration of Fog Computing. 06 CO4
V Fog computing
programming
languages and
frameworks Middleware and software platforms. Development
and deployment considerations. Industrial Internet
of Things (IIoT). Performance Evaluation and
Metrics in Fog Computing. Simulation and
modelling techniques. Applications and Use Cases
of Fog Computing Self-Learning Topics:
Development environments and Frameworks for
programming in Fog Computing. 06 CO5
VI Applications and
Case Studies High -Potential Use cases, Edge computing for
smart cities. Industrial IoT and edge computing.
Edge computing in Healthcare.
03 CO6
Text Books:
1. “Fog and Edge Computing” by Rajkumar Buyya, Satish Narayana Srirama, Wiley Publications
2. "Edge Computing: Models, Technologies, and Applications" by Mung Chiang, Bharath
Balasubramanian, and H. Vincent Poor.
3. Edge Computing with Python: End -to-end Edge Applications, Python Tools and Techniques, Edge
Architectures, and AI Benefit” by Abhinandan Bhadauria, BPB publications.
4. “Edge Computing: Simply in Depth” by Ajit Singh,

Page 18

5. Edge Computing: Fundamentals, Advances and Applications (Advances in Industry 4.0 and Machine
Learning) by K. Anitha Kumari, G. Sudha Sadasivam, D. Dharani, M. Niranjanamurthy, CRC Press.
References:

1. "Edge Computing for IoT: Architectures and Applications" by Bharat Bhargav a, Sudip
Misra, Valentina E. Balas, and Raghvendra Kumar
2. "Practical Industrial Internet of Things Security: A practitioner's guide to securing
connected industries" by Sravani Bhattacharjee and Rajdeep Chowdhury
3. "Edge Computing: An Introd uction to the Next Generation of Networked Systems" by
Kiran Chitturi, Bharadwaj Veeravalli, and Satish Narayana Srirama
4. "Building the Web of Things: With examples in Node.js and Raspberry Pi" by Dominique
D. Guinard and Vlad M. Trifa
5. "Internet of Things (IoT): Technologies, Applications, Challenges, and Solutions" edited
by Balamuralidhar P., Bharadwaj Veeravalli, and V. Raghu
6. "Fog and Edge Computing: Principles and Paradigms" by Rajkumar Buyya, Satish
Srirama, and Pradeep Kumar S.
7. "IoT Fundamentals: Networking Technologies, Protocols, and Use Cases for the Internet of
Things" by David Hanes and Gonzalo Salgueiro
8. "Edge Analytics in IoT" by Shivashankar B. Nair, Siddhartha Bhattacharyya, and Thomas
Edward Joshua
9. "Edge Computing: The Convergence of Big Data and Internet of Things" by Samee U.
Khan, Albert Y. Zomaya, and Salman A. Baset

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
● Quest ion 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 needs to be answered.

Page 19

Course code Theory Practical Tutorial Theory Practical
/Oral Tutorial Total
IOTDO701
1 IoT for
Healthcare
Application 03 -- -- 03 -- -- 03

Subject Code Subject
Name Examination Scheme
Theory Marks
Term
Work Practical Oral Total Internal assessment End
Sem.
Exam Test
1 Test 2 Avg. of 2
Tests
IOTDO701
1 IoT for
Healthcare
Application 20 20 20 80 -- -- -- 100

Course Objectives: Six Course Objectives
1. To introduce basics of IoT in healthcare
2. To understand the IoT enabling technologies
3. To study various IoT in healthcare systems
4. To study various IoT supported medical products
5. To get familiarized with various security issues in healthcare IoT and the technologies used to overcome them
6. To learn various case studies for IoT in health care

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 describe basics of IoT in healthcare L1

2. To describe the IoT enabling technologies L2
3. To analyze various IoT enabled healthcare systems L3
4. To compare various IoT supported medical products L4
5. To identify various security issues in healthcare IoT and the technologies to o
overcome them L1
6. To evaluate various case studies for IoT in healthcare L4

Prerequisite: IoT Architecture, Protocols and Networking technologies, Wireless networks security, Basics of AI

DETAILED SYLLABUS:
Sr.
No. Module Detailed Content Hours CO
Mapping

Page 20

0 Prerequisite IoT Architecture, Protocols and Networking technologies,
Wireless networks security, Basics of AI 2 -
I Introduction Challenges in healthcare, Classification of IoT applications
in healthcare, Components of healthcare IoT, Advantages
and Risks 4 CO1
II Enabling IoT
Technologies
for Healthcare Sensors for Healthcare, WBAN, Cloud and Fog Computing,
Blockchain technology, AI for healthcare, Physically
Unclonable Function (PUF) Devices, SDN for IoT in
healthcare 8 CO2
III IoT systems in
Healthcare Ambient Assisted Living, Wearable devices, Community -
Based Healthcare Services, Cognitive Computing, Glucose
Level Monitoring, Oxygen Saturation Monitoring, Asthma
Monitoring, Mood Monitoring, Blood Pressure Monitoring,
Medication Management, Wh eelchair Management,
Rehabilitation System, Telemedicine, Chronic Disease
Detection and Prevention, Home and elderly healthcare 8 CO3
IV IoT supported
Medical
Products Best IoT applications in healthcare, Must -Have Apps for
Healthcare Professionals, IoT Applications in the
Connected Healthcare Space 6 CO4
V IoT Security
for Medical
Sector IoT security concerns, Key security issues, Security
architecture in IoT, Security Issues of IoT in Medical
Sector, Blockchain basics, Blockchain based security
mechanisms for IoT systems in healthcare 6 CO5
VI Case studies PUF-based Authentication for E -healthcare, SDN Enabled
E-healthcare, Blockchain Assisted Patient -Centric System,
Wearable IoT enabled real time health monitoring system 5 CO6
Text Books:
1. Sudip Misra, Anandarup Mukherjee, Arijit Roy, Introduction to IoT, Cambridge University Press
References:
1. IoT and Cloud Computing -Based Healthcare Information Systems, Edited by - Anand Sharma, Hiren Kumar
Deva Sarma, S. R. Biradar, CRC Press
2. Intelligent IoT Systems in Personalized Health Care, Edited by - Arun Kumar Sangaiah, Subhas
Mukhopadhyay, Elsevier
3. IoT and ICT for Healthcare Applications (EAI/Springer Innovations in Communication and Computing)
Edited by Nishu Gupta, Sara Paiva, 1st ed. 2020 Edition
Online References:
1. https://www.techscience.com/csse/v35n6/40719
2. https://www.tandfonline.com/doi/full/10.1080/02564602.2021.1927863
3. https://www.hindawi.com/journals/jhe/2021/6632599/
4. https://easternpeak.com/blog/int ernet -of-medical -things -applications -in-healthcare/
5. https://connecteam.com/apps -for-healthcare -professionals/
6. https://screencloud.com/blog/healthcare/iot -applications -healthcare -space
7. https://www.researchgate.net/publication/337910674_Security_Issues_of_In ternet_of_Thin
gs_in_Health -Care_Sector_An_Analytical_Approach

Page 21

8. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9003194/
9. https://www.tandfonline.com/doi/full/10.1080/02564602.2021.1927863
10. https://www.researchgate.net/publication/329868510_Wearable_IoT_enabled_r eal-
time_health_monitoring_system

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 syl labus
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.

Page 22

Subject
Code Subject Name Theor
y Practical Tutoria
l Theory Oral Tutorial Total
IOTDO
7012 Wearable
Computing
and IOE 03 -- -- 03 -- -- 03

Subject
Code Subject
Name Examination Scheme
Theory Marks Term
Wor
k Practical Oral Total Internal assessment End
Sem.
Exam Test
1 Test 2 Avg. of 2
Tests
IOTDO7012 Wearable
Computing
and IOE 20 20 20 80 -- -- -- 100

Course Objectives:
The course aims to,
1. Provide a basic understanding of evolution of IoE and its functional modules.
2. Understand advanced and emerging technologies in wearable computing.
3. Learn how to use software programs to perform varying and complex tasks.
4. Expand upon the knowledge learned and apply it to solve real world problems.

Course Outcomes:
On successful completion of the course students will be able to,

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 understands the basics of IoE L1

2. To Identify various wearable sensors and connecting technologies L1
3. To Design and develop IoE based wearable devices L3
4. To analyze wearable computing architecture for IoE devices L3
5. To analyze security and ethical issues related to Wearable devices L3
6. To identify the real world problem and provide IoE solutions through
wearable technology. L4

Prerequisite:

Page 23

Microcontroller and Embedded Systems
DETAILED SYLLABUS:
Sr.
No. Module Detailed Content Hours CO
Mappi
ng
0 Prerequisite Microcontroller and Embedded Systems , networking,
wireless Technologies 02 -
I Internet of
Everything What is IoE, How it is different than IoT, Industrial IoT,
Industry 4.O 03 CO1

II Introduction To
Wearable
Technologies Fundamentals of Wearable Technologies, History of
wearable Technologies, User Experience Design for IoE,
Social Aspects of Wearability, Internet of Everything –
Applications, Wearable Chemical and Biochemical Sensors,
Technology of Connected Devices (ZigBe e, Wi -fi, RFID,
etc.) 07 CO2

III Design
consideration for
Wearable
Computing Energy Expenditure and Energy Harvesting, Technology of
Connected Devices, Energy Considerations, Flexible
Electronics and Textiles for Wearable Technologies, Nano
devices 06 CO2
IV Wearable
Computing
Architecture Wearable Algorithms, Web of Things, Architecture
Standardization, Data Mining for Body Sensor Network,
Embedded Device UX Design, Electronic Health Records 08 CO3
V Security and
Ethical Issues in
wearable devices Security challenges and privacy, vulnerability analysis,
Security attacks on wearable systems, secure algorithms,
Ethical issues 07 CO5
VI Wearable
Computing Case
Studies Wearable Sensors for Monitoring of Physical and
Physiological Changes and for Early Detection of Diseases -
Wearable and Non -Invasive Assistive Technologies.
Real time applications of Wearable Technologies such as
Medical Applications, Banking applicatio n etc. 06 CO6

Text Books:
1. Giacomo Veneri, Antonio Capasso - Hands -On Industrial Internet of Things_ Create a
powerful Industrial IoT infrastructure using Industry 4.0 -Packt Publishing (2018)
2. “Wearable Sensors” by Edward Sazonov Released August 2014 Publisher(s): Academic
Press, O’Reilly Publication
3. “Fundamentals of IoT and Wearable Technology Design”, Haider Raad,
ISBN:9781119617532 |Online ISBN:9781119617570 |DOI:10.1002/9781119617570

Reference Books:
1. “Internet of Things”, Hands -on-Approach, Harshd eep Bahga, Vijay Madisetti, University
Press

Page 24

Online References:
1. Wearables -a-new-opportunity -in-banking – Cisco
2. https://codereality.net/wearable -computing/
3. Mohd Javaid, Abid Haleem, Ravi Pratap Singh, Shanay Rab, Rajiv Suman,Internet of
Behaviors (IoB) and its role in customer services, Sensors International,Volume 2, 2021,
100122, ISSN 2666 -3511, https://doi.org/10.1016/j.sintl.2021.100122
MOOC Courses:
1. https://www.mooc -list.com/tags/wearable -technology
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 diffe rent 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.

Page 25

Subject Code Subject
Name Theory Practical Tutorial Theory Practic
al/Oral Tutorial Total
IOTDO7013 Privacy
&
Security 03 -- -- 03 -- -- 03



Subject Code Subject
Name Examination Scheme
Theory Marks
Term
Work Practica
l Ora
l Total Internal assessment End
Sem.
Exam Test1 Test 2 Avg. of
2 Tests
IOTDO7013 Privacy &
Security 20 20 20 80 -- -- -- 100

Course Objectives:

1. To learn the fundamentals of the Internet of things and its applications.
2. To learn and illustrate the various Threats and Attacks associated with IOT.
3. To emphasis on the concept of Cryptographic Fundamentals for IoT.
4. To provide and maintain Trust and Authentication for IoT devices.
5. To discuss and learn various application areas of IOT in ensuring privacy of data.
6. To understand the concept of Cloud Security for IoT.


Course Outcomes:

On successful completion, of course, learner/student will be able to:


Prerequisite:

Computer Networks, Basics of Cryptography, Operating Systems

DETAILED SYLLABUS: 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 fundamentals of the Internet of things and its
applications. L2

2. Illustrate the various Threats and Attacks associated with IoT. L3
3. To Apply the concept of Cryptographic Fundamentals for IoT . L3
4. To Analyze Trust and Authentication for IoT devices. L3
5. Understand the various application areas of IoT in ensuring privacy of
data. L2
6. To Analyze the concept of Cloud Security for IoT . L3

Page 26

Sr.
No. Module Detailed Content Hours CO
Mapping
0 Prerequisite Basic concepts of Computer Network, Operating System 02
I Introduction:
Security the
Internet of
Things Security Requirements in IoT Architecture: Security in
Enabling Technologies, Security Concerns in IoT
Applications. Security Architecture in the Internet of Things:
Security Requirements in IoT, Insufficient
Authentication/Authorization, Insecure Access Control,
Threats to Access Control, Privacy and Availability: Attacks
Specific to IoT, The secure IoT system implementation
lifecycle. 06 CO1
II Threats and
Attacks Phases of IoT System, Internet of Things as Interconnections
of Threats (IoT vs. IoT), Phase attacks, Attacks as per
architecture: Wormhole Attack, Sinkhole Attack, Replay
Attack, IP Spoof Attack, Centrality Attacks, Network
Resilience, and Topological Defense Schem e, Sybil Attacks,
Malware Schemes in IoT 07 CO2
III Cryptographic
Fundamentals
for IoT Cryptography and its role in securing the IoT , Types and uses
of the cryptographic primitives in the IoT: Encryption and
decryption, Hashing , Digital signatures, Random number
generation, Cryptographic module principles , Cryptographic
key management fundamentals 07 CO3
IV Trust and
Authentication Trust and trust models for the IoT: Trust and security from a
device perspective, Secure key storage, Trust and security
from a network perspective, Trust Model Concepts,
Preventing Unauthorized access to sensor data: Cooperative
authentication, Cooperatio n incentive, Conflict balancing,
Authentication in IoT - Fundament of Authentication 07 CO4
V Privacy
Preservation for
IOT – Case
Studies and
Applications Network model, Threat Model, Overview of a Smart Building
Concept, Privacy Threats in Smart Buildings, Privacy -
Preserving Approaches in Smart Buildings, Smart Meter
Privacy -Preserving Approaches. 06 CO5
VI Cloud Security
for IoT Cloud services and the IoT:, Cloud IoT security controls:,
Tailoring an enterprise IoT cloud security architecture. 04 CO6

Text Books:
1. Shancang Li, Li Da “Securing the Internet of Things”, Syngress; 1st edition 2017.
2. Fei HU, “Security and Privacy in Internet of Things (IoTs): Models, Algorithms, and
Implementations”, CRC Press Taylor and Francis Group ,2016
3. Russell, Brian and Drew Van Duren, “Practical Internet of Things Security”, PACKT Publishing, 2016.

Page 27

References:
1. Brij B. Gupta, Aakanksha Tewari “A Beginner’s Guide to Internet of Things Security: Attacks,
Applications, Authentication and Fundamentals”, CRC Press Ta ylor and Francis Group, 2020.
2. Ollie Whitehouse, “Security of Things: An Implementers’ Guide to Cyber -Security for Internet of
Things Devices and Beyond”, NCC Group, 2014.
3. Tim Mather, Subra Kumaraswamy, and Shahed Latif ,” Cloud Security and Privacy”, Published by
O’Reilly Media, 2009.
Online References:
1. https://www.nptel.ac.in
2. https://swayam.gov.in
3. 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 diffe rent 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.

Page 28

Subject
Code Subject Name Theor
y Practical Tutoria
l Theor
y Practical
/Oral Tutoria
l Total
IOTDO7014 IoT for Smart
Cities 03 -- -- 03 -- -- 03

Subject
Code Subject
Name Examination Scheme
Theory Marks Term
Wor
k Practica
l Oral Total Internal assessment End
Sem.
Exam Test
1 Test 2 Avg. of 2
Tests
IOTDO7014 IoT for
Smart
Cities 20 20 20 80 -- -- -- 100
Course Objectives:
1. Understand the concept and significance of smart cities, and the various components and characteristics
that define them.
2. Explore the transformation of conventional cities into smart cities, and the parameters used to measure
their level of "smartness".
3. Understand the collaboration between drones and the Internet of Things (IoT) in smart cities, and the
implications for privacy, security, energy efficienc y, and public safety.
4. Develop an understanding of the system architecture design principles for IoT -based smart cities,
including domain analysis, reference architecture design, and deployment view.
5. Examine the development of Smart Seoul, including its inf rastructure, government/municipal -
developed services, citizen -developed services, and smart city standardization.
6. Analyze real -world case studies of smart city applications in the areas of parking, weather monitoring,
forest fire detection, and air polluti on monitoring.
Course Outcomes:
After the course students will be able to

Page 29

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 Define the concept of smart cities and explain their importance in
the modern world. L1, L2

2. Identify and describe the parameters used to measure the smartness
of cities. L2,L3
3. Propose energy -efficient solutions using drones and IoT in smart
cities. L3,L4
4. Evaluate the effectiveness of different architectural approaches for
IoT-based smart cities. L2,L3
5. Generate ideas for innovative applications and solutions to improve
smart city infrastructure and services based on the case study of
Smart Seoul. L1,L2
6. Critically assess the impact and potential risks associated with the
implementation of smart city solutions in various domains. L2,L3

Prerequisites:
IoT Architecture and Protocols, RFID and Microcontrollers, Wireless Sensor Technologies

DETAILED SYLLABUS:
Sr.
No. Module Detailed Content Hours CO
Mapping
0 Prerequisit
e IoT architecture, protocols, design stages, applications.
I Introductio
n to smart
cities Introduction, Characteristics of Smart Cities, Smart
Economy, Smart People Smart Governance Smart Mobility,
Smart Environment, Smart Living.

IoT-Based Solutions for Smart Cities , Smart Grid,Smart
Home, Transport and Traffic Management,Smart Healthcare

Challenges Ahead,Planning , Costs and Quality,Security and
Privacy, Risks. 3 CO1
II Journey
from
Convention
al Cities to
Smart
Cities Types of cities, Background of smart cities, Artificial
intelligence for smart cities, Smart cities indexed parameters,
Economy, Human capital, International outreach, Mobility
and transport, Environment, Technology, U rban
planning,Governance, Social cohesion, Infrastructure. 5 CO2
III Collaborati
ve drone
and IoT for
improving
the Overview of the collaboration between drones and the IoT,
privacy and security issues, energy efficiency, data 5 CO3

Page 30

smartness
of smart
cities. collection in smart cities, improving life quality, public
safety in smart cities, disaster management.
IV System
Architectur
e Design of
IoT-Based
Smart
Cities
Domain Analysis, Reference Architecture Design ,
Architecture Framework and Viewpoint Selection,
Decomposition View, Layered View, Deployment View.
Case Study of Smart EV Charging. 8 CO4
V Case study:
Smart
Cities
Seoul Smart Seoul, Smart Seoul Infrastructure,
Government/Municipal -developed Services,
Citizen -developed Services, NFC -based Mobile Payment,
Virtual Store,Smart City Standardization.

Artificial Intelligence Techniques for Smart City
Applications : Machine Learning Algorithms for Smart
Monitoring, Supervised Machine Learning Algorithms for
Smart Monitoring, Unsupervised and Hybrid Machine
Learning Algorithms for Smart Monitoring 7 CO5
VI
Case study
on smart
city
application
s Smart Parking,Weather monitoring, Forest fire detection, Air
pollution monitoring.
8 CO6

Text Books:
1. Internet of Things for Smart Cities: Technologies, Big Data and Security, WaleedEjaz,
AlaganAnpalagan, Springer briefs in electrical and computer engineering
2. Smart Cities and Construction Technologies, Edited by Sara Shirowzhan and Kefeng Zhang, Intech
open, Published in London, United Kingdom
3. Bahga, A. and Madisetti, V. (2015) Internet of Things: A Hands -On Approach., Universities Press.
References:
1. Green Internet of Things for Smart Cities, Concepts, Implications, and Challenges, Edited By Surjeet
Dalal , Vivek Jaglan, Dac -Nhuong Le, CRC Press, 2021
2. Smart Cities: The Internet of Things, People and Systems, Schahram Dustdar , Stefan Nastić ,
Ognjen Šćekić, Springer, 2017.
3. IoT for Sustainable Smart Cities and Society, Edited By Joel J. P. C. Rodrigues , Parul Agarwal ,
Kavita Khanna , Springer, 2022.
Online References:
1. Survey on Collaborative Smart Drones and Internet of Things for Improving Smartness of Smart
Cities, IEEE, https://ieeexplore.ieee.org/document/8795473

Page 31

2. System Architecture Design of IoT -Based Smart Cities, MDPI, https://www.mdpi.com/2076 -
3417/13/7/4173
3. Smart Cities Seoul, International Telecommunication Union, https://www.itu.int/dms_pub/itu -
t/oth/23/01/T23010000190001PDFE.pdf
4. Internet of Things for Sm art Cities, IEEE INTERNET OF THINGS JOURNAL, VOL. 1, NO. 1,
FEBRUARY 2014, https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=6740844
5. Artificial Intelligence Techniques for Smart City Applications, Proceedings of the 18th International
Conference on Com puting in Civil and Building Engineering, 2021, Volume 98, ISBN : 978 -3-030-
51294 -1


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 cover ed 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.

Page 32

Subject Code Subject
Name Theory Practical Tutorial Theory Practical
/Oral Tutorial Total
IOTDO7021 SDN &
NFV for
IoT 03 -- -- 03 -- -- 03

Subject
Code Subject Name Examination Scheme
Theory Marks
Term
Work Practical Oral Total Internal assessment End
Sem.
Exam Test1 Test 2 Avg. of 2
Tests
IOTDO702
1 SDN & NFV
for IoT 20 20 20 80 -- -- -- 100
Course Objectives:
Sr. No. Course Objectives
The course aims:
1 Understand the fundamentals of SDN and NFV.
2 Study the functionalities, and the protocols of SDN controllers.
3 Understand SDN/NFV integration to create agile and flexible network architectures.
4 Study the SDN/NFV deployment models.
5 Analyze the security challenges and solutions specific to SDN and NFV environments.
6 Investigate SDN/NFV use cases.

Course Outcomes: On successful completion of course, learners/students will be able to:

Page 33

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 concept of SDN with respect to its approach, differences and benefits
over traditional network management. L1

2. Describe the relationship between SDN and NFV and their role in network
infrastructure. L2
3. Explain the concept of NFV. L3
4. Analyze performance bottlenecks in virtualized network environments and
propose optimizations. L4
5. Explain the security issues in SDN and NFV. L2
6. Create solutions to address complex challenges in SDN/NFV security, scalability,
or performance. L3

Prerequisite: Basic networking concepts, TCP/IP protocol. Basics of virtualization. OpenStack architecture.
DETAILED SYLLABUS:
Sr.
No. Module Detailed Content Hours CO
Mappin
g
0 Prerequisite Networking fundamentals, Knowledge of OSI and TCP/IP model.
Familiarity with virtualization concepts. Familiarity with cloud
computing concepts.
02
I Basics of
Modern
Networking Evolution of traditional networking architectures. Motivation and
benefits of SDN and NFV. Relationship between SDN, NFV, and IoT.
Introduction to cloud computing, Types of networks and Internet traffic.
Requirements of Big Data, Cloud computi ng and Mobile traffic in terms
of QoS, QoE, Routing and congestion control.

Self-learning Topics: Introduction to Modern Networking Elements.
Genesis of SDN and NFV.

04

CO1
II Software
Defined
Networks
Problem of modern networks. Definition of Software Defined
Networking (SDN). Flavors of SDN. SDN concepts and architecture.
SDN controllers and switches.

SDN -enabled IoT network design and deployment. OpenFlow protocol –
Overview, Basic functionality, Messages, OpenFlow as fundamental
protocol for SDN, OpenFlow limitations. Protocols competing with
OpenFlow. Centralized and distributed controls and data planes.
Architecture of NOX and POX. SDN in the data center.

Self-learning Topics: Data center defi nition, Data center needs and
demands, Tunneling and path technologies in data center, Real world
implementations.



08



CO2

Page 34

III Virtualizatio
n NFV concepts and architecture. Virtualization technologies (e.g.,
hypervisors, containers). NFV -enabled IoT service provisioning and
orchestration.

NFV management and orchestration (MANO), NFV infrastructure
(NFVI). Network programming – Network function virtualization,
NetApp development, Network slicing.

NFV systems - Ciena Agility, Intel, Cisco Evolved Services Platform
(ESP), Open Platform for NFV (OPNFV), NFV specifications.

Network management and orchestration frameworks (e.g., OpenStack,
ONAP) .

Self-learning Topics: Service chaining and function composition in
SDN/NFV -based IoT. Service lifecycle management and service
assurance.


08


CO3
IV Components
of Internet
of Things Scope of IOT. IOT Enabled Things, IOT world forum reference model,
IOTivity. CISCO -IoT systems, ioBridge. SDN and NFV over IoT
deployment.
SDN/NFV -enabled edge computing for IoT.

Self-learning Topics: Edge computing concepts and architectures.
Edge in telligence and analytics in SDN/NFV -based IoT.

06

CO4
V Security Security requirements – Introduction to security in SDN and NFV. ETSI
security perspective. IOT security – The patching vulnerability. IOT
security and privacy requirements.

Introduction to ITU -T. The impact, advantages and disadvantages of
SDN and NFV. IoT security challenges and threats.

Self-learning Topics: SDN/NFV -based security solutions for IoT.
Privacy considerations and data protection in IoT.

06

CO5

VI Applications
and Use
Cases Future of SDN and NFV - Standards bodies, Evolving standards, Novel
applications. SDN applications. SDN Use Cases – The open network
operating system. Real -world deployments of SDN/NFV in IoT.

Self-learning Topics: Projects inv olving SDN/NFV for IoT. Research
and emerging trends in SDN/NFV -based IoT.

05

CO6

Text Books:
1. William Stallings, “Foundations of Modern Networking: SDN, NFV, QoE, IOT and Cloud” Addison -
Wesley 2015.
2. Paul Goransson and Chuck Black, “SDN: A Comprehensive Approach”, Morgn Kaufmann 2014.
3. Siamak Azodolmolky, “SDN with OpenFlow” Packt Publishing.
4. Jim Doherty, “SDN and NFV Simplified: A Visual Guide to Understanding Software Defined Networks
and Net work Function Virtualization” 1st Edition.
References:
1. Rajendra Chayapathi, Syed Farrukh Hassan, Paresh Shah, “Network Functions Virtualization (NFV)
with a Touch of SDN” Addison -Wesley.

Page 35

2. Nick Feamster, Jennifer Rexford, Ellen Zegura, “The road to SDN : an intellectual history of
programmable networks” ACM SIGCOMM Computer Communication Review Volume 44Issue 208 April
2014pp 87 –98.
3. Rahamatullah Khondoker , “SDN and NFV Security”, Springer Publication.
4. Shao Ying Zhu, “Guide to Security in SDN and N FV: Challenges, Opportunities, and Applications”,
Springer Publication.
Online References:
1. SDxCentral (https://www.sdxcentral.com/)
2. European Telecommunications Standards Institute (ETSI) NFV Portal
(https://www.etsi.org/technologies/nfv)
3. VMware Learning Zone (https://www.vmware.com/education -services/learning -zone/sdn -nfv.html)
4. OpenStack (https://www.openstack.org/)
5. Open Networking Foundation (ONF) (https://www.opennetworking.org/)
6. Open Networking Foundation (ONF) (https://www.youtube.com/user/OpenNetwork ing)
7. Cisco DevNet (https://www.youtube.com/c/CiscoDevNet)
8. VMware (https://www.youtube.com/user/vmwaretv)

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 shoul d 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 randoml y selected from all the modules).
● A total of four questions need to be answered.

Page 36

Subject Code Subject Name Theory Practical Tutoria
l Theory Practical/
Oral Tutoria
l Total
IOTDO7022 Blockchain
for IoT 03 -- -- 03 -- -- 03

Subject
Code Subject Name Examination Scheme
Theory Marks
Term
Work Practical Oral Total Internal assessment End
Sem.
Exam Test1 Test 2 Avg. of 2
Tests
IOTDO7022 Blockchain for
IoT 20 20 20 80 -- -- -- 100

Course Objectives:
The course aims at:
1. To understand the fundamentals of blockchain, cryptocurrencies, their characteristics and examples.
2. To understand public blockchains, differentiate between Bitcoin and Ethereum.
3.To understand smart contracts and Solidity programming.
4. To understand private blockchains and Hyperledger.
5. To understand the architecture of an IoT -based ecosystem.
6. To understand the development of IOT solutions with blockchain.
Course Outcomes: On successful completion, of course, learner/student will be able to:
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 fundamentals of blockchain, cryptocurrencies, their
characteristics and examples. L1

2. Compare Bitcoin and Ethereum blockchains. L2
3. Execute smart contracts using Solidity. L3
4. Define private blockchains and Hyperledger. L1
5. Apply architecture of an IoT -based ecosystem L3
6. Design IOT solutions with blockchain. L6

Prerequisite: Blockchain Technology, IoT
DETAILED SYLLABUS:

Page 37

Sr.
No. Module Detailed Content Hours CO
Mapping
0 Prerequisite Fundamentals of Distributed Systems, Cryptography, Hashing
(SHA), Public and Private Keys, Digital Signatures 02
I Introduction
to
Blockchain Defining blockchain, Origin of blockchain (cryptographically
secure hash functions), Blockchain architecture, Generic
elements of a blockchain: Address, Transaction, Block -
previous block hash (hash pointer), timestamp, and nonc e,
Merkle root, Blockchain functionality: Consensus, Types of
blockchain: Distributed ledger, Shared ledger, Public, Private,
and Consortium/Federated blockchain, Benefits and features of
blockchain, Limitations of blockchain technology.
Cryptocurrency :I ntroduction to cryptocurrency, Characteristics
of cryptocurrency, Cryptocurrency wallets, Cryptocurrency
usage, Fork and its types, Examples of cryptocurrencies:
Bitcoin, Altcoin, and Tokens.
Self-study: Blockchain Demo, Defi, Metaverse 07 CO1
II Public
Blockchain:
Bitcoin and
Ethereum Bitcoin blockchain: Introduction to Bitcoin, Consensus
mechanism in Bitcoin, Bitcoin PoW system, Double spending
problem, difference between PoW, PoB, and PoS, PoET, UTXO
model of Bitcoin, Life of a miner, Mining difficult y, Mining
pool and its methods.
Ethereum blockchain: Ethereum and its components, EVM,
Mining in Ethereum, Transactions, Accounts, Architecture and
Workflow
Comparison between Bitcoin and Ethereum
Self-study: Blockchain Explorer: Bitcoin Tracker, Etherscan .io 07 CO2
III Smart
Contracts
and
Blockchain
Programmi
ng using
Solidity Introduction to smart contracts: Definition, properties, and real -
world applications, Ricardian contracts, Smart contract
templates/structure of a smart contract, smart contract
approaches, limitations of smart contract, Oracles and its types,
Decentralized autonomous organization.

Solidity Programming: Basics, functions (fall back function),
visibility (public, private, internal and external) and activity
(constant, view, pure, and payable) qualifiers, address and
address payable, data types in solidity, arrays (fixed and
dynamic), special dynamically sized arrays, inheritance and its
types, error handling (require, assert, revert)

Self-study: Advances in smart contract technolo gy (Solana
Sealevel, Digital Asset Modeling Language) 08 CO3
IV Private
Blockchain:
Hyperledger Introduction to Private Blockchain, Key Characteristics, Need of
a Private Blockchain, Smart contract in a Private Blockchain,
Consensus mechanism (PAXOS and RAFT), Byzantine Faults:
BFT and pBFT

Hyperledger: Introduction to Hyperledger, Tools and
Framewo rk, Hyperledger Fabric Architecture, Components of
Hyperledger Fabric: MSP, Chain Codes, Transaction Flow,
Working of Hyperledger Fabric
07 CO4

Page 38

Self-study: Case Study of Supply Chain Management using
Hyperledger
V Convergenc
e of
Blockchain
and IoT IoT devices (sensors, actuators, chips) and their functionalities
such as sensing, reacting, collecting, and communicating,
Typical architecture of an IoT -based ecosystem, IoT layered
model, Benefits of IoT and blockchain convergence, Layered
blockchain -based IoT model, Implementing blockchain -based
IoT. Role of blockchain in machine to machine communication.

Self-study: Blockchain applications in government, finance,
media, and healthcare, IOTA 04 CO5
VI IoT
Solutions
with
Blockchain Creating a blockchain network: Concepts and enumerations,
asset definitions, participants, manipulating assets via
transactions, generating and exporting participant business
cards, defining ACLs. Creating IOT Solution: hardware setup,
firmware development, application developm ent. End -to End
Testing.

Self Study: The IOT, Blockchain and Industry 4.0 06 CO6

Text Books:
1. Blockchain Technology, Chandramouli Subramanian, Asha A. George, Abhillash K. A and Meena
Karthikeyen, Universities Press.
2. Mastering Blockchain by Imran Bashir (4th Edition) (2023)
3. Mastering Ethereum, Building Smart Contract and Dapps, Andreas M. Antonopoulos Dr. Gavin Wood,
O’Reilly.
4. Mastering Bitcoin, Programming the Open Blockchain, 2nd Edition by Andreas M. Antonopoulos, June
2017, Publisher(s): O’Reilly Media, Inc. ISBN: 9781491954386.
5. Hyperledger Fabric In -Depth: Learn, Build and Deploy Blockchain Applications Using Hyperledger
Fabric by Ashwani Kumar, BPB publications
6. Solidity Programming Essentials: A beginner’s Guide to Build Smart Cont racts for Ethereum and
Blockchain by Ritesh Modi, Packt publication
7. Hands -On IoT Solutions with Blockchain by Maximiliano Santos, Enio Moura, Packt publication.
References:
1. Blockchain Technology: Concepts and Applications, Kumar Saurabh and Ashutosh Saxena, Wiley.
2. The Basics of Bitcoins and Blockchains: An Introduction to Cryptocurrencies and the Technology that
Powers Them (Cryptography, Crypto Trading, Digital Assets, NFT) by Antony Lewis (2018)
3. Blockchain for Beginners, Yathish R and Tejaswini N, SPD
4. Blockchain Basics, A Non -technical Introduction in 25 Steps, Daniel Drescher, Apress.
5. Blockchain with Hyperledger Fabric, Luc Desrosiers, Nitin Gaur, Salman A. Baset, Venkatraman
Ramakrishna, Packt Publishing
Online References:

Page 39

1. Blockchain for Business, https://www.ibm.com/downloads/cas/3EGWKGX7.
2. NPTEL: https://onlinecourses.nptel.ac.in/noc19_cs63/preview
3. Hyperledger: 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) 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.

Page 40

Subject Code Subject Name
Theory Practical Tutorial Theory Oral Tutorial Total
IOTDO7023 Enterprise IoT
Cyber Security 03 -- -- 03 -- -- 03

Subject
Code Subject
Name Examination Scheme
Theory Marks
Term
Work Practical Oral Total Internal assessment End
Sem.
Exam Test1 Test 2 Avg. of 2
Tests
IOTDO
7023 Enterprise
IoT Cyber
Security 20 20 20 80 -- -- -- 100

Course Objectives: The course aims:
1. To learn fundamentals of Enterprise IoT, vulnerabilities, attacks and countermeasures for IoT systems.
2. To gain knowledge in security engineering for IoT development and lifecycle.
3. To understand the cryptographic fundamentals for IoT security engineering.
4. To develop a comprehensive understanding of challenges and solutions in secured identity management.
5. To gain knowledge of the different privacy r egulations and compliance requirements .
6. To analyze various case studies and applications for Enterprise IoT.

Course Outcomes: On successful completion of course, learner/student will be able to:
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 Discuss fundamentals of Enterprise IoT, vulnerabilities, attacks and threats in IoT
systems L2

2. Illustrate IoT security life cycle L4
3. Examine various cryptographic controls for IoT protocols. L4
4. Evaluate the identity and access management solution for IoT security. L5
5. Identify applicable privacy regulations and compliance requirements for data in
IoT environments L2
6. Evaluate various case studies and applications for Enterprise IoT L5

Prerequisite: Knowledge of IoT and Cryptography
DETAILED SYLLABUS

Page 41

Sr. No. Module Detailed Content Hours CO
Mapping
0 Prerequisite Basics of IoT and cryptography 2
I INTRODUCTION TO
ENTERPRISE IOT
CYBER SECURITY Fundamentals of IOT in Enterprise, IoT device lifecycle.
Security Requirements in IoT Architecture, Security in
Enabling Technologies.
Primer on threats, vulnerability and risks (TVR), Primer on
attacks and countermeasures .
Today’s IoT attacks.
Self Learning Topics : Threat modeling an IoT System. 5 CO1
II IOT SECURITY
ENGINEERING AND
DEVELOPMENT Building security into design and development - Security in
Agile developments
Secure design - Safety and security design, Proces s and
agreements, Technology selection – security products and
services
IoT security lifecycle – Implementation and integration,
operations and maintenance, Dispose.
Self Learning Topics: Cyber attack on Industrial control
system, ransomware attack on healthcare enterprise
“Wannacry” case study 7 CO2
III CRYPTOGRAPHIC
FUNDAMENTALS
FOR IOT SECURITY Cryptographic primitives and its role in securing the IoT.
Cryptographic module principles, key managemen t
fundamentals.
Cryptographic controls built into IoT communication and
messaging protocols
IoT Node Authentication
Self Learning Topics: Future directions of IoT and
Cryptography (Including blockchain for IoT security) 6 CO3
IV IDENTITY & ACCESS
MANAGEMENT
SOLUTIONS FOR
SECURE IOT Identity lifecycle
Authentication credentials – Passwords, Symmetric keys,
Certificates, Biometrics
IoT IAM infrastructure –802.1X, PKI for IoT
Authorization and access control – OAuth 2.0, publish/
subscribe protocols and communication protocols
Self Learning Topics: Authentication and authorization
framework of IIoT 6 CO4
V MITIGATING IOT
PRIVACY CONCERNS
AND COMPLIANCE
MONITORING Privacy challenges introduced by the IoT, Performing an IoT
Privacy Impact Assessment (PIA) , Privacy by Design (PbD)
principles, Privacy engineering recommendations
IoT Compliance, challenges associated with IoT compliance,
examining compliance standard support for IoT
Self Learning Topics: Differential privacy in Industrial IoT 7 CO5
VI ENTERPRISE IOT: CASE
STUDIES AND
APPLICATION Cleaning Service Industry and Technology, Global Cold Chain
Management, Intelligent Lot Tracking, Industrial Internet
Consortium Testbeds 6 CO6


Text Books:
1. "Enterprise IoT: Strategies and Best Practices for Connected Products and Services" by Dirk Slama, Frank
Puhlmann, Jim Morrish, and Rishi M. Bhatnagar, O′Reilly

Page 42

2. “Practical Internet of Things Security” by Brian Russell, Drew Van Duren, and John Sammons, PACKT
Publishing
3. "Securing the Internet of Things" by Shancang Li, Li Da Xu, and Liming Chen, SYNGRESS

References:
1. Security and Privacy in Internet of Things (IoTs) Models, Algorithms, and Implementations by FEI HU,
CRC Press
2. Security, Privacy and Trust in the IoT Environment by Zaigham Mahmood, Springer, ISBN:
9783030180744, 2019.
3. Ollie Whitehouse, “Security of Things: An Implementers’ Guide to Cyber -Security forInternet of Things
Devices and Beyond”, NCC Group, 2014
4. “Practical Industrial Internet of Things Security”, By Sravani Bhattacharjee, PACKT Publishing.
Online References:

1. https://www.coursera.org/learn/iot -cyber -security
2. https://www.edx.org/course/cybersecurity -and-privacy -in-the-iot

Assessment:
Internal Assess ment (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.

Page 43

Course
Code Subject Name Theory Practical Tutorial Theory Practical
/Oral Tutorial Total
IOTDO7024 Software
Engineering &
Testing
Methodology
for IoT 03 -- -- 03 -- -- 03

Subject
Code Subject Name Examination Scheme
Theory Marks
Term
Work Practic
al Oral Total Internal assessment End
Sem.
Exam Test1 Test 2 Avg. of
2 Tests
IOTDO
L7024 Software
Engineering
& Testing
Methodolog
y for IoT 20 20 20 80 -- -- -- 100

Course Objectives:
1. To provide the knowledge of the new process models and trends for IoT based software engineering
practices.
2. To acquire skills on web based IoT application development
3. To gain the ability to identify the challenges in IoT to automate the real -time problems.
4. To acquire knowledge about various software test planning and techniques for IoT.

Course Outcomes: On successful completion of course, learners will be able to:

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 Apprehend new process models and trends for IoT based software
engineering practices. L1

2. Design and model an IoT system using UML diagrams. L3,L4
3. Understand the challenges in IoT to automate the real -time
problems. L1, L2
4. Understand IoT based testing concepts and challenges. L1,L2
5. Identify different IoT testing planning and strategies. L1,L2
6. Explore various IoT testing techniques. L3,L4

Prerequisite:
Software Engineering , IoT Architecture and Protocols
DETAILED SYLLABUS

Page 44

Sr.
No. Module Detailed Content
Hours CO
Mapping
0 Prerequisite Process models in Software Engineering: Prescriptive,
evolutionary, and agile process models, UML Diagrams, IoT
devices and protocols. 2
I IoT Based
Software
Engineering New process model for IoT based Software Engineering:
Introduction, Layers of IoT, IoT based SDLC, Identifying
Business needs through IoT, IoT in various domains.
Introduction to trends in integrating IoT into Software
Engineering practices : DevOps in IoT, DevSecOps in IoT,
Integrating security into IoT, Machine Learning and AI in
IoT of Software Engineering practices. 6 CO1
II Modelling &
Design of IoT
System Modeling of IoT system using UML diagrams: IoT
Software Engineering, UML representations of IoT
Systems: Use case diagram, class diagram, interaction
diagrams, and physical diagrams,
Architecture design of IoT system, Cryptographic
approaches, Machine Learning approaches.
8 CO2
III Web Based IoT
Application
Development Introduction to web based IoT application
development , IoT layered architecture for web
application development, challenges of IoT application
development, End -to-end complete IoT Solution. 5 CO3
IV Introduction to
IoT Testing Challenges in IoT Testing , advanced IoT device
challenges, IoT development -test-security -operation
lifecycle, Verification & Validation testing concepts,
factors and keys for IoT testing. 4 CO4
V IoT Test
Planning &
Strategy Basics of IoT Test Planning , IoT test planning &
strategy for hardware & software, Agile/DevOps test
lifecycle, Product and Development Lifecycle Impacts
on Test Planning – DevOps and Agile, V & V activities,
IoT test planning: Regression test cases, OTS hardware
and software, Secur ity and critical quality factors, IoT
strategy. 8 CO5
VI IoT Testing
Techniques and
Practices Techniques, practices, levels and types of testing to
apply to IoT , Functional test design techniques,
Exploratory testing, structural testing, industrial test
practices, IoT levels of testing related to lifecycle
phases, test planning for Agile Team. 6 CO6

Text Books:
1. Jon Duncan Hagar, IoT System Testing: An IoT Journey from Devices to Analytics and the Edge, Apress
2022.
2. D. Jeya Mala, Integrating the Internet of Things into Software Engineering Practices , IGI Global 2019.
References:
1. Sudham Sudhakar, Testing IoT: Build and Implement Test Automation and Performance Testing for IoT
Systems .
2. Aaron Guzman, Aditya Gupta, IoT Penetration Testing Cookbook: Identify vulnerabilities and secure your
smart devices Paperback – Import, 29 November 2017.
3. Yogesh Singh, Software Testing, Cambridge University Press, 2012.
4. Mauro Pezze, Michal Young: Software Testing and Analysis – Process, Principles a nd Techniques , Wiley
India, 2009.

Page 45

5. Haengkon Kim, Roger Lee, Software Engineering in IoT, Big Data, Cloud and Mobile Computing, Springer
Nature, 2020.

Online References:
1. https://bytebeam.io/blog/iot -software -testing -guide/
2. www.omg.org/spec/UML/2.5.1/About -UML/
3. https://www.softwaretestinghelp.com/internet -of-things -iot-testing/
4. https://www.techarcis.com/whitepapers/security -testing -in-iot/
5. https://dl.acm.org/doi/abs/10.1145/3356317.3356326
6. https://yalantis.com/blog/iot -testing -guide/



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 questio ns 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.

Page 46

Course
Code: Course Title Credit
IOTL701 Machine Learning and IOT Lab

Lab Objectives: The course will help the students to:

1. To understand the concepts of ML and IOT.
2. To learn and apply ML techniques for IoT data sets.
3. To practice various ML platforms.
4. To analyze & illustrate various ML techniques.
5. To demonstrate the ML and IOT applications.
6. To familiarize with the MLops life cycle.


Lab Outcomes: Upon Completion of this course, the learner should be able to:

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 Understand the concepts Machine Learning and IOT L2

2. Explore with various data science platforms. L2
3. Demonstrate different ML libraries and tools. L3
4. Experiment Machine Learning Algorithms on given data sets. L4
5. Analyze the various ML techniques. L4
6. Apply MLops tools for ML application development. L3



SR.
NO
List of experiments:
Lab Outcome
1
Introduction to platforms such as Anaconda, COLAB LO1
2 Study of Machine Learning Libraries and tools (Python library, tensorflow,
keras,...) LO2,LO3
3 Implementation of following algorithms for a given example data set :
Linear Regression.
LO3,LO4,
LO5
4 Implementation of following algorithms for a given example data set :
Logistic Regression.
- LO3,LO4,
LO5
5 Implementation of following algorithms for a given example data set : LO3,LO4,

Page 47

Support Vector Machines
LO5
6 Implementation of following algorithms for a given example data set :
Hebbian Learning
LO3,LO4,
LO5
7 Implementation of following algorithms for a given example data set :
Expectation -Maximization algorithm
LO3,LO4,
LO5
8 Implementation of following algorithms for a given example data set :
McCulloch Pitts Model.
- LO3,LO4,
LO5
9 Implementation of following algorithms for a given example data set :
Single Layer Perceptron Learning algorithm
LO3,LO4,
LO5
10 Implementation of following algorithms for a given example data set : Error
Backpropagation Perceptron Training Algorithm
LO3,LO4,
LO5
11 First 4 phases of MLops life cycle -
- ML Developments,
- Model Training
- Model Evaluation,
- Model Deployment LO6
12
5-7 phases of MLops –
- Prediction Serving,
- Model Monitoring,
- Data and Model Management
LO6

Note : Data used for this lab should be collected with the help of different sensors (at least 5).

Text Books
1. Peter Harrington, ―Machine Learning n Action‖, DreamTech Press
2. Ethem Alpaydın, ―Introduction to Machine Learning‖, MIT Press
3. Tom M. Mitchell, ―Machine Learning‖ McGraw Hill
4. Stephen Marsland, ―Machine Learning An Algorithmic Perspective‖, CRC
Press
5 : Neeraj Kumar, Aaisha Makkar, “ MACHINE LEARNING IN COGNITIVE
IOT”, https://www.routledge.com/Machine -Learning -in-Cognitive -
IoT/Kumar Makkar/p/book/9780367359164 ISBN 9780367359164 Published
June 1, 2020 by CRC Press
Reference Books

Page 48

1.Puneet Mathur, “ IoT Machine Learning Applications in Telecom, Energy,
and Agriculture,
With Raspberry Pi and Arduino Using Python”, ISBN 978 -1-4842 -5549 -0
2. Nicolas Modrzyk, “ Real -Time IoT Imaging with Deep Neural Networks -
Using Java on the
Raspberry Pi 4” , Apress Publication , Year: 2020, ISBN: 9781484257210,
978148425722
3.Han Kamber, ―Data Mining Concepts and Techniques‖, Morgan Kaufmann
Publi shers
4. Margaret. H. Dunham, ―Data Mining Introductory and Advanced Topics,
Pearson Education
5. Kevin P. Murphy , Machine Learning ― A Probabilistic Perspective‖
6. Samir Roy and Chakraborty, ―Introduction to soft computing‖, Pearson
Edition. 5 Richard Duda, Peter Hart, David G. Stork, ―Pattern Classification‖,
Second Edition, Wiley Publications.

References:

1. https://www.packtpub/product/hands -on-artificial -intelligence -for-iot/9781788836067
2. https://it.mitindia.edu/PDF/books/ml1.pdf
3. https://www.perlego.com/book/1491982/machine -learning -and-iot-a-biological -perspective -pdf
4. https://media -exp1.licdn.com/dms/document/C4E1FAQE8SeLwleYzqA/feedshare -document -
pdf-
analyzed/0/1650189848484?e=2147483647&v=beta&t=OGnNH7tasNrvlEjV7h99wyWF3DY6
QcaTT Vg2-IdsJiE

Term Work:
1. Term work should consist of 10 experiments
2. Journal must include at least 2 assignments based on Theory and Practical
3. The final certification and acceptance of term work ensures satisfactory performance of laboratory
work and minimum passing marks in term work.
4. Total 25 Marks (Experiments: 15 -marks, Attendance Theory & Practical: 05 -marks, Assignments:
05-marks)

Oral exam: Based on the entire syllabus of Machine Learning & IoT theory and lab

Page 49

Subject
Code Subject Name Theory Practical Tutorial Theory Practical
& Oral Tutorial Total
IOTL703 DevOps Lab -- 2 -- -- -- -- 01

Subject Code Subject Name Examination Scheme
Theory Marks
Term
Work Practica
l &
Oral Total Internal assessment End
Sem.
Exam Test1 Test 2 Avg. of
2 Tests
IOTL703
DevOps Lab -- -- -- -- 25 25 50

Lab Objectives: The course will help the students to
● To understand the concept of distributed version control.
● To familiarize with Jenkins build & test software Applications & Continuous integration.
● To understand Docker to build, ship and run containerized images.
● To familiarize with the concept of Software Configuration Management & Continuous Monitoring.
● To understand the basics of Static Application security testing.
● To familiarize with the concept of Cloud and Infrastructure as a Code.
Lab Outcomes: Upon Completion of this course, the learner should be able to:

Page 50

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 Understand the concepts of distributed version control using GIT
and GITHUB L1

2. Apply Jenkins to Build, Deploy and Test the Software
Applications L3,L4
3. Analyze & Illustrate the Containerization of OS images and
deployment of applications over Docker L2,L3
4. Deploy and Examine the Software Configuration management
using Ansible and Continuous monitoring using Nagios L3
5. Use Sonarqube to perform code quality checks. L1,L2
6. Implement Terraform scripts to manage VMs on a cloud. L3,L4

Detailed Syllabus
Sr.
No. Module Detailed Content Hours LO
Prerequisite Concept of DevOps with related technologies which are
used to Code, Build, Test, Configure & Monitor the
Software Applications. 02
I Version Control
using GIT To Perform Version Control on documents/files websites/
Softwares using GIT & GITHUB that covers all GIT
commands given in GIT cheat sheet
1. To implement Version control for different
files/directories using GIT
2. To implement version control using GITHUB to
sync local GIT repositories and perform various
related operation s. 04 LO 1
II Working with
Jenkins 3. To deploy and test Java/web/Python application on
jenkins server
4. To implement Jenkins pipeline using
scripted/declarative pipeline
5. To use jenkins to deploy and run test cases for
Java/Web application using Selenium/JUnit
6. To implement jenkins Master/Slave architecture 06 LO 2

Page 51

III Containerizatio
n 7. To use docker to run containers of different
applications and operating Systems
8. To create a custom docker image using Dockerfile
and upload it to the docker hub. 04 LO 3
IV
Software
Configuration
Management
and Continuous
Monitoring 9. To implement continuous deployment using Ansible
10. To implement continuous monitoring using
Splunk/ NagiOS 04 LO 4
V Static
Application
Security Testing 11. To implement Static Application Security Testing
using SonarQube 02 LO 5
VI Cloud and
Infrastructure as
a code 12. To create and work with virtual machine on cloud
(GCP / AWS / Azure)
13. To implement terraform script for deploying
infrastructure on cloud platforms (GCP / AWS /
Azure) 04 LO 6

Text Books:
1. Prem Kumar Ponuthorai, Jon Loeliger, Version Control with Git, 3rd Edition,O'Reilly Media.
2. John Ferguson Smart,”Jenkins, The Definitive Guide”, O'Reilly Publication.
3. Karl Matthias & Sean P. Kane, Docker: Up and Running, O'Reilly Publication.
4. Russ McKendrick , Learn Ansible, Pakt Publication
5. Yevgeniy Brikman, Terraform: Up and Runni ng, 3rd Edition, O'Reilly Publication.
6. G. Ann Campbell ,SonarQube in Action,First Edition, Manning publication.
References:
1. Sanjeev Sharma and Bernie Coyne,”DevOps for Dummies”, Wiley Publication
2. Httermann, Michael, “DevOps for Developers”,Apress Publication.
3. Joakim Verona, “Practical DevOps”,Pack publication

Term Work:
1 Term work should consist of experiments
2 Journal must include at least 2 assignments based on Theory and Practical

Page 52

3 The final certification and acceptance of term work ensures satisfactory performance of
laboratory work and minimum passing marks in term work.
4 Total 25 Marks (Experiments: 1 5-marks, Attendance Theory & Practical: 05 -marks,
Assignments: 05 -marks)

Oral exam:
Based on the entire syllabus of DeVOPs Lab IOTL703

Page 53

Subject Code Subject
Name
Teaching Scheme
(Contact Hours)
Credits Assigned
Theory Practical Tutorial Theory Oral Tutorial Total
IoTCSBCL702
Edge and
Fog
Computing
Lab -- 2 -- -- 1 -- 1

Subject Code Subject
Name Examination Scheme
Theory Marks Term
Work Oral Total
Internal assessment End
Sem.
Exam
Test1 Test
2 Avg. of
2 Tests
IoTCSBCL702 Edge and Fog
Computing
Lab
-- -- -- -- 25 25 50

Lab Objectives:
Sr. No. Lab Objectives
1 To study the concepts of virtual servers and AWS Edge platforms
2 To get acquainted with different Aws IoT Core Services.
3 To learn message passing between AWS IoT Core devices
4 To study different simulators and development of Edge Computing networks
5 To study different simulators and development of FogComputing networks

Lab Outcomes:

Page 54

Sr. No. Lab Outcomes Cognitive Levels
of Attainment as
per Bloom’s
Taxonomy
On successful completion of the course students will be able to,
1 Understand the concept of virtual servers deployed on AWS Edge
platform L1
2 Analyze the use of AWS IoT Core and related services. L3
3 To examine the message passing techniques in AWS IoT Core
devices and assess the security using VPC on AWS. L3
4 Deploy Edge computing networks using Edge computing simulators L4
5 Deploy Fog computing networks using Fog computing simulators L5

Prerequisite: Cloud Computing and IoT concepts

Sr. No. Suggested list of Assignments LO
1 Create and deploy virtual servers on AWS / Azure. LO1
2 To deploy Raspberry Pi on AWS IoT Core LO2
3 To implement MQTT messaging between Raspberry Pi and AWS IoT
Core LO2
4 To implement virtual private cloud (VPC) on AWS for IoT services. LO3
5 Study assignment on Edge and Fog Simulators LO4
6 Design and deploy an edge computing architecture using edge
simulators such as Mobius / EdgeCloudSim. LO4
7 Develop and evaluate edge -based data analytics algorithms in an edge
simulator. LO5
8 Design and deploy a fog computing architecture using simulators such
as iFogSim / CloudSim. LO4
9 Explore collaboration between edge and fog nodes for IoT applications. LO5
Text Books:
1. “Fog and Edge Computing” by Rajkumar Buyya, Satish Narayana Srirama, Wiley Publications

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2. "Edge Computing: Models, Technologies, and Applications" by Mung Chiang, Bharath
Balasubramanian, and H. Vincent Poor.
3. Edge Computing with Python: End -to-end Edge Applications, Python Tools and Techniques,
Edge Architectures, and AI Benefit” by Abhinandan Bhadauria, BPB publications.
4. “Edge Computing: Simply in Depth” by Ajit Singh,
5. Edge Computing: Fundamentals, Advances and Applications (Advances in Industry 4.0 and
Machine Learning) by K. Anitha Kumari, G. Sudha Sadasivam, D. Dharani, M. Niranjanamurthy,
CRC Press.
References:

1. "Edge Computing for IoT: Architectures and Applications" by Bharat Bhargava, Sudip Misra,
Valentina E. Balas, and Raghvendra Kumar
2. "Practical Industrial Internet of Things Security: A practitioner's guide to securing connected
industries" by Sravani Bhattacharjee and Rajdeep Chowdhury
3. "Edge Computing: An Introduction to the Next Generation of Networked Systems" by Kiran
Chitturi, Bharadwaj Veeravalli, and Satish Narayana Srirama
4. "Building the Web of Things: With examples in Node.js and Raspberry Pi" by Dominique D.
Guinard and Vlad M. Trifa
5. "Internet of Things (IoT): Technologies, Applications, Challenges, and Solutions" edited by
Balamuralidhar P., Bharadwaj Veeravalli, and V. Raghu
6. "Fog and Edge Computing: Principles and Paradigms" by Rajkumar Buyya, Satish Srirama, and
Pradeep Kumar S.
7. "IoT Fundamentals: Networking Technologies, Protocols, and Use Cases for the Internet of
Things" by David Hanes and Gonzalo Salgueiro
8. "Edge Analytics in IoT" by Shivashankar B . Nair, Siddhartha Bhattacharyya, and Thomas Edward
Joshua
9. "Edge Computing: The Convergence of Big Data and Internet of Things" by Samee U. Khan,
Albert Y. Zomaya, and Salman A. Baset


Online References:
1. http://www.steves -internet -guide.com/mqtt -protocol -messages -overview/
2. https://aws.amazon.com/iot -core/

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3. https://github.com/CagataySonmez/EdgeCloudSim/wiki
4. https://www.cloudsimtutorials.online/ifogsim -project -structure -a-beginners -guide/
5. https://www.udemy.com/course/essential -ifogsim -tutorials/
6. https://slogix.in/source -code/ifog -computing -samples/how -to-create -fog-topology -in-ifogsim/

Assessment:
Term Work: Term Work shall consist of at least 10 to 12 practicals based on the above list. Also, Term
work Journal must include at least 2 assignments.
Term Work Marks: 25 Marks (Total marks) = 15 Marks (Experiment) + 5 Marks (Assignments) + 5
Marks (Attendance)
Oral Exam: An Oral exam will be held based on the above s yllabus / suggested list of Assignment.

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Teaching Scheme
(Contact Hours) Credits Assigned
Course Code Course Name Theory Practical Tutorial Theory Prac Tutorial Total
IOTL704
Linux
Administration
Lab -- 02 -- -- 1 -- 1

Subject Code Subject
Name Examination Scheme
Theory Marks Term
Work Practical/
Oral Total
Internal Assessment End Sem.
Exam Test
1 Test 2 Avg. of 2
Tests
IOTL704 Linux
Administ
ration
Lab -- -- -- -- 25 25 50

Lab Objectives :
1. To effectively manage and maintain a Linux -based system infrastructure.
2. To develop and utilize shell programming and scripting skills in Linux systems.
3. To configure storage and manage networks in Linux systems.
4. To manage user accounts, groups, and permissions in Linux systems.
5. To administer a nd secure network infrastructure in Linux systems.
6. To configure and manage DNS, DHCP, and mail server services in Linux systems.
Lab Outcomes : After successful completion of the course, students will be able to

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 Understand the installation of Linux OS and apply different
commands for Linux administration. L1

2. Develop shell scripts to perform tasks in a shell programming
environment. L2,L3
3. Demonstrate the Linux storage configuration and network
management. L3
4. Demonstrate the creation and management of user/group accounts
in Linux. L3
5. Illustrate the use of iptables for Firewall setup. L1,L2
6. Demonstrate the configuration and management of different
server services like DNS, DHCP, and Mail Server. L3

Prerequisite : Operating Systems, Computer Networks
DETAILED SYLLABUS :

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Sr.
No. Module Detailed Content Hours LO
Mappi
ng
0 Prerequisite Basics of Operating System, Computer Networks 2 --
1 Introduction and
Linux
Administration
Tasks Introduction : History of Linux OS, Architecture of Linux OS,
Linux Distributions, Installation of Linux OS, Administration
Tasks : Introduction to terminal, Basic commands, File system,
File handling commands, process and process management
commands, VI editor. 4 LO1
2 Shell
Programming Introducing Bash Shell Scripting : Introduction, Elements of a
Good Shell Script, Executing the Scr ipt, Working with
Variables and Input, Understanding Variables, Variables,
Subshells, and Sourcing, Working with Script Arguments,
Asking for Input, Using Command Substitution, Substitution
Operators, Changing Variable Content with Pattern Matching,
Perfor ming Calculations, Using Control Structures, Using
if...then...else, Using case, Using while, Using until, Using for,
Configuring booting with GRUB. 4 LO2
3 Storage
Configuration,
and Network
Management Configuring and Managing Storage : Types of storages,
creating partitions using fdisk command, Logical volume
management (LVM), Creating file system, mounting file
system.
Connecting to the Network : Understanding NetworkManager,
Working with Services and Runlevels, Configuring the
Network with NetworkManager , Working with system -config -
network, NetworkManager Configuration Files, Network
Service Scripts, Networking from the Command Line,
Troubleshooting Networking, Setting Up IPv6, Configuring
SSH, Enabling the SSH Server, Using the SSH Client. 4 LO3
4 User and Group
Management Working with Users, Groups, and Permissions : Managing
Users and Groups, Commands for User Management,
Managing Passwords, Modifying and Deleting User Accounts,
Configuration Files, Creating Groups, Using Graphical Tools
for User, and Group Management, Using External
Authentication Sources, the Auth entication Process, sssd,
nsswitch, Pluggable Authentication Modules, Managing
Permissions, the Role of Ownership, Basic Permissions: Read,
Write, and Execute, Advanced Permissions, Working with
Access Control Lists, Setting Default Permissions with umask,
Working with Attributes 2 LO4
5 Network
Configuration
and File Sharing Securing Server with iptables : Understanding Firewalls,
Setting Up a Firewall with system -config -firewall, Allowing
Services, Trusted Interfaces, Masquerading, Configuration
Files, Se tting Up a Firewall with iptables, Tables, Chains, and
Rules, Composition of Rule, Configuration Example, Advanced
iptables Configuration, Configuring Logging, The Limit
Module, Configuring NAT, Configuring Virtual Network
Computing (VNC) Server and Client .
Configuring Server for File Sharing : What is NFS?
Advantages and Disadvantages of NFS, Configuring NFS4,
Setting Up NFSv4, Mounting an NFS Share, Making NFS
Mounts Persistent, Configuring Automount, Configuring
Samba, Setting Up a Samba File Server, Samb a Advanced 4 LO5

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Authentication Options, Accessing Samba Shares, Offering
FTP Services.
6 Configuration of
DNS, DHCP,
and Mail Server Configuring DNS and DHCP : Introduction to DNS, The DNS
Hierarchy, DNS Server Types, The DNS Lookup Process, DNS
Zone Type s, Setting Up a DNS Server, Setting Up a Cache -
Only Name Server, Setting Up a Primary Name Server, Setting
Up a Secondary Name Server, Understanding DHCP, Setting
Up a DHCP Server
Setting Up a Mail Server : Using the Message Transfer Agent,
the Mail Delive ry Agent, and the Mail User Agent, Setting Up
Postfix as an SMTP Server, Working with Mutt, Basic
Configuration, Internet Configuration, Configuring Dovecot for
POP and IMAP 4 LO6

List of Experiments:
Sr.
No. Name of the Experiment LO Mapping
1 Installation of RHEL6.x and above/ CentOS/ Ubuntu/ Raspberry Pi OS on
VirtualBox/ VMware. LO1
2 Graphical User Interface, Command Line Interface, and Processes
(a) Exploring the Graphical Desktop
(b) The Command Line Interface
(c) Process Management LO1
3 Shell Prog ramming – I
(a) Write a menu -driven program for the following options
● List of files
● Processes of Users
● Today’s Date
● Quit out of Linux
(b) Write a shell program that accepts the name of a file from the standard
input and then performs the following test on it.
● File Existence
● File Readable and Writable
(c) Write a shell program to perform a simulated cp command. Proceed this
program using positional parameter and the usage will be on the form of
copy and ensure that parameters are properly used.
(d) Write a shell program to convert all lowercase letters in a file to uppercase
letter.
(e) Write a shell program for file containing several records where each
record contains name and city, name of state, and name of country. How
would you sort this file with co untry as the primary key and state as the
secondary sort key? LO2
4 Shell Programming – II
(a) 2-3 C Programs
(b) 2-3 Java Programs
(c) 2-3 Python Programs LO2
5 Storage Devices and Links, Backup, and Repository LO3

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(a) Mounting and working with storage devices and links
(b) Making a backup
(c) Creating a Repository
6 Working with RPMs, YUM, Storage, and Networking
(a) Extracting Files from RPMs, YUM
(b) Configuring and Managing Storage
(c) Connecting to the Network LO3
7 Working with Users, Groups, and Permissions
(a) Creating a user
(b) Creating a group
(c) Assigning permissions to user and group
(d) Access Control List
(e) Login in multi -user mode.
(f) Identify the current run level.
(g) Identify the default run level of the system.
(h) Change the default run level to 2.
(i) Check the difference between run level 3 and single -user mode.
(j) Create run control scripts and execute them at the time of system
startup in the default run level. LO3, LO4
8 (a) Firewall services to secure Server with iptables.
(b) Configuring VNC Server and VNC Client. LO5
9 Configuring Server for File Sharing
(a) Configuring NFS Server and Client
(b) Configuring FTP Server LO5
10 Configuring DNS, DHCP, and Mail Server
(a) Configuring DNS
(b) Configuring DHCP
(c) Setting up a Mail Server LO6

Textbooks:
1. Wale Soyinka, “Linux Administration: A Beginner’s Guide”, McGraw Hill Publication, 6th Edition,
2012.
2. B.M. Harwani, “UNIX & Shell Programming”, Oxford University Press, 2013.
3. W. Richard. Stevens, “Advanced Programming in the UNIX Environment”, Pearson Education, 3rd
Edition, 2013.
Reference Books:
1. Cristopher Negus, “Linux Bible”, John Wiley & Sons, 10th Edition, 2020.
2. Ellen Siever, Stephen Figgins, Robert Love, Arnold Robbins, “Linux in a Nutshell”, O’Reilly, 6th
Edition, 2009.
3. Neil Mathew & Richard Stones, “Beginning Linux Programming”, Wiley, 4th Edition, 2008.
4. W. Richard. Stevens, “Advanced Programming in the UNIX Environment‖, Pearson Education, 2013.
Online Resources:
1. https://nptel.ac.in/courses/117106113
2. https://www.tutorialspoint.com/linux_admin/index.htm
3. https://linode.com/docs/tools -reference/linux -system -administrationbasics/
4. opensourceforu.com/2016/07/introduction -linux -system -administration/

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5. https://www.linuxfoundation.org
6. https://www.classcentral.com/course/youtube -linux -full-course -of-rhcsa -ex200 -in-hindi -rhel8 -red-hat-
linux -8-for-beginners -90420


Term Work :
Term Work shall consist of at least 8 to 10 practicals based on the above list. Also, the Term Work Journal
must include at least 2 assignments.

Term Work Marks :
25 Marks (Total marks) = 15 Mark s (Experiment) + 5 Marks (Assignments) + 5 Marks (Attendance)

Oral Exam : Oral exam will be held on the above syllabus for 25 Marks (Total marks).

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Course
Code: Course Title Credit
IOTP701 Major Project 1 3


Course Objectives:
1 To acquaint yourself with the process of identifying the needs and converting it into
the problem.
2 To familiarize the process of solving the problem in a group.
3 To acquaint with the process of applying basic engineering fundamentals to attempt
solutions to the
problems.
4 To inculcate the process of self -learning and research.
Course Outcomes:
1 Identify problems based on societal /research needs.
2 Apply Knowledge and skill to solve societal problems in a group
3 Draw the proper inferences from available results through theoretical/
experimental/simulations
4 Analyze the impact of solutions in societal and environmental context for sustainable
development.
5 Demonstrate capabilities of self -learning in a group, which leads to lifelong learning.
6 Demonstrate project management principles during project work.

Guidelines:

1. Project Topic Selection and Allocation:
· Project topic selection Process to be defined and followed:
o Project orientation can be given at the end of sixth semester.
o Students should be informed about the domain and domain experts whose guidance
can be taken before selecting projects.

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o Student‘s should be recommended to refer papers from reputed conferences/journals
like IEEE, Elsevier, ACM etc. which are not more than 3 years old for review of
literature.
o Dataset selected for the project should be COLLECTED from IOT devices (large and
real time)
o Students can certainly take ideas from anywhere, but be sure that they shou ld evolve
them in the unique way to suit their project requirements. Students can be informed
to refer to Digital India portal, SIH portal or any other hackathon portal for problem
selection.

· Topics can be finalized with respect to following criterion :
o Topic Selection : The topics selected should be novel in nature (Product based, Application based or
Research based) or should work towards removing the lacuna in currently existing systems.

o Technology Used: Use of latest technology or modern tools can be encouraged. IoT, AI,
ML, DL, NNFL, NLP based algorithms can be implemented
o Students should not repeat work done previously (work done in the last three years).
o Project work must be carried out by the group of at least 3 students and maximum 4.
o The project work can be undertaken in a research
institute or organization/Industry/any business establishment. (out -house projects)
o The project proposal presentations can be scheduled according to the domains and
should be jud ged by faculty who are expert in the domain.
o Head of department and senior staff along with project coordinators will take
decision regarding final selection of projects.
o Guide allocation should be done and students have to submit weekly progress report
to the internal guide.
o Internal guide has to keep track of the progress of the project and also has to
maintain attendance report. This progress report can be used for awarding term
work marks.
o In case of industry/ out -house projects, visit by internal guide will be preferred and
external members can be called during the presentation at various levels

2. Project Report Format:

At the end of semester, each group needs to prepare a project report as per the guidelines issued by the
Univers ity of Mumbai.

A project report should preferably contain following details:
o Abstract
o Introduction
o Literature Survey/ Existing system
o Limitation Existing system or research gap
o Problem Statement and Objective
o Proposed System
o A nalysis/Framework/ Algorithm
o Design details
o Methodology (your approach to solve the problem) Proposed System
o Experimental Set up
o Details of Database or details about input to systems or selected data
o Performance Evaluation Parameters (for Validation)
o Software and Hardware Setup
o Implementation Plan for Next Semester

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o Timeline Chart for Term1 and Term -II (Project Management tools can be
used.)
o References

Desirable

Students can be asked to undergo some Certification course (for the technical skill set that will be useful
and applicable for projects.)

3. Term Work:

Distribution of marks for term work shall be done based on following:
o Weekly Log Report
o Project Work Contribution
o Project Report (Spiral Bou nd) (both side print)
o Term End Presentation (Internal)
The final certification and acceptance of TW ensures the satisfactory performance on the above aspects.

4. Oral and Practical:

Oral and Practical examination (Final Project Evaluation) of Project 1 should be conducted by Internal and
External examiners approved by University of Mumbai at the end of the semester.

Suggested quality evaluation parameters are as follows:

o Quality of problem selected
o Clarity of problem definition and feasibility of problem solution
o Relevance to the specialization / industrial trends
o Originality
o Clarity of objective and scope
o Quality of analysis and design
o Quality of written and oral presentation
o Individual as well as teamwork

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# Institute Level Optional Course (ILO)

Every student is required to take one Institute Elective Course for Semester VII, which is
not closely allied to their disciplines. Different sets of courses will run in the both
the semesters.


ILO701X Institute Optional Course – 1 ( Common for all branches will be notified )
ILO7011 Product Lifecycle Management
ILO7012 Reliability Engineering
ILO7013 Management Information System
ILO7014 Design of Experiments
ILO7015 Operation Research
ILO7016 Cyber Security and Laws
ILO7017 Disaster Management and Mitigation
Measures
ILO7018 Energy Audit and Management
ILO7019 Development Engineering

Page 66

Course Code Course Name Credits
ILO7011 Product Life Cycle Management 03


Course Objectives: Students will try :
1. To familiarize the students with the need, benefits and components of PLM
2. To acquaint students with Product Data Management & PLM strategies
3. To give insights into new product development program and guidelines for des igning and
developing a product
4. To familiarize the students with Virtual Product Development

Course Outcomes: Students will be able to :
1. Gain knowledge about phases of PLM, PLM strategies and methodology for PLM feasibility study
and PDM implementation.
2. Illustrate various approaches and techniques for designing and developing products.
3. Apply product engineering guidelines / thumb rules in designing products for moulding, machining,
sheet metal working etc.
4. Acquire knowledge in applying virtual product dev elopment tools for components, machining and
manufacturing plant



Module
Detailed Contents
Hrs



01 Introduction to Product Lifecycle Management (PLM): Product Lifecycle
Management (PLM), Need for PLM, Product Lifecycle Phases, Opportunities of
Globalization, Pre -PLM Environment, PLM Paradigm, Importance & Benefits of
PLM, Widespread Impact of PLM, Focus and Application, A PLM Project, Starting the
PLM Initiati ve, PLM Applications
PLM Strategies: Industrial strategies, Strategy elements, its identification, selection
and implementation, Developing PLM Vision and PLM Strategy ,
Change management for PLM 10





02 ProductDesign: Product Design and Development Process, Engineering Design,
Organization and Decomposition in Product Design, Typologies of Design Process
Models, Reference Model, Product Design in the Context of the Product Development
Process, Relation with the Development Pro cess Planning Phase, Relation with the Post
design Planning Phase, Methodological Evolution in Product Design, Concurrent
Engineering, Characteristic Features of Concurrent Engineering, Concurrent
Engineering and Life Cycle Approach, New Product Developmen t (NPD) and
Strategies, Product Configuration and Variant Management, The Design for X System,
Objective Properties and Design for X
Tools, Choice of Design for X Tools and Their Use in the Design Process 09

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03 Product Data Management (PDM): Product and Product Data, PDM systems and
importance, Components of PDM, Reason for implementing a PDM system,
financial justification of PDM, barriers to PDM implementation 05
04 Virtual Product Development Tools: For components, machines, and
manufacturing plants, 3D CAD systems and realistic rendering techniques, 05

Digital mock -up, Model building, Model analysis, Modeling and simulations in
Product Design, Examples/Case studies


05 Integration of Environmental Aspects in Product Design: Sustainable
Development, Design for Environment,Need for Life Cycle Environmental Strategies,
Useful Life Extension Strategies, End -of-Life Strategies, Introduction of
Environmental Strategies into the Design Process, Life Cycle Environmental Strategies
and Considerations for Product Design 05


06 Life Cycle Assessment and Life Cycle Cost Analysis: Properties, and
Framework of Life Cycle Assessment, Phases of LCA in ISO Standards, Fields of
Application and Limitations of Life Cycle Assessment, Cost Analysis and the Life
Cycle Approach, General Framework for LCCA, Evolution of Models for Product Life
Cycle Cost Analysis 05


Assessment :

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

End Semester Theory Examination:
Some guidelines for setting up the question paper.Minimum 80% syllabus should be covered in question
papers of end semester examination. In question pap er weightage of each module will be proportional to
number of respective lecture hours as mention in the syllabus.
1. Question paper will comprise of total six question
2. All question carry equal marks
3. Questions will be mixed in nature (for example supposed Q.2 has part (a) from module 3 then part
(b) will be from any module other than module 3)
4. Only Four question need to be solved.


REFERENCES:

1. John Stark, “Product Lifecycle Management: Paradigm for 21st Century Product Realisation”,
Springer -Verlag, 2004. ISBN: 1852338105
2. Fabio Giudice, Guido La Rosa, AntoninoRisitano, “Product Design for the environment -A life cycle
approach”, Taylor & Francis 2006, ISBN: 0849327229
3. SaaksvuoriAntti, ImmonenAnselmie, “Product Life Cycle Management”, Springer, Dreamtech,

Page 68

ISBN: 3540257314
4. Michael Grieve, “Product Lifecycle Management: Driving the next generation of lean thinking”,
Tata McGraw Hill, 2006, ISBN: 0070636265

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Course Code Course Name Credits
ILO7012 Reliability Engineering 03


Objectives:
1. To familiarize the students with various aspects of probability theory
2. To acquaint the students with reliability and its concepts
3. To introduce the students to methods of estimating the system reliability of simple and complex systems
4. To understand the various aspects of Maintainability, Availability and FMEA procedure

Outcomes: Learner will be able to…
1. Understand and apply the concept of Probability to engineering problems
2. Apply various reliability concepts to calculate different reliability parameters
3. Estima te the system reliability of simple and complex systems
4. Carry out a Failure Mode Effect and Criticality Analysis



Module
Detailed Contents
Hrs


01 Probability theory: Probability: Standard definitions and concepts; Conditional
Probability, Baye’s Theorem.
Probability Distributions: Central tendency and Dispersion; Binomial, Normal,
Poisson, Weibull, Exponential, relations between them and their significance.
Measures of Dispersion: Mean, Median, Mode, Range, Mean Deviation,
Standard Deviation, Var iance, Skewness and Kurtosis.

08


02 Reliability Concepts: Reliability definitions, Importance of Reliability, Quality
Assurance and Reliability, Bath Tub Curve.
Failure Data Analysis: Hazard rate, failure density, Failure Rate, Mean Time To
Failure (MTTF), MTBF, Reliability Functions.
Reliability Hazard Models: Constant Failure Rate, Linearly increasing, Time
Dependent Failure Rate, Weibull Model. Distribution functions and reliability analysis.

08
03 System Reliability: System Configurations: Series, parallel, mixed
configuration, k out of n structure, Complex systems. 05

04 Reliability Improvement: Redundancy Techniques: Element redundancy, Unit
redundancy, Standby redundancies. Markov analysis.
System Reliability Analysis – Enumeration method, Cut -set method, Success
Path method, Decomposition method.
08


05 Maintainability and Availability: System downtime, Design for Maintainability:
Maintenance requirements, Design methods: Fault Isolation and self -diagnostics, Parts
standardization and Interchangeability, Modularization and Accessibility, Repair Vs
Replacement.
Availability – qualitative aspects.
05

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06 Failure Mode, Effects and Criticality Analysis: Failure mode effects analysis,
severity/criticality analysis, FMECA examples. Fault tree construction, basic symbols,
development of functional reliability block diagram, Fau1t tree
analysis and Event tree Analysis
05


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

End Semester Theory Examination:
Some guidelines for setting up the question paper. Minimum 80% syllabus should be covered in question papers of
end semester examination. In question paper weightage of each module will be proportional to number of
respective lecture hours as mention in the syllabus.
1. Question paper will comprise of total six question
2. All question carry equal marks
3. Questions will be mixed in nature (for example supposed Q.2 has part (a) from module 3 then part (b) will
be from any module other than module 3)
4. Only Four question need to be solved.


REFERENCES:

1. L.S. Srinath, “Reliability Engineering”, Affiliated East -Wast Press (P) Ltd., 1985.
2. Charles E. Ebeling, “Reliability and Maintainability Engineering”, Tata McGraw Hill.
3. B.S. Dhillion, C. Singh, “Engineering Reliability”, John Wiley & Sons, 1980.
4. P.D.T. Conor, “Practical Reliability Engg.”, John Wiley & Sons, 1985.
5. K.C. Kapur, L.R. Lambers on, “Reliability in Engineering Design”, John Wiley & Sons.
6. Murray R. Spiegel, “Probability and Statistics”, Tata McGraw -Hill Publishing Co. Ltd.

Page 71

Course Code Course Name Credits
ILO7013 Management Information System 03


Objectives:
1. The course is blend of Management and Technical field.
2. Discuss the roles played by information technology in today’s business and define various technology
architectures on which information systems are built
3. Define and analyze typical functional information systems and identify how they meet the needs of
the firm to deliver efficiency and competitive advantage
4. Identify the basic steps in systems development

Outcomes: Learner will be able to…
1. Explain how information systems Transform Business
2. Identify the imp act information systems have on an organization
3. Describe IT infrastructure and its components and its current trends
4. Understand the principal tools and technologies for accessing information from databases to improve
business performance and decision makin g
5. Identify the types of systems used for enterprise -wide knowledge management and how they provide value
for businesses



Module
Detailed Contents
Hrs

01 Introduction To Information Systems (IS): Computer Based Information Systems,
Impact of IT on organizations, Imporance of IS to Society.
Organizational Strategy, Competitive Advantages and IS.
4

02 Data and Knowledge Management: Database Approach, Big Data, Data warehouse
and Data Marts, Knowledge Management.
Business intelligence (BI): Managers and Decision Making, BI for Data analysis
and Presenting Results
7
03 Ethical issues and Privacy: Information Security. Threat to IS, and Security
Controls 7

04 Social Computing (SC): Web 2.0 and 3.0, SC in business -shopping, Marketing,
Operational and Analytic CRM, E-business and E -commerce – B2B B2C.
Mobile commerce.
7
05 Computer Networks Wired and Wireless technology, Pervasive computing,
Cloud computing model. 6

06 Information System within Organization: Transaction Processing Systems, Functional
Area Information System, ERP and ERP support of Business Process. Acquiring
Information Systems and Applications: Various System development
life cycle models.
8

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Assessment :

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

End Semester Theory Examination:
Some guidelines for setting up the question paper. Minimum 80% syllabus should be covered in question papers of
end semester examination. In question paper weightage of each module will be proportional to number of
respective lecture hours as mention in th e syllabus.
1. Question paper will comprise of total six question
2. All question carry equal marks
3. Questions will be mixed in nature (for example supposed Q.2 has part (a) from module 3 then part (b) will
be from any module other than module 3)
4. Only Four questi on need to be solved.


REFERENCES:

1. Kelly Rainer, Brad Prince,Management Information Systems, Wiley
2. K.C. Laudon and J.P. Laudon, Management Information Systems: Managing the Digital Firm, 10th Ed.,
Prentice Hall, 2007.
3. D. Boddy, A. Boonstra, Managing Information Systems: Strategy and Organization, Prentice Hall, 2008

Page 73

Course Code Course Name Credits
ILO7014 Design of Experiments 03


Objectives:
1. To understand the issues and principles of Design of Experiments (DOE)
2. To list the guidelines for designing experiments
3. To become familiar with methodologies that can be used in conjunction with experimental designs for
robustness and optimization

Outcomes: Learner will be able to…
1. Plan data collection, to turn data into information and to make decis ions that lead to appropriate action
2. Apply the methods taught to real life situations
3. Plan, analyze, and interpret the results of experiments



Module
Detailed Contents
Hrs


01 Introduction
Strategy of Experimentation
Typical Applications of Experimental Design
Guidelines for Designing Experiments
Response Surface Methodology

06



02 Fitting Regression Models
Linear Regression Models
Estimation of the Parameters in Linear Regression Models
Hypothesis Testing in Multiple Regression
Confidence Intervals in Multiple Regression
Prediction of new response observation
Regression model diagnostics
Testing for lack of fit


08



03 Two -Level Factorial Designs
The 22 Design
The 23 Design
The General2k Design
A Single Replicate of the 2k Design
The Addition of Center Points to the 2k Design,
Blocking in the 2k Factorial Design
Split -Plot Designs


07

Page 74

04 Two -Level Fractional Factorial Designs
The One -Half Fraction of the 2k Design
The One -Quarter Fraction of the 2k Design
The General 2k-p Fractional Factorial Design
Resolution III Designs
Resolution IV and V Designs
Fractional Factorial Split -Plot Designs


07



05 Response Surface Methods and Designs
Introduction to Response Surface Methodology
The Method of Steepest Ascent
Analysis of a Second -Order Response Surface
Experimental Designs for Fitting Response Surfaces

07

06 Taguchi Approach
Crossed Array Designs and Signal -to-Noise Ratios
Analysis Methods
Robust design examples
04


Assessment :

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

End Semester Theory Examination:
Some guidelines for setting up the question paper. Minimum 80 % syllabus should be covered in question papers of
end semester examination. In question, paper weightage of each module will be proportional to the number of
respective lecture hours as mentioned in the syllabus.
Question paper will comprise of total six question
All question carry equal marks
Questions will be mixed in nature (for example supposed Q.2 has part (a) from module 3 then part (b) will be
from any module other than module 3)
Only Four questions need to be solved.

REFERENCES:

1. Raymond H. Mayers, Douglas C. Montgomery, Christine M. Anderson -Cook, Response Surface
Methodology: Process and Pr oduct Optimization using Designed Experiment, 3rd edition,John Wiley
& Sons, New York, 2001
2. D.C. Montgomery, Design and Analysis of Experiments, 5th edition, John Wiley & Sons, New York, 2001
3. George E P Box, J Stuart Hunter, William G Hunter, Statistics fo r Experimenters: Design,
Innovation and Discovery, 2nd Ed. Wiley
4. W J Dimond, Practical Experiment Designs for Engineers and Scientists, John Wiley and Sons Inc. ISBN:
0-471-39054 -2
5. Design and Analysis of Experiments (Springer text in Statistics), Springer by A.M. Dean, and
D. T.Voss

Page 75

Course Code Course Name Credits
ILO7015 Operations Research 03


Objectives:
1. Formulate a real -world problem as a mathematical programming model.
2. Understand the mathematical tools that are needed to solve optimization problems.
3. Use mathematical software to solve the proposed models.

Outcomes: Learner will be able to…
1. Understand the theoretical workings of the simplex method, the relationship between a linear program and
its dual, including strong duality a nd complementary slackness.
2. Perform sensitivity analysis to determine the direction and magnitude of change of a model’s optimal
solution as the data change.
3. Solve specialized linear programming problems like the transportation and assignment problems, solve
network models like the shortest path, minimum spanning tree, and maximum flow problems.
4. Understand the applications of integer programming and a queuing model and compute important
performance measures



Module
Detailed Contents
Hrs









01 Introduction to Operations Research : Introduction, , Structure of the
Mathematical Model, Limitations of Operations Research
Linear Programming : Introduction, Linear Programming Problem,
Requirements of LPP, Mathematical Formulation of LPP, Graphical method,
Simplex Method Penalty Cost Method or Big M -method, Two Phase Method, Revised
simplex method, Duality , Primal – Dual construction, Symmetric and Asymmetric
Dual, Weak Duality Theorem, Complimentary Slackness Theorem, Main Duality
Theorem, Dual Simp lex Method, Sensitivity Analysis Transportation Problem :
Formulation, solution, unbalanced Transportation problem. Finding basic feasible
solutions – Northwest corner rule, least cost method and Vogel’s approximation
method. Optimality test: the stepping s tone method and MODI method.
Assignment Problem : Introduction, Mathematical Formulation of the Problem,
Hungarian Method Algorithm, Processing of n Jobs Through Two Machines and m
Machines, Graphical Method of Two Jobs m Machines Problem Routing Problem,
Travelling Salesman Problem
Integer Programming Problem : Introduction, Types of Integer Programming
Problems, Gomory’s cutting plane Algorithm, Branch and Bound Technique.
Introduction to Decomposition algorithms.








14

Page 76

02 Queuing models : queuing systems and structures, single server and multi -server
models, Poisson input, exponential service, constant rate service, finite and infinite
population
05
03 Simulation : Introduction, Methodology of Simulation, Basic Concepts, 05

Simulation Procedure, Application of Simulation Monte -Carlo Method:
Introduction, Monte -Carlo Simulation, Applications of Simulation, Advantages of
Simulation, Limitations of Simulation

04 Dynamic programming . Characteristics of dynamic programming. Dynamic
programming approach for Priority Management employment smoothening,
capital budgeting, Stage Coach/Shortest Path, cargo loading and Reliability problems.
05

05 Game Theory . Competitive games, rectangular game, saddle point, minimax
(maximin) method of optimal strategies, value of the game. Solution of games with
saddle points, dominance principle. Rectangular games without saddle point – mixed
strategy for 2 X 2 games.
05
06 Inventory Models : Classical EOQ Models, EOQ Model with Price Breaks,
EOQ with Shortage, Probabilistic EOQ Model, 05

Assessment :

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

End Semester Theory Examination:
Some guidelines for setting up the question paper. Minimum 80% syllabus should be covered in question papers of
end semester examination. In question paper weightage of each module will be propo rtional to number of
respective lecture hours as mention in the syllabus.
1. Question paper will comprise of total six question
2. All question carry equal marks
3. Questions will be mixed in nature (for example supposed Q.2 has part (a) from module 3 then part (b) will
be from any module other than module 3)
4. Only Four question need to be solved.


REFERENCES:

1. Taha, H.A. "Operations Research - An Introduction", Prentice Hall, (7th Edition), 2002.
2. Ravindran, A, Phillips, D. T and Solberg, J. J. "Operations Research: Principles and Practice", John
Willey and Sons, 2nd Edition, 2009.
3. Hiller, F. S. and Liebermann, G. J. "Introduction to Operations Research", Tata McGraw Hill, 2002.
4. Operations Research, S. D. Sharma, KedarNath Ram Nath -Meerut.
5. Operations Research, KantiSwarup, P. K. Gupta and Man Mohan, Sultan Chand & Sons.

Page 77

Course Code Course Name Credits
ILO7016 Cyber Security and Laws 03


Objectives:
1. To understand and identify different types cybercrime and cyber law
2. To recognized Indian IT Act 2008 and its latest amendments
3. To learn various types of security standards compliances

Outcomes: Learner will be able to…
1. Understand the concept of cybercrime and its effect on outside world
2. Interpret and apply IT law in various legal issues
3. Disti nguish different aspects of cyber law
4. Apply Information Security Standards compliance during software design and development



Module
Detailed Contents
Hrs

01 Introduction to Cybercrime: Cybercrime definition and origins of the world,
Cybercrime and information security, Classifications of cybercrime, Cybercrime and
the
Indian ITA 2000, A global Perspective on cybercrimes.
4




02 Cyber offenses & Cybercrime: How criminal plan the attacks, Social Engg, Cyber
stalking, Cyber café and Cybercrimes, Bot nets, Attack vector, Cloud computing,
Proliferation of Mobile and Wireless Devices, Trends in Mobility, Credit Card Frauds
in
Mobile and Wireless Computing Era, Security Challenges Posed by Mobile Devices,
Registry Settings for Mobile Devices, Authentication Service Security, Attacks on
Mobile/Cell Phones, Mobile Devices: Security Implications for Organizations,
Organizational Measures for Handling Mobile, Devices -Related Security Issues,
Organizational Security Policies and Measures i n Mobile
Computing Era, Laptops



9

03 Tools and Methods Used in Cyber line
Phishing, Password Cracking, Key loggers and Spywares, Virus and Worms,
Steganography, DoS and DDoS Attacks, SQL Injection, Buffer Over Flow, Attacks on
Wireless Networks, Phishing, Identity Theft (ID Theft)
6


04 The Concept of Cyberspace
E-Commerce , The Contract Aspects in Cyber Law ,The Security Aspect of
Cyber Law ,The Intellectual Property Aspect in Cyber Law
, The Evidence Aspect in Cyber Law , The Criminal Aspect in Cyber Law, Global
Trends in Cyber Law , Legal Framework for Electronic Data
Interchange Law Relating to Electronic Banking , The Need for an Indian Cyber
Law

8

Page 78

05 Indian IT Act.
Cyber Crime and Criminal Justice : Penalties, Adjudication and Appeals Under the
IT Act, 2000, IT Act. 2008 and its Amendments
6
06 Information Security Standard compliances
SOX, GLBA, HIPAA, ISO, FISMA, NERC, PCI. 6
Assessment :

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

End Semester Theory Examination:
Some guidelines for setting up the question paper. Minimum 80% syllabus should be covered in question papers of
end semester examination.
In question paper weightage of each module will be proportional to number of respective lecture hours as mention
in the syllabus.
1. Question paper will comprise of total six question
2. All question carry equal marks
3. Questions will be mixed in nature (for example supposed Q.2 has part (a) from module 3 then part (b) will
be from any module other than module 3)
4. Only Four question need to be solved.


REFERENCES:

1. Nina Godbole, Sunit Belapure, Cyber Security , Wiley Indi a, New Delhi
2. The Indian Cyber Law by Suresh T. Vishwanathan; Bharat Law House New Delhi
3. The Information technology Act, 2000; Bare Act - Professional Book Publishers, New Delhi.
4. Cyber Law & Cyber Crimes By Advocate Prashant Mali; Snow White Publications, Mumbai
5. Nina Godbole, Information Systems Security, Wiley India, New Delhi
6. Kennetch J. Knapp, Cyber Security &Global Information Assurance Information Science Publishing.
7. William Stallings , Cryptography and Network Security, Pearson Publication
8. Websites for more information is available on : The Information Technology ACT, 2008 - TIFR :
https://www.tifrh.res.in
9. Website for more information , A Compl iance Primer for IT professional :
https://www.sans.org/reading -room/whitepapers/compliance/compliance -primer -professionals - 33538

Page 79

Course Code Course Name Credits
ILO7017 Disaster Management and Mitigation Measures 03

Objectives:
1. To understand physics and various types of disaster occurring around the world
2. To identify extent and damaging capacity of a disaster
3. To study and understand the means of losses and methods to overcome /minimize it.
4. To understand role of individual and various organization during and after disaster
5. To understand application of GIS in the field of disaster management
6. To understand the emergency government response s tructures before, during and after disaster
Outcomes: Learner will be able to…
1. Get to know natural as well as manmade disaster and their extent and possible effects on the
economy.
2. Plan of national importance structures based upon the previous history.
3. Get acquainted with government policies, acts and various organizational structure associated
with an emergency.
4. Get to know the simple do’s and don’ts in such extreme events and act accordingly.


Module
Detailed Contents
Hrs


01 Introduction
1.1 Definition of Disaster, hazard, global and Indian scenario, general perspective,
importance of study in human life, Direct and indirect effects of disasters, long
term effects of disasters. Introduction to global warming and
climate change.

03



02 Natural Disaster and Manmade disasters:
Natural Disaster: Meaning and nature of natural disaster, Flood, Flash flood, drought,
cloud burst, Earthquake, Landslides, Avalanches, Volcanic eruptions, Mudflow,
Cyclone, Storm, Storm Surge, climate change, global warming, sea level rise, ozone
depletion
Manmade Disasters: Chemical, Industrial, Nuclear and Fire Hazards. Role of
growing population and subsequent industrialization, urbanization and changing
lifestyle of human beings in frequent occurrences of manmade
disasters.


09



03 Disaster Management, Policy and Administration
Disaster management: meaning, concept, importance, objective of disaster
management policy, disaster risks in India, Paradigm shift in disaster management.
Policy and administration:
Importance and principles of disaster management policies, command and co -
ordination of in disaster management, rescue operations -how to start with
and how to proceed in due course of time, study of flowchart showing the entire
process.


06

Page 80

04 Institutional Framework for Disaster Management in India:
4.1 Importance of public awareness, Preparation and execution of emergency
management programme.Scope and responsibilities of National Institute of
Disaster Management (NIDM) and National disaster management authority
(NDMA) in India.Methods and measures to avoid disasters, Management of

06

Page 81

casualties, set up of emergency facilities, importance of
effective communication amongst different agencies in such
situations.
4.2 Use of Internet and softwares for effective disaster management.
Applications of GIS, Remote sensing and GPS in this regard.


05 Financing Relief Measures:
Ways to raise finance for relief expenditure, role of government agencies and NGO’s in
this process, Legal aspects related to finance raising as well as overall management of
disasters. Various NGO’s and the works they have carried out in the past on the
occurrence of various disasters, Ways to approach these teams.
International relief aid agen cies and their role in extreme events.

09




06 Preventive and Mitigation Measures:
Pre-disaster, during disaster and post -disaster measures in some events in general
Structural mapping: Risk mapping, assessment and analysis, sea walls and
embankments, Bio shield, shelters, early warning and communication
Non Structural Mitigation: Community based disaster preparedness, risk transfer
and risk financing, capacity development and training, awareness and education,
contingency plans.
Do’s and don’ts in case of disasters and effective implementation of relief
aids.



06

Assessment :

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

End Semester Theory Examination:
Some guidelines for setting up the question paper. Minimum 80% syllabus should be covered in question papers of
end semester examination. In question paper weightage of each module will be proportional to number of
respective lecture hours as mention in the syllabus.
1. Question paper will comprise of total six question
2. All question carry equal marks
3. Questions will be mixed in nature (for example supposed Q.2 has part (a) from module 3 then part (b) will
be from any module other than module 3)
4. Only Four question need to be solved.

REFERENCES:

1. ‘Disaster Management’ by Harsh K.Gupta, Universities Press Publications.
2. ‘Disaster Management: An Appraisal of Institutional Mechanisms in India’ by O.S.Dagur, published by
Centre for land warfare studies, New Delhi, 2011.
3. ‘Introduction to International Disaster Management’ by Damon Copolla, Butterworth Heinemann Elseveir
Publications.
4. ‘Disaster Management Handbook’ by Jack Pinkowski, CRC Press Taylor and Francis group.
5. ‘Disaster management & rehabilitation’ by Rajdeep Dasgupta, Mittal Publications, New Delhi.

Page 82

6. ‘Natural Hazards and Disaster Management, Vulnerability and Mitigation – R B Singh, Rawat Publications
7. Concepts and Techniques of GIS –C.P.Lo Albert, K.W. Yonng – Prentice Hall (India) Publications.
(Learners are expected to refer reports published at national and International level and updated information
available on authentic web sites)

Page 83

Course Code Course Name Credits
ILO7018 Energy Audit and Management 03


Objectives:

1. To understand the importance energy security for sustainable development and the
fundamentals of energy conservation.
2. To introduce performance evaluation criteria of various electrical and thermal installations to facilitate
the energy management
3. To relate the data collected during performance evaluation of systems for identification of energy
saving opportunities.

Outcomes: Learner will be able to…

1. To identify and describe present state of energy security and its importance.
2. To identify and describe the basic principles and methodologies adopted in energy audit of an utility.
3. To describe the energy performance evaluation of some common electrical installations and identify the
energy saving opportunities.
4. To describe the energy performance evaluation of some common thermal installations and identify the
energy saving opportunities
5. To analyze the data collected during performance evaluation and recommend energy saving measures


Module
Detailed Contents
Hrs


01 Energy Scenario:
Present Energy Scenario, Energy Pricing, Energy Sector Reforms, Energy Security,
Energy Conservation and its Importance, Energy Conservation Act - 2001 and its
Features. Basics of Energy and its various forms, Material and
Energy balance

04



02 Energy Audit Principles:
Definition, Energy audit - need, Types of energy audit, Energy management (audit)
approach -understanding energy costs, Bench marking, Energy performance, Matching
energy use to requirement, Maximizing system efficiencies, Optimizing the input
energy requirements, Fuel and energy substitution. Elements of monitoring& targeting;
Energy audit Instruments; Data and information -analysis.
Financial analysis techniques: Simple payback period, NPV, Return on investment
(ROI), Internal rate of return (IRR)


08

Page 84

03 Energy Management and Energy Conservation in Electrical System: Electricity
billing, Electrical load management and maximum demand Control; Power factor
improvement, Energy efficient equipments and appliances, star ratings.
Energy efficiency measures in lighting system, Lighting control: Occupancy
sensors, daylight integration, and use of intelligent controllers.
Energy conservation opportunities in: water pumps, industrial drives, induction
motors, motor retrofitting, soft starters, variable speed drives.


10




04 Energy Management and Energy Conservation in Thermal Systems:
Review of different thermal loads; Energy conservation opportunities in: Steam
distribution system, Assessment of steam distribution losses, Steam leakages, Steam
trapping, Condensate and flash steam recovery system.
General fuel economy measures in Boilers and furnaces, Waste heat recovery, use of
insulation - types and application. HVAC system: Coefficient of perform ance, Capacity,
factors affecting Refrigeration and Air Conditioning system performance and savings
opportunities.


10

05 Energy Performance Assessment:
On site Performance evaluation techniques, Case studies based on: Motors and
variable speed drive, pumps, HVAC system calculations; Lighting System:
Installed Load Efficacy Ratio (ILER) method, Financial Analysis.
04

06 Energy conservation in Buildings:
Energy Conservation Building Codes (ECBC): Green Building, LEED rating,
Application of Non-Conventional and Renewable Energy Sources
03


Assessment :

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

End Semester Theory Examination:
Some guidelines for setting up the question paper. Minimum 80% syllabus should be covered in question papers of
end semester examination. In question paper weightage of each module will be proportional to number of
respective l ecture hours as mention in the syllabus.
1. Question paper will comprise of total six question
2. All question carry equal marks
3. Questions will be mixed in nature (for example supposed Q.2 has part (a) from module 3 then part (b) will
be from any module other than module 3)
4. Only Four question need to be solved.


REFERENCES:

1. Handbook of Electrical Installation Practice, Geofry Stokes, Blackwell Science
2. Designing with light: Lighting Handbook, By Anil Valia, Lighting System
3. Energy Management Handbook, By W.C. T urner, John Wiley and Sons

Page 85

4. Handbook on Energy Audits and Management, edited by A. K. Tyagi, Tata Energy Research
Institute (TERI).
5. Energy Management Principles, C.B.Smith, Pergamon Press
6. Energy Conservation Guidebook, Dale R. Patrick, S. Fardo, Ray E. Richardson, Fairmont Press
7. Handbook of Energy Audits, Albert Thumann, W. J. Younger, T. Niehus, CRC Press
8. www.energymanagertraining.com
9. www.bee -india.nic.in

Page 86

Course Code Course Name Credits
ILO7019 Development Engineering 03

Objectives:

1. To familiarize the characteristics of rural Society and the Scope, Nature and
Constraints of rural Development
2. To provide an exposure to implications of 73rdCAA on Planning,
Development and Governance of Rural Areas
3. An exploration of human values, which go into making a ‘good’ human being,
a ‘good’ professional, a ‘good’ society and a ‘good life’ in the context of work
life and the personal life of modern Indian professionals
4. To familiarize the Nature and Type of Human Values relevant to Planning Institutions

Outcomes: Learner will be able to…

1. Demonstrate Understanding of knowledge for Rural Development.
2. Prepare solutions for Management Issues.
3. Take up Initiatives and design Strategies to complete the task
4. Develop acumen for higher education and research.
5. Demonstrate the art of working in group of different nature
6. Develop confidence to take up rural project activities independently



Module Contents Hrs
1 Introduction to Rural Development Meaning, nature and scope of development; Nature of
rural society in India; Hierarchy of settlements; Social, economic and ecological
constraints for rural development
Roots of Rural Development in India Rural reconstruction and Sarvodaya programme
before independence; Impact of voluntary effort and Sarvodaya Movement on rural
development; Constitutional direction, directive principles; Panchayati Raj - beginning of
planning and community development; National extension services. 08
2 Post-Independence rural Development Balwant Rai Mehta Committee - three tier system
of rural local Government; Need and scope for people’s participation and Panchayati Raj;
Ashok Mehta Committee - linkage between Panchayati Raj, participation and rural
development. 06

Page 87

3 Rural Development Initiatives in Five Year Plans Five Year Plans and Rural
Development; Planning process at National, State, Regional and District levels; Planning,
development, implementing and monitoring organizations and agencies; Urban and rural
interface - integrated approach and local plans; Development initiatives and their
convergence; Special component plan and sub -plan for the weaker section; Micro -eco
zones ; Data base for local planning; Need for decentralized planning; Sustainable rural
development 07

4 Post 73rd Amendment Scenario 73rd Constitution Amendment Act, including - XI
schedule, devolution of powers, functions and finance; Panchayati Raj institutions
- organizational linkages; Recent changes in rural local planning; Gram Sabha - revitalized
Panchayati Raj; Institutionalization; resource mapping, resource mobilization including
social mobilization; Information Technology and rural planning; Need for further
amendments. 04
5 Values and Science and Technology Material development and its values; the
challenge of science and technology; Values in planning profession, research and
education
Types of Values Psychological values — integrated personality; mental health; Societal
values — the modern search for a good society; justice, democracy, rule of law, values in
the Indian constitution; Aesthetic values — perception and enjoyment of beauty; Moral
and ethical values; nature of moral judgmen t; Spiritual values; different concepts; secular
spirituality; Relative and absolute values; Human values — humanism and human values;
human rights; human values as freedom, creativity, love and wisdom 10
6 Ethics Canons of ethics; ethics of virtue; ethics of duty; ethics of responsibility;
Work ethics; Professional ethics; Ethics in planning profession, research and education 04

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:
Weightage of each module in end semester examination will be proportional to the
number of respective lecture hours mentioned in the curriculum.

Page 88

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
1. ITPI, Village Planning and Rural Development, ITPI, New Delhi
2. Thooyavan, K.R. Human Settlements: A 2005 MA Publication, Chenn ai
3. GoI, Constitution (73rdGoI, New Delhi Amendment) Act, GoI, New Delhi
4. Planning Commission, Five Year Plans, Planning Commission
5. Planning Commission, Manual of Integrated District Planning, 2006, Planning
Commission New Delhi
6. Planning Guide to Beginners
7. Weaver, R.C., The Urban Complex, Doubleday
8. Farmer, W.P. et al, Ethics in Planning, American Planning Association, Washington
9. How, E., Normative Ethics in Planning, Journal of Planning Literature, Vol.5, No.2, pp.
123-150
10. Watson, V. Conflicting Rationalitie s: -- Implications for Planning Theory and
Ethics, Planning Theory and Practice, Vol. 4, No.4, pp.395 – 407

Page 89

Teaching Scheme (Contact
Hours)
Credits Assigned
Course Code Course Name Theory Practical Tutorial Theory Oral Tutorial Tot
al
IOTC801 Industrial IoT
03 - -- -- - -- 3

Subject
Code Subject
Name Examination Scheme
Theory Marks
Term
Work Oral Total Internal assessment End Sem.
Exam Test
1 Test 2 Avg. of
2 Tests
IOTC801 Industrial IoT
20 20 20 80 - - 100
Course Objectives: The course aims:
1. To understand the concepts of Industry 4.0 and IIOT.
2. To comprehend the Business models and reference architecture of IIoT.
3. To interpret Data Transmission and Data Acquisition systems for IIoT.
4. To explore middleware and WAN technologies.
5. To learn the security aspects in IIoT.
6. To understand real time applications of IIoT in various domains.

Course Outcomes:On successful completion, of course, learner/student will be able to:

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 concepts of Industry 4.0 and IIOT. L2
2. Illustrate the Business models and reference architecture of IIOT. L3
3. Analyze Data Transmission and Data Acquisition systems for IIoT. L4
4. Discuss various middleware and WAN technologies in IIOT. L2
5. Explain security aspects in IIoT.
L2
6. Analyze real time applications of IIoT in various domains.
L4

Page 90

Prerequisite: IoT Architecture and Protocols, Wireless Sensor Technologies
Sr.
No. Module Detailed Content Hou
rs CO
Mappi
ng
0 Prerequisite IoT Architecture and Protocols, Wireless Sensing
Technologies 02
I Introduction to
Industry 4.0 and
IIOT Overview of Industry 4.0 and Industrial Internet of Things,
Industry 4.0: Industrial Revolution: Phases of Development,
Basics of CPS, CPS and IIOT, Design requirements of Industry
4.0, Drivers of Industry 4.0, Sustainability Assessment of
industries, Smar t Business Perspective, Cybersecurity, Impacts of
Industry 4.0, Industrial Internet of Things: Basics, Industrial
Internet Systems , Industrial Sensing, Industrial Processes.
Self-learning Topics: Study real time IIoT challenges in
industry. 6 CO1
II Business Models
and Reference
Architecture of
IIoT Introduction, Definition of a business model, Business
Models of IoT and IIoT, Reference Architecture of IIoT,
Industrial Internet Reference Architecture( IIRA) , Key
Performance Indicators for Occupational Safety and Health.
Self-learning Topics: Study IoT Architecture. 6 CO2
III Data
Transmission and
Acquisition for
Industrial IoT 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. 7 CO3
IV IIOT
Middleware and
WAN
Technologies
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,
Web Services,
IIOT Middleware Platforms – Middleware Architecture IIOT
WAN Technologies and Protocols - IIoT Device Low -Power
WAN Optimized Technologies for M2M, SigFox, LoRaWAN,
nWave, Dash7 Protocol, Ingénue RPMA, Low Power Wi -Fi,
LTE Category -M, Weightless, Millimeter Radio
Self-learning Topics: Study different IIoT Middleware and
WAN Technologies. 8 CO4
V IIoT Security Threats, Vulnerabilities and Risks in IIoT, IIoT Identity and
Access Management: Identification, Authentication, 6 CO5

Page 91

Authorization and Account Management, IAM in IIoT, Securing
IIoT Edge, Fog, Cloud and Application, IIoT Security using
Emerging Technologies: Blockchain to Secure IIoT Transactions,
AI-based IIoT Security.

Self-learning Topics: Case Studies on Vulnerability, Threat and
Attacks and Possible Defense Mechanism in Different
Application Scenarios.
VI IIOT Applications
Machine Learning and Data Science Applications in Industry,
Health Care Applications in Industry, IIoT in Inventory
Management and Quality Control, IIoT in Plant Safety and
Security, Case Studies: Manufacturing Industry, Automotive
Industry, Mining Industr y.
Self-learning Topics: Case Studies on Real -Time Applications 6 CO6

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. “Practical Industrial Internet of Things security”: A practitioner's guide to securing connected
industries, by Bhattacharjee and Sravani, Packt Publishing Ltd, 2018.
Reference Books:
1. “Internet of Things Principles and Paradigms”, by Rajkumar Buyya, Amir Vahid Dastjerdi,
ELSEVIER Inc.
2. “Practical Internet of Things Security”, by Brian Russell, Drew Van Duren (Packt Publishing)
3. “IoT Fundamentals – Networking Technologies, Protocols, and Use Cases for the
Internet of Things”, David Hanes, Gonzalo Salgueiro, Patrick Grossetete, Rob Barton,
Jerome Henry,1st Edition, Published by Pearson Education, Inc, publishing as Cisco
Press, 2017.

Online References:
1. https://onlinecourses.nptel.ac.in/noc23_cs51/preview
2. https://onlinecourses.nptel.ac.in/noc20_cs69/preview
3. https://onlinecourses.nptel.ac.in/noc22_me123/preview
4. The Industrial Internet of Things (IIOT) - How to Build a Digitally Connected Enterprise |

Page 92

Coursera
Assessment:
Internal Assessme nt (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 fr om 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.

Page 93

Theory Practical Tutorial Theory Practical/
Oral Tutorial Total
IOTDO801
1 User Interface
Design for IoT 03 -- -- 03 -- -- 03

Subject
Code Subject Name Examination Scheme
Theory Marks
Term
Work Practical Oral Total Internal assessment End
Sem.
Exam Test
1 Test 2 Avg. of 2
Tests

IOTDO801
1 User Interface
Design for
IoT 20 20 20 80 -- -- -- 100
Course Objectives: Six Course Objectives
1. To understand the need for a good UI design in IoT
2. To orient students to the different data management technologies
3. To understand the need for web connectivity
4. To understand the importance of Cloud services in data collection and storage
5. To study and understand various software used for IoT Applications
6. Understanding various frontend and backend technologies used for designing IoT Applications
Course Outcomes: Six Course outcomes

Page 94

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 Interaction Design Process and User Experience in IoT. L1
2. Design with the development of connected devices in various industries
ensuring positive user experiences L3
3. Apply the knowledge of Web Connectivity in the UI design for IoT.
L3
4. Illustrate Data Collection, Storage and Computing using a Cloud Platform. L3
5. Prototyping the Software for IoT Applications. L1,L2
6. Create websites using different web technologies for IoT applications. L2,L3

Prerequisite: IoT Architecture and Protocols, Web X.0
DETAILED SYLLABUS:
Sr.
No. Module Detailed Content Hours CO
Mappi
ng
0 Prerequisite Software Engineering concepts, IoT basics and Cloud
Computing basics. 02 NA
I Introduction to
Interaction
Design Good and Poor Design, What is Interaction Design, The
User Experience, The Process of Interaction Design,
Interaction Design and the User Experience, Necessity
of UI/UX.

Self-learning Topics: Study of Various interactive day
to day IoT applications. 05 CO1
II Design
Principles for
Connected
Devices Introduction, IoT/M2M Systems Layers and Design
Standardisation, Communication Technologies, Data
Enrichment, Data Consolidation and Device
Management at gateway.
Self-learning Topics: Understanding Security and
Usability of the data. 05 CO2
III Design
Principles for
Web
Connectivity Introduction, Web communication protocols for
connected devices, Message Communication Protocols
for connected devices, Web connectivity for connected
devices network using gateway, SOAP, REST, HTTP
RESTful and webSockets.
Self-learning Topics: To build RE STful API. 08 CO3

Page 95

IV Data Collection,
Storage and
Computing
Using a Cloud
Platform Introduction, Cloud Computing Paradigm for data
collection, Storage and Computing, Everything as a
Service and Cloud Service Models, IoT Cloud -based
services using Xively , Nimbits and other platforms.
Self-learning Topics: Study of tools like ThingSpeak,
Ubidots, AWS cloud 08 CO4
V Prototyping and
Designing the
Software for IoT
Applications Introduction, Prototyping Embedded Device Software,
Devices, Gateways, Internet and Web/Cloud
ServicesSoftware -Development, Prototyping Online
Component APIs and Web APIs.
Self-learning Topics: Study of online UI Tool like
Figma 06 CO5
VI Web
Technologies
used for User
Interface Design
for IoT
applications Front End Technologies: Responsive website design
using HTML5, ReactJs, AngularJs etc.
Back End Technologies: NodeJs, ExpressJs and
MongoDB.
Self-learning Topics: Use Case for Healthcare
Monitoring Syste m. 07 CO6

Text Books:
1. Interaction Design, by J. Preece, Y. Rogers and H. Sharp. ISBN 0 -471-49278 -7.
2. Wilbert O. Galitz, ―The Essential Guide to User Interface Design, Wiley publication.
3. INTERNET OF THINGS:Architecture and Design Principles, Raj Kamal, McGraw Hill
Education.
References:
1. Human -Computer Interaction, by ALAN DIX, JANET FINLAY,GREGORY D. ABOWD,
RUSSELL BEALE, Pearson Education Limited, Edition 3
2. Internet of Things, by Vinayak Shinde, Yogesh Pingle, Anjali Y eole, Sybgen Learning
3. Internet of Things for Architects, Perry Lea, Packt

Online References:
1. Design & Implementation Of Human -Computer Interfaces
https://onlinecourses.nptel.ac.in/noc23_cs116/preview

Assessment:

Page 96

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 w ill 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. Fo r 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.


Subject Code Subject Name Theory Practical Tutoria
l Theory Practic
al/Oral Tutorial Total
IOTDO8012 Energy
Harvesting
and Power
Management
for IoT devices 03 -- -- 03 -- -- 03

Subject
Code Subject
Name Examination Scheme
Theory Marks
Term
Work Practical Oral Total Internal assessment End
Sem.
Exam Test
1 Test
2 Avg. of 2
Tests
IOTDO801
2 Energy
Harvesting
and Power
Managemen
t for IoT
devices 20 20 20 80 -- -- -- 100

Page 97

Course Objectives:
1. To understand the energy sources and harvesting based sensor networks.
2. To learn Piezoelectric materials and energy harvesters.
3. To emphasize on Electromechanical Modeling of Cantilevered Piezoelectric Energy
Harvesters for Persistent Base Motions.
4. To Learn principles of Electromagnetic Energy Harvesting and Non -linear Techniques.
5. To Understand t he various Power sources for WSN.
6. To Learn the applications of Energy harvesting systems.
Course Outcomes:
Sr. No. Course Outcomes Cognitive levels of
attainment as per
Bloom’s
Taxonomy
On successful completion, of course, the learner/student will be able to:
1 Illustrate the knowledge of various energy sources, harvesting cell and the
impact of factors influencing the efficiency. L1, L2, L3
2 Analyze the properties of piezoelectric materials to convert the mechanical
vibrations, and strains into electrical energy. L1, L2, L3, L4
3 Develop mathematical models to analyse cantilevered piezoelectric energy
harvesters' behaviour and dynamics. L1, L2, L3, L4
4 Design electromagnetic energy harvesting devices and systems to explore
non-linear techniques for improving energy harvesting efficiency. L1, L2, L3, L4
5 Identify the different techniques of Energy Harvesting for Wireless
Sensors and their appropriate applications. L1, L2, L3
6 Summarize applications of Energy Harvesting Systems and apply them in
relevant applications. L1, L2, L3

Prerequisite:
IoTC601 IoT Architecture and Protocols, IoTC602 RFID and Microcontrollers, IoTC603
Wireless Sensor Technologies, CSDO701X IoT for Heal thcare Application, CSDO701X IoT
for Smart Cities

DETAILED SYLLABUS:
Sr.
No. Module Detailed Content Hrs. CO
Map
ping

Page 98

0 Prerequisite Basic knowledge of electrical circuits and electronics,
Fundamentals of IoT, Analog and digital electronics,
Energy and power fundamentals, Basic knowledge of
sensors and actuators, Electrical power systems 03
I Energy
Harvesting
Electronic
Systems 1.1 Available Energy Sources - Mechanical Energy,
Thermal Gradients, Radio Frequency Electromagnetic
Energy, Human Generation, Microbial Fuel Cells,
Light.
1.2 Comparison of Harvestable Energy Sources
1.3 Energy Harvesting -Based Sensor Networks -
Introduction, Energy Neutrality, Examples of WSN
Powered by Harvested Energy
1.4 Photovoltaic Cell Technologies – Introduction -
Concepts and Parameters Regarding PV Cells -
Standard Illumination Conditions -Fill Factor -
Efficiency -Peak Watt
1.5 Generation of Electric Power in Semicond uctor PV
Cells - Efficiency Limit According to Shockley and
Queisser
1.6 Types of PV Cells - First-Generation PV Cells -
Second Generation PV Cells -Third -Generation PV
Cells - Comparison of the Different PV Technologies
Self Learning Topics: Indoor Light Energy A vailability
Study - Light Power Intensity Measurements 06 CO1
II Piezoelectric
Energy
Harvesting 2.1 Piezoelectric Materials - Piezoelectric Polycrystalline
Ceramics - Piezoelectric Single Crystal Materials -
Piezoelectric and Electrostrictive Polymers -
Piezoelectric Thin Films
2.2 Piezoelectric Transducers
2.3 Meso -macro -scale Energy Harvesters - Mechanical
Energy Harvester Using Laser Micromachining -
Mechanical Energy Harvester Using Piezoelectric
Fibers
2.4 Piezoelectric Microgenerator - Piezoelectric
Microcantilevers
2.5 Energy Harvesting Circuits
2.6 Strategies for Enhancing the Performance of Energy
Harvester - Multi -modal Energy Harvesting -
Magnetoelectric Composites - Self-Tuning -
Frequency Pumping - Wide -Bandwidth Transducers
Self Learning Topics: Selected Applications - Border
Security Sensors - Biomedical Applications 06 CO2
III Electromechani
cal Modeling of
Cantilevered 3.1 Amplitude -Wise Correction of the Lumped Parameter
Model - Uncoupled Lumped Parameter Base 05 CO3

Page 99

Piezoelectric
Energy
Harvesters for
Persistent Base
Motions Excitation Model - Uncoupled Distributed Parameter
Base Excitation Model
3.2 Correction Factors for the Lumped Parameter Model -
Correction Factor in the Piezoelectricall y Coupled
Lumped Parameter Equations
3.3 Coupled Distributed Parameter Models and Closed -
Form Solutions - Modeling Assumptions -
Mathematical Background –
3.4 Unimorph Configuration
3.5 Bimorph Configurations
Self Learning Topics: Single -Mode Electromechanical
Equa tions, Experimental Validation
IV Electromagneti
c Energy
Harvesting and
Non-linear
Techniques 4.1 Basic Principles - Micro -Fabricated Coils - Magnetic
Materials
4.2 Scaling of Electromagnetic Vibration Generators -
Scaling of Electromagnetic Damping -
4.3 Maximizing Power from an EM Generator
4.4 Microscale Implementations
4.5 Macro -Scale Implementations
4.6 Introduction to Nonlinear Techniques and their
Application to Vibration Control - Principles
4.7 Energy Harvesting Using Nonlinear Techniques in
Steady -State Case - Principles - Analysis Without
Induction of Vibration Damping
Self Learning Topics: Energy Harvesting in Pulsed
Operation, Energy Harvesting Techniques under
Broadband Excitation 07 CO4
V Energy
Harvesting
Wireless
Sensors 5.1 Power Sources for Wireless Sensor Networks -
Introduction - Primary Batteries
5.2 Energy harvesting - Energy Harvesting versus Energy
Scavenging - Photonic Methods - Vibrational
Methods - Thermal Methods
5.3 Alternative Methods - RF Power - Radioactive
Sources - Power Conversion - Energy Storage -
Examples - case studies.
5.4 Harvesting Microelectronic Circuits - Harvesting
Sources - Energy and Power - Energy Sources
5.5 Power Conditioning - Microsystem - Linear DC –DC
Converters - Switching DC –DC Converters -
Switching AC –DC Converters - Comparison
5.6 Power Losses - Conduction Losses - Switching
Losses - Quiescent Losses - Losses Across Load
Self Learning Topics: Tracking Helicopter Component
Loads with Energy Harvesting Wireless Sensors,
Monitoring Large Bridge Spans with Solar -Powered
Wireless Sensors 06 CO5

Page 100

VI Selected
Applications of
Energy
Harvesting
Systems 6.1 Power Source for Implanted Medical Devices -
Intro duction - Generator Driven by Muscle Power -
Selection of Mechanical -to-Electrical Conversion
Method - Properties of Piezoelectric Material
Relevant to the Generator System - Predicted Output
Power of Generator - Steps Towards Reduction to
Practice
6.2 Piezoelectric Energy Harvesting for Bio -MEMS
Applications - Introduction - General Expression for
Harvesting Energy with Piezoelectric - Unimorph
Diaphragm in Bending - Simply Supported Unimorph
Diaphragm that is Partially Covered with
Piezoelectric Materi al - Clamped Unimorph
Diaphragm that is Partially Covered with
Piezoelectric Material
6.3 Energy Harvesting (EH) for Active RF Sensors and
ID Tags - EH Technologies for RF sensors - EH
Design Considerations - Energy Storage Technologies
- Energy Requirements a nd Power Management
Issues - Vibrational Energy Harvesting - Solar Energy
Harvesting
Self Learning Topics: Powering Wireless SHM Sensor
Nodes through Energy Harvesting 06 CO6
Text Books:
1. Shashank Priya, Daniel J. Inman, "Energy Harvesting Technologies",S pringer New
York, NY, ISBN: 978 -0-387-76463 -4, DOI - https://doi.org/10.1007/978 -0-387-76464 -1
2. Carlos Manuel Ferreira Carvalho, Nuno Filipe Silva Veríssimo Paulino (auth.), "CMOS
Indoor Light Energy Harvesting System for Wireless Sensing Applications [1 ed .]" 978 -
3-319-21616 -4, 978 -3-319-21617 -1, Springer International Publishing 2016.

References:
1. Danick Briand, Eric Yeatman, Shad Roundy (eds.), "Micro Energy Harvesting" ,
Advanced Micro and Nanosystems - Wiley -VCH, 2015.
2. Elena Blokhina, Abdelali El Aroudi , Eduard Alarcon, Dimitri Galayko (eds.),
"Nonlinearity in Energy Harvesting Systems: Micro - and Nanoscale Applications",
Springer International Publishing,978 -3-319-20354 -6, 978 -3-319-20355 -3, 2016.

Page 101

3. Bin Yang, Huicong Liu, Jingquan Liu, Chengkuo Lee, "Micr o and Nano Energy
Harvesting Technologies", Artech House; Illustrated edition (1 Dec. 2014), ISBN -13:
978-1608078141.
Online References:
Selection of Nanomaterials for Energy Harvesting and Storage Applications -
https://onlinecourses.nptel.ac.in/noc19_me7 3/preview

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 co vered 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.

Page 102

Theory Practical Tutorial Theory Practical/
Oral Tutorial Total
IOTDO8013 Information
Retrieval
System 03 -- -- 03 -- -- 03

Subject Code Subject
Name Examination Scheme
Theory Marks
Term
Work Practical Oral Total Internal assessment End
Sem.
Exam Test1 Test 2 Avg. of 2
Tests
IOTDO8013 Information
Retrieval
System 20 20 20 80 -- -- -- 100
Course Objectives: Six Course Objectives
1. To learn the fundamentals of the information retrieval system.
2. To classify various Information retrieval models.
3. To demonstrate the query processing techniques and operations
4.To compare the relevance of query languages for text and multimedia data
5. To analyse the significance of various multimedia information retrieval models.
6. To understand IoT da ta management and analytics.
Course Outcomes: Six 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 Define the objectives of the basic concepts of the Information retrieval system. L1,
2 Apply different information retrieval models to real time world problems. L2, L3
3 Solve text and multimedia retrieval queries and their operations. L3, L4

Page 103

4 Apply text processing techniques and operations in the Information Retrieval
system. L3, L4
5 Analyze various multimedia Information Retrieval models. L3
6 Apply different IoT data management techniques L3

Prerequisite: Indexing and searching Algorithms,Internet of Things (IoT) Fundamentals

DETAILED SYLLABUS: t
Sr.
No. Module Detailed Content Hours CO
Mapping
0 Prerequisite Indexing and searching Algorithms, Internet of Things
(IoT) Fundamentals 02
I Introduction to
Information
Retrieval System Motivation, Basic Concepts, The Retrieval Process,
Information System: Components, parts and types on
information system; Definition and objectives on
information retrieval system, Information versus Data
Retrie val. Search Engines and browsers
Self-learning Topics : Search Engines , Search API 06 CO1
II IR Models Modeling: Taxonomy of Information Retrieval
Models,Retrieval: Formal Characteristics of IR
models, Classic Information Retrieval, Alternative
Set Theoretic models, Probabilistic Models,
Structured text retrieval Models, models for
Browsing;
Self-learning Topics: Terrier - IR Platform and
similar IR Platforms 06 CO2
III Query Processing
and Operations Query Languages: Keyword based Querying, Pattern
Matching, Structural Queries, Query Protocols;
Query Operations: User relevance feedback
Self-learning Topics: Proximity Queries and
Wildcard Queries 05 CO3
IV Text Processing Text and Multimedia languages and properties:
Metadata, Markup Languages, Multimedia; Text
Operations: Document Preprocessing, Document
Clustering.
Self-learning Topics: Digital Library : Greenstone
06 CO4

Page 104

V Multimedia IR
models Inverted files, Other indices for text, Boolean
Queries, Sequential Searching, Pattern Matching,
Structural Queries, Compression
Multimedia IR models: Data Modeling
Multimedia IR: Indexing and Searching: - A Generic
Multimedia indexing approach, ,Automatic Feature
extraction; Searching Web: Challenges,
Characterizing the web, Search Engines. Browsing,
Meta searches, Searching using Hyperlinks
Self-learning Topics: Google Image Search Engine 08 CO5
VI IoT Data
Management and
Anlytics IoT Evolution, IoT Architectures, Resource
Management, IoT Data Management and Analytics,
IoT Applications

Self-learning Topics: ThingSpeak, Ubidots, AWS
cloud platform 06 CO6
Text Books:
1. Modern Information Retrieval, Ricardo Baeza -Yates,berthier Ribeiro - Neto, ACM Press - Addison
Wesley
2. Information Retrieval Systems: Theory and Implementation, Gerald Kowaski, Kluwer Academic
Publisher
3. Internet of Things - Principles and Paradigms, Rajkumar Buyya and Amir V. Dastjerdi, Elesvier
References:
1. Information Retrieval Implementing and Evaluating search Engines by Stefan Buttcher, Charles
L.A. Clarke -The M IT Press Cambridge, Massachusetts London, England
2. Introduction to Information Retrieval By Christopher D. Manning and Prabhakar Raghavan,
Cambridge University Press.
3. Introduction to Modern Information Retrieval. G.G. Chowdhury. NealSchuman.
Online Referenc es:
https://nptel.ac.in/courses/106101007
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.

Page 105

➢ 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.

Page 106

Theo
ry Practic
al Tutorial Theory Practica
l/Oral Tutoria
l Total
IOTDO8014 Next
Generation
IoT
03 -- -- 03 -- -- 03

Subject
Code Subject
Name Examination Scheme
Theory Marks
Term
Work Practica
l Oral Tota
l Internal assessment End
Sem.
Exam Test1 Test
2 Avg. of
2 Tests
IOTDO801
4 Next
Generati
on IoT 20 20 20 80 -- -- -- 100

Course Objective
1. Understand the fundamental concepts and principles of IoT and its role in driving digital
transformation in various sectors, including its impact on the economy and society.
2. Explore the strategic research and innovation trends in IoT, including next -generation
IoT t echnologies, digitization, tactile IoT/IIoT, and digital twins for IoT applications.
3. Gain knowledge of the enabling technologies in IoT, such as edge computing, artificial
intelligence, networks and communication, and distributed ledger technology/blockchain,
and understand their significance in IoT systems.
4. Examine the future trends in IoT, including key technological advancements,
interoperability challenges, and strategies to boost IoT innovation and deployment.
5. Investigate the impleme ntation of IoT in smart environments and applications, including
wearables, smart health, wellness and aging well, smart buildings and architecture, smart
energy, and smart mobility and transport.
6. Explore real-world IoT implementations through the study of European large -scale pilot
projects, focusing on integration, experimentation, testing, and user engagement in IoT
initiatives.

Course Outcome
Sr.
No. Course Outcomes Cognitive
levels of
attainment as
per Bloom’s
Taxonomy

Page 107

On successful completion, of course, learner/student will be able to:
1 Understand the impact of IoT on the economy and society, including its role
as a major enabler for digitizing industries and its implications for projects,
partnerships, and standardization. L1
2 Analyze the European Union's IoT strategy, current state, and future
perspectives, with a focus on research and innovation under Horizon 2020 and
the deployment of IoT within the Next Generation Internet. L2, L3
3 Identify future trends in IoT, including key tec hnological game -changers,
interoperability challenges, and strategies to boost IoT innovation and
deployment. L3
4 Explore the next generation IoT platforms, including the implementation
process, working groups, state of play, and understanding the needs and
priorities for the future IoT platform. L3, L4
5 Evaluate emerging technologies and research trends in IoT, such as next -
generation IoT, tactile IoT/IIoT, digital twins, edge computing, artificial
intelligence, networks and communi cation, and distributed ledger
technology/blockchain L2,L3
6 Examine IoT security technologies, including the identification of emerging
security challenges and the exploration of solutions to ensure secure and
trustworthy IoT systems. L2,L3


SrNo Topics Hours
1 IoT Driving Digital Transformation 4
IoT Driving Digital Transformation – Impact on Economy and Society
1.1 IoT as a Major Enabler for Digitizing Industry, Main Elements of the IoT
Implementation Plan and Its First Pillar, The Second and the Third Pillar –
Projects, Partnerships and Standardisation
1.2 IoT EU Strategy, State of Play and Future Perspectives
Research and Innovation under Horizon 2020, Deployment – IoT Focus Area
and Focus Area on Digitization, IoT within the Next Generation Internet –
Preparing the Next Framework Programme for Research and Innovation
1.3. Future Trends in IoT
Key Technological Game Changers for IoT,Interoperability,Boosting IoT
Innovation and Deployment
1.4 Next Generation IoT Platforms
DEI Implementation – Working Groups, DEI Implementation – Working
Groups, IoT Platforms – State of Play, Needs and Priorities for the Next
Generation IoT platform

2 Internet of Things Cognitive Transformation Technology Research Trends and
Applications 6

Page 108

2.1 Next Generation Internet of Things
2.2 Next Generation IoT Strategic Research and Innovation
Digitisation, Tactile IoT/IIoT, Digital Twins for IoT
2.3 Future Internet of Things Enabling Technologies
Edge Computing, Artificial Intelligence, Networks and Communication,
Distributed Ledger Technology/Blockchain Technology
2.4 Emerging IoT Security Technologies
2.5 IoT/IIoT Technology Market Developments
Digital Business Model Innovation and IoT as a Driver, Business models and
business model Innovation, The use of IoT for digital business development,
The design and implementation processes of digital business development

3 Internet of Things Cognitive Transformation Technology Research Trends and
Applications 10
3.1 Internet of Things Evolving Vision
IoT Common Definition, IoT Cognitive Transformation,
IoT Strategic Research and Innovation Directions , IoT Research Directions and
Challenges
IoT Smart Environments and Applications
IoT Use Cases and Applications, Wearables, Smart Health, Wellness and
Ageing Well, Smart Buildings and Architecture, S mart Energy, Smart Mobility
and Transport
3.2 IoT and Related Future Internet Technologies
Edge Computing, Networks and Communication,
IoT Distributed Security – Blockchain Technology
Verification and Validation in Blockchain, IoT Blockchain Application in
Healthcare, IoT Platforms
3.3 Internet of Robotic Things Concept, IoRT Platforms Architecture,
IoRTapllication


4 IoT European Large -Scale Pilots – Integration, Experimentation and Testing 6
4.1 ACTIVAGE – Activating Innovative IoT Smart Living Environments for
Ageing Well, IoF2020 – Internet of Food and Farm 2020 , MONICA –
Management of Networked IoT Wearables – Very Large Scale Demonstration
of Cultural Societal Applications,
4.2 SynchroniCity: Delivering a Digital Single Market for IoT -enabled Urban
Services in Europe and Beyond

Page 109

4.3 AUTOPILOT – Automated Driving Progressed by Internet of Things ,
CREATE -IoT Cross Fertilisation through Alignment, Synchronisation and
Exchanges fo r IoT
4.4 U4IoT – User Engagement for Large Scale Pilots in the Internet of Things

5. IoT European Security and Privacy Projects: Integration, Architectures and
Interoperability 6
5.1 BRAIN -IoT, Cognitive Heterogeneous Architecture for Industrial
IoT – CHARIOT
5.2 ENACT: Development, Operation, and Quality Assurance
of Trustworthy Smart IoT Systems, Search Engines for Browsing the Internet of
Things – IoTCrawler
5.3 SecureIoT: Multi -Layer Architecture for Predictive End -to-End Internet -of-
Things Security
5.4 SEMIoTICS, SerIoT, SOFIE

6. Future IoT technologies 7
6.1 IoMT,IoAT,IoDT,IoUT
6.2 A Smart Tags Driven Service Platform for Enabling
Ecosystems of Connected Objects
6.3 A Novel IoT Architecture based on 5G-IoT and Next Generation Technologies

Page 110

TextBook
1
Next Generation Internet of Things – Distributed Intelligence at the Edge and Human -Machine
Interactions Vermesan, Ovidiu, Bacquet, Joël River Publishers,
2 Ovidiu Vermesan, Joël Bacquet, Cognitive Hyperconnected Digital Transformation, River
Publishers
3 Nishith Pathak Anurag Bhandari , IoT, AI, and Blockchain for .NET
Building a Next -Generation Application from the Ground Up,apress

4. Bob Familiar,Microservices,IoT , and Azure Leveraging DevOps and Microservice Architecture
to Deliver SaaS Solutions,Apress

5 Anand Tamboli, Build Your Own IoT Platform Develop a Fully Flexible and Scalable Internet
of Things Platform in 24 Hours,apress



Useful Links
IODT
Internet of
Drone
things The Internet of Drones: Requirements, Taxonomy, Recent Advances,
and Challenges of Research Trends https://www.mdpi.com/1424 -8220/21/17/5718

The Internet of Drone Things (IoDT): Future Envision of Smart Drones
https://link.springer.com/chapter/10.1007/978 -981-15-0029 -9_45

IoAT
IoT of
Agriculture
Things Applications of IoT in Agriculture - Making Agriculture Smarte
https://www.biz4intellia.com/blog/5 -applications -of-iot-in-agriculture/

IOT IN AGRICULTURE:
9 TECHNOLOGY USE CASES FOR SMART FARMING
(AND CHALLENGES TO CONSIDER)
http://ml6.in/ABKwx
Smart Farming: Internet of Things (IoT) -Based Sustainable Agriculture
https://www.mdpi.com/2077 -0472/12/10/1745

IoMT
IoT Medical
things Internet of Medical Things (IoMT) - An overview
https://ieeexplore.ieee.org/document/9075733

Internet of Medical Things (IoMT): Overview, Emerging Technologies,

Page 111

and Case Studies
https://www.tandfonline.com/doi/full/10.1080/02564602.2021.1927863
Internet of Medical Things (IoMT) - Based Smart Healthcare System: Trends and
Progress http://ml6.in/eteYj


IoUT
Under ground
and Under
water An overview on IoUT and the performance of WiFi low -cost nodes for IoUT
Applications https://ieeexplore.ieee.org/document/9348057

Internet of underwater things: Challenges and routing protocols
https://ieeexplore.ieee.org/document/8394494
Batteryless IoT Sensor to be used underwater and in outer space
https://www.onio.com/article/batteryless -io-sensor -underwater -and-outer -space.h tml
Towards the internet of underwater things: a comprehensive survey
https://www.researchgate.net/publication/359064835_
Towards_the_internet_of_underwater_things_a_comprehensive_survey

Papers
P1 Next Generation Internet of Things
https://www.ngiot.eu/wp -content/uploads/sites/73/2020/03/NGIoT_D2.1_Revised.pdf
https://www.ngiot.eu/wp -content/uploads/sites/73/2020/03/NGIoT_D2.1_Revised.pdf
P2 Blockchain -Driven Intelligent Scheme for IoT -Based Public
Safety System beyond 5G Networks
https://www.mdpi.com/1424 -8220/23/2/969
P3 From IoT to 5G I -IoT: The Next Generation IoT -Based Intelligent Algorithms and 5G
Technologies https://ieeexplore.ieee.org/document/8519960
P4 Next -Generation Internet of Things (IoT): Opportunities, Challenges, and
Solutions https://www.mdpi.com/1424 -8220/21/4/1174
P5 INTERNET OF THINGS (IOT) AND 5G BASED SMART ALGORITHM
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3878692

Assessment: Internal Assessment (IA) for 20 marks:
● IA will consist of Two Compul sory 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.

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● 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.

Page 113

Theor
y Practical Tutorial Theory Practical/
Oral Tutorial Total
IOTDO8021 Business Process
Management &
Cognitive IoT 03 -- -- 03 -- -- 03

Subject Code Subject Name Examination Scheme
Theory Marks
Term
Work Practical Oral Total Internal assessment
End
Sem.
Exam T
e
st
1 Test 2 Avg. of 2
Tests
IOTDO8021 Business Process
Management &
Cognitive IoT 2
0 20 20 80 -- -- -- 100

Course Objectives: The course aims at:
1. To understand the fundamental concepts, terminology and benefits of business process
management(BPM).
2. To understand the fundamental concepts of the cognitive Internet of Things (IoT).
3. To identify the benefits using BPM concepts in the management of IoT applications, benefits
of using IOT in BPM and the intersections/challenges in the two paradigms.
4. To understand cognitive enterprises, analyze existing pr ocesses of the system, and understand
the opportunities to apply cognitive -IOT in them using the design principles of cognitive IOT.
5. To understand management of Cognitive IoT -enabled Business Processes.
6. To understand the use cases of cognitive -IOT.

Course Outcomes: On successful completion, of course, learner/student will be able to:

Sr.
No. Course Outcomes Cognitive
levels of
attainment
as per
Bloom’s
Taxonomy
On successful completion, of course, learner/student will be able to:

Page 114

1 Describe the fundamental concepts, terminology and benefits of business process
management(BPM). L2
2 Understand the fundamental concepts of the cognitive Internet of Things (IoT). L2
3 Relate the benefits using BPM concepts in the management of IoT applications,
benefits of using IOT in BPM and the intersections/challenges in the two
paradigms. L2
4 Design the application areas of cognitive -IOT in enterprise processes of the system
using appropriate cognitive IOT design principles. L6
5 Develop strategy for management of cognitive IoT -enabled Business Processes. L6
6 RExamine the use cases of cognitive -IOT. L4


Prerequisite: IoT Architecture and Protocols
DETAILED SYLLABUS:
Sr.
No. Module Detailed Content Hour
s CO
Mapping
0 Prerequisite Sensors, Characteristics of IoT, Conceptual
Framework of IoT, Physical and Logical design of
IoT, Functional blocks of IoT, Communication
models and APIs, Architecture and Protocols 02 CO1
I Introduction to
Business Process
Management
(BPM) Defining BPM, BPM Lifecycle, Benefits and
Importance of BPM in Organizations: Improved
Efficiency, Enhanced Quality, Increased Agility,
Cost Savings, Customer Satisfaction, Compliance
and Risk Management, Continuous Improvement,
Key Concepts and Terminolog ies in BPM: Process,
Process Owner, Process Mapping, Process
Analysis, Process Design, Process Automation, Key
Performance Indicators (KPIs)
Self-study: Drivers and triggers for BPM,
approaches followed in BPM 05 CO1

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II Fundamentals of
Cognitive IoT Introduction to Cognitive IoT, Need for Cognitive
IoT, Key Components and Technologies in
Cognitive IoT: Sensors and Actuators,
Connectivity, Cloud Computing, Artificial
Intelligence (AI), Edge Computing, Data Analytics.
Current and Future trends of IoT, C ognitive
computing and applications. Security in Cognitive
IoT: Security issues in IoT, A hardware assisted
approach for security, Architectural level overview
for providing security, Security threats.
Self-study: Data Analytics of Cognitive IoT, Cloud
and Edge Computing in IoT 08 CO2
III Integrating
Cognitive IoT with
BPM Benefits of Cognitive IoT with BPM and vice versa,
Factors to be considered for integrating Cognitive
IoT with BPM such as placement of sensors,
management of manually executed physical
processes, connection of analytical processes with
IoT, integrating Io T with process correctness
checks, dealing with unstructured environments,
segregating end -to-end processes, identifying new
processes from data, etc.

Self-study: Cognitive process transition and
adoption phases 08 CO3
IV Designing
Cognitive IoT -
enabled Business
Processes Introduction to Cognitive Enterprise, Building
Cognitive Enterprise: Market -making Business
Platforms, Intelligent Workflows, Enterprise
Experience and Humanity

Analyzing existing business processes, Identifying
opportunities for auto mation and cognitive decision
making

Cognitive Design Principles: Context -awareness,
data-driven decision making, event -driven triggers,
human -machine collaboration, security and privacy,
scalability and interoperability, and continuous
improvement.

Self-study: Design Principles for Industrial
Cognitive Automation 07 CO4
V Managing
Cognitive IoT -
enabled Business
Processes Strategic planning, operational execution, and
continuous monitoring.
Steps for managing cognitive IoT -enabled business
processes: define clear business objectives, identify
relevant use cases, design and architect cognitive 06 CO5

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IoT solutions, deploy and implement solutions,
monitor and optimize performance, ensure Security
and privacy.

Self-study: Role of BPM methodologies,
frameworks, and tools in managing Cognitive IoT -
enabled processes
VI Use Cases Applications of Cognitive IoT: Smart Home
Automation, Industrial Automation and Predictive
Maintenance, Healthcare and R emote Patient
Monitoring, Smart Agriculture, Supply Chain
Optimization.

Self-study: Energy Management, Intelligent
Transportation Systems, Environmental Monitoring 03 CO6

Text Books:
1. Fundamentals of Business Process Management by Marlon Dumas, Marcello La Rosa, Jan
Mendling Hajo A. Reijers, Springer.
2. The Process Improvement Handbook: A Blueprint for Managing Change and Increasing
Organizational Performance by Marlon Dumas , Marc ello La Rosa.
3. Business Process Management: Concepts, Languages, Architectures by Mathias Weske (2019)
4. Business Process Management Practical Guidelines to Successful Implementations by John Jeston
(2022)
5. The Business of Things: Designing business models to win in the cognitive IoT by IBM Institute
for Business Value.
6. Building the Cognitive Enterprise: Nine Action Areas by IBM Institute for Business Value
7. IoT Solutions in Microsoft's Azure IoT Suite: Data Acquisition and Analysis in the Real World
by Scott Klein (2017)
8. IoT Fundamentals: Networking Technologies Protocols and Use Cases for the Internet of Things
by Hanes David, Salgueiro Gonzalo, Grossetete Patrick, Barton Rob, Henry Jerome (2017)
9. The Internet -of-Things Meets Business Process Management: A Manifesto Christian Janiesch,
Agnes Koschmider, Massimo Mecella, Barbara Weber, Andrea Burattin, Claudio Di Ciccio,
Giancarlo Fortino, Avigdor Gal, Udo Kannengiesser, Francesco Leotta, Felix Mannhardt, Andrea
Marrella, Jan Mendling, Andreas Oberweis, Manfred Reichert, Stefanie Rinderle -Ma, Estefania
Serral Asensio, WenZhan Song, Jianwen Su, Victoria Torres, Matthias Weidlich, Mathias Weske,
and Liang Zhang.
References:

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1. Digital Transformation: Survive and Thrive in an Era of Mass Ex tinction by Thomas M. Siebel (2019)
2. How Cognitive Computing Unlocks Business Process Management’s Performance -Enhancing Virtues
3. The design of things: Building in IoT connectivity - The Internet of Things in product design: A
research collaboration be tween Deloitte and IBM
4. BPM Everywhere: Internet of Things, Process of Everything by Nathaniel Palmer, Scott Francis, Peter
Whibley (2019)
5. Enabling Things to Talk: Designing IoT solutions with the IoT Architectural Reference Model by
Alessandro Bass i, Martin Bauer, Martin Fiedler, Thorsten Kramp, Rob van Kranenburg, Sebastian Lange,
Stefan Meissner (2013)
6. Building the Internet of Things: Implement New Business Models, Disrupt Competitors, Transform
Your Industry by Maciej Kranz (2016)
7. Cognitive Internet of Things: A New Paradigm Beyond Connection Qihui Wu, Guoru Ding, Yuhua Xu,
Shuo Feng, Zhiyong Du, Jinlong Wang, and Keping Long.
8. Cognitive Business Operations: Processes and decisions that sense, respond, and learn by IBM.
Online References:
1. Architectural Threats to Security and Privacy: A Challenge for Internet of Things (IoT) Applications
(Link: https://www.mdpi.com/2079 -9292/12/1/88)
2. Cognitive Automation in Industry – Design Principles and Case Study (Link:
https://www.ripublication. com/ijaer18/ijaerv13n20_51.pdf)
3. IBM: BPM, Workflow, and Case (IBM Business Automation) (Link:
https://community.ibm.com/community/user/automation/communities/community -
home?CommunityKey=810abde6 -3916 -441b -aac3-b9105bb37e3c)
4. Cognitive IoT: Unleashing the future potential of IoT systems (Link: https://www.iot -
now.com/2023/04/13/129617 -cognitive -iot-unleashing -the-future -potential -of-iot-systems/)

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.

Page 118

● 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 t hen part
(b) must be from any other Module randomly selected from all the modules).
● A total of four questions need to be answered.

Page 119

Course Code Course Name Theory Practical Tutorial Theory Practical
/Oral Tutorial Total
IOTDO8022 RESTful
Design for IoT
Systems 03 -- -- 03 -- -- 03

Course
Code Course
Name Examination Scheme
Theory Marks
Term
Work Practical Oral Total Internal assessment End
Sem.
Exam Test
1 Test 2 Avg. of 2
Tests
IOTDO8022 RESTful
Design for
IoT Systems 20 20 20 80 -- -- -- 100

Course Objectives:
Sr. No. Course Objectives
The course aims:
1 To understand the concept of RESTful architecture .
2 To familiarize a standardized way of integrating Web -based applications .
3 To design the API to access the data of IOT components for secure communication.
4 To identify the issues and challenges associate with scalability in RESTful IoT systems.
5 To Explore and Analyze the concept of AI integration with RESTful APIs in IOT.
6 Enable the students to analyze real -world implementations of RESTful design for IoT
systems.

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 Conceptual Framework and methods of RESTful
architecture L1,L2
2 Understand how web service enables the communication among
various applications . L1,L2,L3
3 Designing standard framework for connecting various IOT
applications L1,L2,L3
4 Identify the issues Associated With IoT Scalability. L1,L2
5 Analyze different IOT protocols for integration with RESTful L1,L2,L4

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APIs.
6 Analyze and evaluate Real world RESTful design for various
IoT systems L1,L2,L3,L4



DETAILED SYLLABUS:

Sr.
No. Module Detailed Content Hour
s CO
Mapping
0 Prerequisite IoT concepts and principles,Basics of HTML,XML,CSS
and Database Concepts, Knowledge of HTTP request and
HTTP response 02 --
I Introduction to
RESTful Design RESTful architecture : RESTful relevance to IoT.
Principles of Representational State Transfer (REST).
HTTP methods (GET, POST, PUT, DELETE). Resource
modeling and URI design for IoT devices and services.
Benefits and challenges of using REST for IoT systems.

Self-learning Topics:
Case Study on allow the users to do the four methods of HTTP
to create RESTful API 04 CO1
II Web Services
Design XML Representations: XML Parsers. Design
JSON Representations. JSON Parsers.Links in XML
Representations. Links in JSON Representations.Assign
Link Relation Types. Manage Application Flow.Clients
Made Easy with WAD.

Self-learning Topics: Case study on Writing Web services
for Client Communication using Various languages HTTPs
Library 06 CO2
III Designing
RESTful APIs
for IoT Systems API design principles and best practices: Creating
resource representations for IoT devices and sensors.
Implementing CRUD operations on IoT resources.
Interacting with IoT Resources through RESTful APIs.
Resource discovery and registration in IoT systems.
Performing data retrieval, filtering, an d aggregation.
Security and Authentication in RESTful IoT Systems
Self-learning Topics : Case Study on Design of RESTful
APIs for M2M services 06 CO3
IV Managing
scalability
challenges in
RESTful IoT
systems Caching strategies and content delivery networks (CDNs)
for improved performance. Load balancing and horizontal
scaling techniques. Integrating IoT with Cloud Services
using RESTful APIs. Connecting IoT devices and services
with cloud platforms. Using REST ful APIs to interact with 06 CO4

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cloud -based IoT platforms. Handling data storage,
analytics, and visualization in the cloud
Self -learning Topics: Case Study on Best Practices to
manage the scalability and complexity of IoT infrastructure
V ML & AI
Integration Industry standards and protocols for IoT
communication: Exploring emerging trends and
technologies in RESTful IoT systems. Machine learning
and AI integration with RESTful APIs in IoT. Traffic and
Transportation Optimization, RESTful services t o analyze
sensor data for environmental monitoring. Edge computing
and fog computing for improved IoT performance.
Integration of standards like MQTT, CoAP, and
WebSocket with RESTful APIs. Interoperability
considerations in IoT systems

Self-learning Topi cs: Case study on IoT communication
protocols (bluetooth,wifi,
LTE,etc)to and meet the specific functional requirement of
an IoT system .. 09 CO5
VI Case Studies
and Real -World
Examples Real -world implementations of RESTful design for IoT
systems: Examining use cases across different industries
(e.g., smart homes, industrial IoT, healthcare). Case studies
on Twitter API, GitHub API, Amazon Web Services
(AWS) API, Google Maps API, Stripes API. Analyzing
challenges and lessons learned from deployed s ystems 06 CO6



Text Books:
1. "RESTful Web Services Cookbook" by Subbu Allamaraju
2. “RESTful Web Services”by Leonard Richarson.
3. "RESTful IoT with MQTT and Node -RED" by Colin Dow and Tim Pulver
4. "RESTful Java with JAX -RS 2.1: Designing and Developing Distributed Web Services"
by Bill Burke
5. "Building the Web of Things: With examples in Node.js and Raspberry Pi" by
Dominique D. Guinard and Vlad M. Trifa
6. "Designing Connected Products: UX for the Consumer Internet of Things" by Claire
Rowland, Elizabeth Go odman, Martin Charlier, and Ann Light .

References:

1. "Designing the Internet of Things" by Adrian McEwen and Hakim Cassimally
2. “Internet Of Things: A Hands -On Approach Paperback”, by Arsheep Bahga (Author),
Vijay Madisetti, Universities Press, Reprint 2020
3. “IoT Fundamentals Networking Technologies, Protocols, and Use Cases for the Internet
of Things CISCO” by David Hanes, Gonzalo Salgueiro, Patrick Grossetete, Robert

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Barton, Jerome Henry,

Online References:

1. https://www.udemy.com/course/api -and-webservices/
2. https://restfulapi.net/rest -api-design -tutorial -with-example/
3. https://www.mygreatlearning.com/iot/free -courses
4. https://www.researchgate.net/figure/RESTful -services -design -for-IoT-
systems_fig3_339025795
5. https://www.edureka.co/blog/what -is-rest-api/

Assess ment:

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 ea ch
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.

Page 123

Theory Practical Tutoria
l Theor
y Practica
l/Oral Tutorial Tota
l
CSDO8023 Green IT 03 -- -- 03 -- -- 03

Subject
Code Subject
Name Examination Scheme
Theory Marks
Term
Work Practical Oral Total Internal assessment End
Sem.
Exam Test
1 Test 2 Avg. of 2
Tests
CSDO8023 Green IT
20 20 20 80 -- -- -- 100

Course Objectives:
1. To understand what Green IT is and How it can help improve environmental
Sustainability.
2. To understand the principles and practices of Green IT.
3. To understand how Green IT is adopted or deployed in enterprises.
4. To understand how data centers, cloud computing, storage systems, software and
networks can be made greener.
5. To measure the Maturity of a Sustainable ICT world.
6. To implement the concept of Green IT in Informa tion Assurance in
Communication and Social Media and all other commercial field.
Course Outcomes:
Course
Outcom
e Course Outcome Statement Cognitive Levels
of attainment as
per Bloom’s
taxonomy

Page 124

CO 1 Describe awareness among stakeholders and promote green
agenda and green initiatives in their working environments
leading to green movement. L1
CO2 Identify IT Infrastructure Management and Green Data Center
Metrics for software development L1 L2
CO3 Recognize Objectives of Green Network Protocols for Data
communication. L1 L2
CO4 Apply Green IT Strategies and metrics for ICT development. L1 L2 L3
CO5 Illustrate various green IT services and its roles L1 L2
CO6 Demonstrate and use new career opportunities available in IT
profession, audits and others with special skills such as energy
efficiency, ethical IT assets disposal, carbon footprint
estimation, reporting and development of green products,
applications and services. L1 L2 L3

Prerequisite: Environmental Studies
DETAILED SYLLABUS:
Sr.
No. Module Detailed Content Hours CO
Mapping
0 Prerequisite Environmental Studies 2
I Introduction Environmental Impacts of IT, Holistic Approach to
Greening IT, Green IT Standards and Eco -Labeling,
Enterprise Green IT Strategy, Green IT: Burden or
Opportunity?
Hardware: Life Cycle of a Device or Hardware,
Reuse, Recycle and Dispose.
Software: Introdu ction, Energy Saving Software
Techniques, Evaluating and Measuring Software
Impact to Platform Power.
Self-Learning: Evaluating and Measuring software
impact to platform power 6 CO1
II Software
development
and data
centers Sustainable Software, Software Sustainability
Attributes, Software Sustainability Metrics,
Sustainable Software Methodology, Data Centers and
Associated Energy Challenges, Data Centre IT
Infrastructure, Data Centre Facility Infrastructure: 6 CO1 CO2

Page 125

Implications for Energy Efficiency, IT Infrastructure
Management, Green Data Centre Metrics
Self-learning Topics: Sustainable Software: A Case
Study, Data Centre Management Strategies
III Data storage
and
communicati
on Storage Media Power Characteristics, Energy
Management Techniques for Hard Disks, System -
Level Energy Management, Objectives of Green
Network Protocols, Green Network Protocols and
Standards
Self-learning Topics: System -Level Energy
Management 6 CO1 CO3
IV Information
systems,
green IT
strategy and
metrics Approaching Green IT Strategies, Business Drivers
of Green IT Strategy, Business Dimensions for Green
IT Transformation, Multilevel Sustainable
Information, Sustainability Hierarchy Models,
Product Level Information, Individual Level
Information, Functional Level Information,
Organizational Level Information, Regional/City
Level Information, Measuring the Maturity of
Sustainable ICT.
Self-learning Topics: Business Dimensions for
Green IT transformation. 6 CO1 CO4
V Green IT
services and
roles Factors Driving the Development of Sustainable IT,
Sustainable IT Services (SITS), SITS Strategic
Framework, Sustainable IT Roadmap, Organizational
and Enterprise Greening, Information Systems in
Greening Enterprises, Greening the Enterprise: IT
Usage and Hardware, Inter -organizational Enterprise
Activities and Green Issues, Enablers and Making the
Case for IT and the Green Enterprise.
Self-learning Topics: Inter-organizational Enterprise
Activities and Gre en Issues, Enablers and Making the
Case for IT and the Green Enterprise. 6 CO1 CO4
CO5
VI Managing
and
regulating
green IT Strategizing Green Initiatives, Implementation of
Green IT, Information Assurance, Communication
and Social Media, The Regulatory E nvironment and
IT Manufacturers, Nonregulatory Government
Initiatives, Industry Associations and Standards
Bodies, Green Building Standards, Green Data
Centers, Social Movements and Greenpeace. Case 7 CO1 CO5
CO6

Page 126

study on: Industry Sustainability with Green IT,
Managin g Green IT, The energy consumption in
Torrent systems with malicious content, The use of
thin client instead of desktop PC
Self-learning Topics: Information Assurance, Green
Data Centers
Text Books:
1. San Murugesan, G. R. Gangadharan, Harnessing Green IT, WILEY 1st Edition -2018
2. Mohammad Dastbaz Colin Pattinson Babak Akhgar, Green Information Technology A
Sustainable Approach , Elsevier 2015
3. . Reinhold, Carol Baroudi, and Jeffrey Hill Green IT for Dummies, Wiley 2009
References:
1. Mark O’ Neil, Green IT for Sustainable Business Practice: An ISEB Foundation Guide,
BCS
2. Jae H. Kim, Myung J. Lee Green IT: Technologies and Applications, Springer, ISBN:
978-3-642- 22178 -1
3. Elizabeth Rogers, Thomas M. Kostigen The Green Book: The Everyday Guide to Saving
the Planet One Simple Step at a Time, Springer
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
● Remain ing 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.

Page 127

Theory Practical Tutorial Theory Practical/
Oral Tutorial Total
CSDO8024 IoT for Smart
Grids 03 -- -- 03 -- -- 03

Subject Code Subject Name Examination Scheme
Theory Marks
Term
Work Practical Oral Total Internal assessment End
Sem.
Exam Test
1 Test 2 Avg. of 2
Tests
CSDO8024 IoT for
Smart Grids 20 20 20 80 -- -- -- 100

Course Objectives:

Sr. No. Course Objectives
The course aims:
1 To impart knowledge of futuristic power grid technology and the path on which development is taking
place.
2 To elaborate the fundamentals of various technologies and tools which will play a vital role in formation
of the Smart grids in near future.
3 To familiarize the students with distribution management systems in smart grid.
4 To expose students to various communication protocols used in smart grid.
5 To acquaint students with knowledge of smart meters and infrastructure in smart grid.
6 To understand different data management tools in a sm art grid.

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 identify the role and significance of smart in future power systems L1, L2
2 To evaluate and compare applications of smart measurement and monitoring
technologies. L1, L2, L3, L4
3 To describe the role of a distribution management system in a smart grid. L1, L2
4 To select and analyze different communication protocols for different applications L1, L2, L3, L4

Page 128

in a smart grid.
5 To illustrate the importance of advanced metering infrastructure in smart grids. L1, L2, L3
6 To apply data management techniques and develop machine learning algorithms
for smooth operation of smart grid. L1, L2, L3, L4, L5

Prerequisite: IoTC601: IoT Architecture and Protocols, CSDO701X IoT for Smart Cities
DETAILED SYLLABUS:
Sr.
No. Module Detailed Content Hours CO
Mapping
0 Prerequisite Fundamentals of Power Distribution System, Transmission
and Distribution, Power system Operation and Control,
Communication Networks 2 -
I Smart Grid:
Architecture and
Design 1.1. Introduction, Smart Grid Drivers
1.2. Transformation of the Grid
1.3. Characteristics of a Smart Grid
1.4. Smart Grid Technology Framework
1.5. Benefits of Smart grid

Self-Learning Topics: Smart grid architecture around the
globe 5 CO1
II Smart Grid
Technology 2.1 Smart Energy Resources - Renewable energy
generation
2.2 Energy storage
2.3 Electric vehicles
2.4 Energy Resources Integration Challenges, Solutions,
and Benefit
2.5 Smart Substation - Protection, Monitoring, and Control
Devices (IEDs) – Sensors – SCADA
2.6 IEC 61850 -Based Substation Design
2.7 Energy Management Systems
2.8 Wide Area Monitoring, Protection and Control
(WAMPAC)
2.9 Role of WAMPAC and Transmission Systems in a
Smart Grid

Self-Learning Topics: Microgrids versus smart grids 9 CO2
III Smart Distribution
Systems 3.1 Distribution Management Systems
3.2 Volt/VAr Control
3.3 Fault Detection, Isolation, and Service Restoration
3.4 Outage Management
3.5 Consumer Demand Management
5 CO3

Page 129

Self-Learning Topics: High -Efficiency Distribution
Transformers
IV Communication
Networks and
Cyber Security 4.1 Communications Requirements for the Smart Grid
4.2 Communication layer - Home automation network,
Building automation network, Neighbourhood area
network, Local area network, Field area network, Wide
area network
4.3 Wireless Network Solutions for Smart Grid - Cellular,
RF Mesh
4.4 Communication Stan dards and Protocols - IEC 61850,
DNP3 and IEC 60870 -5
4.5 IEEE C37.118, IEC 61968 -9 and MultiSpeak, ANSI
4.6 Communications Challenges in the Smart Grid
4.7 Cyber Security for Smart Grid.

Self-Learning Topics: Probable attacks on smart grid. 8 CO4
V Smart Meters and
Advanced
Metering
Infrastructure
(AMI) 5.1 Evolution of the Electric Meter, and Meter Reading
5.2 AMI Drivers and Benefits
5.3 AMI Protocols, Standards, and Initiatives
5.4 AMI Security
5.5 AMI Needs in the Smart Grid
5.6 Phasor Measurement Unit.

Self-Learning Topics: Smart appl iances 6 CO5
VI Data Management
and Forecasting 6.1 Smart Grid Data Management, Characterization of
Smart Grid Data
6.2 Secure Information and Data Management Architecture
6.3 Secure Data Management, Applications of Smart Grid
Data
6.4 Importance of machine learning in energy forecasting,
Big data in smart grid.

Self-Learning Topics: Renewable Energy Forecasting,
Fault Detection and Predictive Maintenance, Data
Visualization and Decision Support 4 CO6

Text Books:
1. James Momoh, “Smart Grid:Fundamentals of Design and Analysis”, IEEE Press and Wiley
Publications, 2015
2. K. Liyanage, Jianzhong Wu, A. Yokoyama, Nick Jenkins J.Ekanayake, “Smart Grid: Technology
and Applications”, Wiley Publications , 2015
3. Stuart Borlase, “Smart Grids: Infras tructure, Technology, and Solutions”, CRC Press, 2012
4. Clark W. Gellings, “The Smart Grid: Enabling Energy Efficiency and Demand Response”, CRC
Press

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References:
1. Mini S. Thomas, John D McDonald, “Power System SCADA and Smart Grids”, CRC Press,
2015
2. Kenneth C.Budka, Jayant G. Deshpande, Marina Thottan, “Communication Networks for Smart
Grids”, Springer, 2014.
3. H. T. Mouftah, and M. Erol -Kantarci, “Smart Grid: Networking, Data Management, and Business
Models”, CRC Press, 2016
4. Yang Xiao, “Communication and Networking in Smart Grids”, CRC Press, 2012

Online References:
1. https://onlinecourses.nptel.ac.in/noc23_ee60/preview
2. https://onlinecourses.nptel.ac.in/noc21_ee68/preview
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 qu estions 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) fro m
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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Teaching Scheme (Contact
Hours)
Credits Assigned
Subject Code Subject Name Theory Practical Tutorial Theory Oral Tutorial Total
IOTL801 IoT
Automation
Lab
- 02 -- -- - -- 2

Subject
Code Subject
Name Examination Scheme
Theory Marks
Term
Work Practical/Oral Total Internal assessment End
Sem.
Exam Test1 Test 2 Avg. of
2 Tests
IOTL801 IoT
Automation
Lab
- - - - 25 25 50

Lab Objectives: The course will help the students to:
1. Understand the significance of the Internet of Things for real time applications.
2. Explore different protocols for communication used in IoT systems to other third -party
Clouds.

3. Illustrate PLC programming with real time examples for industrial automation.
4. Study of database collection using controller boards in IoT systems.
5. Explore the relationship between IoT, cloud computing, and DevOps .
6. Examine real time a pplications using IoT systems in different environments.

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:

Page 132

1
Demonstrate the use of various IoT simulators in real time applications.
L3
2 Implement different protocols for Integrating IoT services to other third -
party Clouds.
L3
3 Develop PLC programming with real time examples on industrial
automation. L6
4 Demonstrate the working of databases on controller boards for data
analysis in IoT systems. L3
5 Execute DevOps methodologies for continuous integration and continuous
deployment of IoT applications. L3
6 Develop real time applications usi ng IoT systems in different environments. L6
Prerequisite:
Basics of IoT Architecture and Protocols, Introduction to Embedded and Control systems.
Hardware Requirements Software Requirements Other Requirements
PC With Following
Configuration
1. Intel PIV Processor
2. 4 GB RAM
3. 500 GB Hard disk
4. Network interface card
5. Sensors
6. IoT Kit (Raspberry
Pi/NodeMCU/ESP32)
7. Actuators 1. Windows or Linux
Desktop OS
2.Python
3. IoT Simulator/Emulator
(open source)
4. Delta ISPSoft
5. DOPSoft
5. Devops 1. Internet Connection for installing
additional packages if required

Suggested List of Experiments.
Sr.
No List of Experiments.
LO

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1 To study and demonstrate use of IoT simulators (like Bevywise, COOJA, or
Cupcarbon ) on any real time application. LO1
2
Real time data acquisition and transmission using NodeRed simulator. LO1
3 To study and simulate CoAP protocol in Contiki OS. LO1
3 To study and implement a program on ESP32/NodeMCU to push and retrieve the
data from any cloud like Thingspeak, Thingsboard, AWS, Azure etc. LO2
4 Connecting Raspberry Pi to AWS/Microsoft Iot Core : Setup and code Using Python
and AWS IOT. LO2
6 To study PLC basics, programming elements and their o peration for Ladder
Diagram in IIoT. LO3
7 To develop PLC programming examples on industrial automation using Delta
ISPsoft. LO3
8 To design HMI for PLC programming examples using Delta ISPsoft and DOPSoft. LO3
9 To install MySQL database on Raspberry Pi and perform basic SQL queries for
analysis of data collected. LO4
10 To study and implement Continuous Integration using Jenkins on IoT data and also
perform interfacing of Raspberry Pi into Jenkins. LO5
11 To study and implement Continuous Deployment (Infrastructure as a code) for IoT
using Ansible. LO5
12 Select any one case study (in a group of 3 -4) which will be a solution to a real
problem and can be eased with the use of automation and IOT. The sample case
studies can be as follows:
● Smart agriculture System
● Smart Home Automation
● Smart Cities
● Smart Healthcare system,
● Smart Traffic Management System, etc. LO6

Text & Reference Books:

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● “Hands -On Industrial Internet of Things” by Giacomo Veneri and Antonio Capasso
(Packt)
● “IoT Fundamentals – Networking Technologies, Protocols, and Use Cases for the
Internet of Things”, David Hanes, Gonzalo Salgueiro, Patrick Grossetete, Rob Barton,
Jerome Henry,1st Edition, Published by Pearson Education, Inc, publishing as Cisco
Press, 2017.
● Honbo Zhou,” The internet of things in the cloud”, CRC press, Taylor and Francis
group.
● “PLC Programming for Industrial Automation” Kevin Collins, Exposure Publishing,
2006.
● Joakim Verona,” Practical DevOps”, PACKT publishing, 2016.
Online Resources:
1. http://www.contiki -os.org/
2. https://www.bevywise.com/iot -simulator/
3. https://mqtt.org/
4. https://shorturl.at/kwCV0
5. https://docs.aws.amazon.com/iot/latest/developerguide/connecting -to-existing-
device.htm
6. https://shorturl.at/kzDJ1
7. https://shorturl.at/jor49
8. https://www.nsnam.com/2016/01/iot -coap -implementation -in-contiki -os.html
9. https://www.udemy.com/course/i spsoft -for-delta -plc-programming/
10. http://surl.li/hwxci
11. http://surl.li/hwxek
12. https://nodered.org/docs/tutorials/

Term Work:
1 Term work should consist of 10 experiments
2 Journal must include at least 2 assignments based on Theory and Practical
3 The final certification and acceptance of term work ensures satisfactory performance of
laboratory work and minimum passing marks in term work.
4 Total 25 Marks (Experiments: 15-marks, Attendance Theory & Practical: 05 -marks,
Assignments: 05 -marks)
Oral exam:
Based on the entire syllabus of IOTC801 Industrial IoT and IOTL801 IoT Automation Lab

Page 135

Teaching Scheme (Contact
Hours)
Credits Assigned
Subject Code Subject Name Theory Practical Tutorial Theory Oral Tutorial Total
CSL802 Cyber Security
Lab -- 4 -- -- 2 -- 2

Subject
Code Subject Name Examination Scheme
Theory Marks
Term
Work Oral Total Internal assessment End
Sem.
Exam Test1 Test 2 Avg. of
2 Tests
CSL802 Cyber
Security Lab -- -- -- -- 50 -- 50

Lab Objectives:
● To detect the web application and browser vulnerabilities using various open -source tools
● To explore the network vulnerabilities using various open -source tools
● To conduct digital investigations that conform to accepted professional standards and are
based on the investigative process, including the concept of the chain of evidence
● To identify, preserve, examine, analyze, and report the findings from digital forensics
invest igation
● To recover the digital evidences from various digital devices
● To Explore various forensics tools in Kali Linux and use them to acquire, duplicate and
analyze data and recover deleted data
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:

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1 Gain hands -on experience in cracking passwords using various techniques and
tools & develop skills in capturing and analyzing network traffic to identify
security vulnerabilities and potential threats. L1, L2
2
Understand the techniques used in phishing attacks and learn to recognize and
mitigate such attacks & acquire skills in analyzing malware samples to
understand their behavior and implement appropriate defenses. L3, L4
3
Gain knowledge of firewall vulnerabilities and learn techniques to bypass them
& understand the security vulnerabilities of wireless networks and implement
measures to protect against attacks. L2, L3
4
Develop skills in id entifying and mitigating web application vulnerabilities to
enhance security & understand the techniques used in social engineering
attacks and develop awareness to prevent such attacks. L2, L3
5
Gain practical experience in implementing and analyzing cryptographic
algorithms & develop skills in responding to security incidents effectively and
efficiently. L2, L3
6
Understand various techniques used for data exfiltration and develop
countermeasures to protect against them & acquire knowledge of IoT device
vulnerabilities and learn techniques to secure them. L1, L2, L3, L4

Prerequisite: Basic Networking Concepts, Programming languages, Cybersecurity
fundamentals, Cryptography basics
Sr.
No. Experiment Details LO
Mapping
1 Password Cracking:

Tools: John the Ripper, Hashcat, Hydra
Experiment: Use different password cracking techniques such as brute force attacks,
dictionary attacks, or rainbow table attacks on password -protected files or accounts. LO1
2 Network Sniffing:

Tools: Wireshark, tcpdump
Experiment: Capture network traffic and analyze it to understand the flow of data,
identify potential security vulnerabilities, and observe any sensitive information being
transmitted. LO1

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3 Phishing Attacks:

Tools: GoPhish, Social -Engineer Toolkit (SET)
Experiment: Set up a simulated phishing campaign to send deceptive emails and track
the recipients' responses, measuring the success rate and effectiveness of the phishing
attack. LO2
4 Malware Analysis:

Tools: IDA Pro, OllyDbg, VirusTotal
Experiment: Analyze malware samples in a controlled environment, investigate their
behavior, reverse -engineer their code, and understand their propagation methods. LO2
5 Firewall Bypassing:

Tools: Metasploit, Nmap, Netcat
Experiment: Identify vulnerabilities in firewalls or network devices and attempt to
bypass their security mechanisms to gain unauthorized access to a network or system. LO3
6 Wireless Network Security:

Tools: Aircrack -ng, Kismet, Reaver
Experiment: Assess the security of wir eless networks by cracking WEP or
WPA/WPA2 encryption, implementing attacks like deauthentication attacks or
capturing handshakes for offline cracking. LO3
7 Web Application Security:

Tools: Burp Suite, OWASP Zap, SQLMap
Experiment: Test web applications for security vulnerabilities, such as injection
attacks (e.g., SQL injection), cross -site scripting (XSS), or insecure direct object
references. LO4
8 Social Engineering:

Tools: Maltego, SET, BeEF
Experiment: Conduct a social engineering experiment to a ssess the susceptibility of
individuals to manipulation, such as eliciting sensitive information over the phone, via
email, or in person. LO4
9 Cryptography:

Tools: OpenSSL, Cryptool, HashCalc
Experiment: Implement and analyze cryptographic algorithms, g enerate encryption
keys, perform encryption/decryption, digital signatures, and hash calculations. LO5

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10 Incident Response:

Tools: Volatility, Sleuth Kit, Wireshark
Experiment: Simulate an incident response scenario by investigating a security
breach, analyzing system logs, memory dumps, network traffic, and identifying the
attack vector. LO5
11 Data Exfiltration:

Tools: Steghide, tcpflow, Dnscat2
Experiment: Attempt to extract sensitive data from a target system using techniques
like steganography (h iding data within files), covert channels, or exfiltration through
DNS or ICMP. LO6
12 IoT Security:

Tools: Shodan, Wireshark, Firmware analysis tools
Experiment: Assess the security of Internet of Things (IoT) devices by analyzing their
firmware, identifying vulnerabilities, and demonstrating potential attacks like device
takeover or unauthorized access. LO6

Text Books:
1. "The Web Application Hacker's Handbook: Finding and Exploiting Security
Flaws" by Dafydd Stuttard and Marcus Pinto
2. "Metasploit: The Penetration Tester's Guide" by David Kennedy, Jim O'Gorman,
Devon Kearns, and Mati Aharoni
3. "The Basics of Hacking and Penetration Testing" by Patrick Engebretson

References:
1. "Practical Malware Analysis: The Hands -On Guide to Dissecting Malicious
Software" by Michael Sikorski and Andrew Honig
2. "Hacking Exposed" series by Stuart McClure, Joel Scambray, and George Kurtz
3. "The Incident Response Toolkit: Security Tools & Techniques" by Douglas
Schweitzer

Resource Tools :
1. Wireshark: https://www.wireshark.org/

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2. Kali Linux: https://www.kali.org/
3. Nessus: https://www.tenable.com/products/nessus
4. Metasploit Framework: https://www.metasploit.com/
5. Burp Suite: https://portswigger.net/burp
6. Snort: https://www.snort.org/
7. OWASP ZAP: https://www.zap roxy.org/
8. John the Ripper: https://www.openwall.com/john/
9. OSSEC: https://www.ossec.net/
10. GDB (GNU Debugger): https://www.gnu.org/software/gdb/


Term Work:
1 Term work should consist of 10 experiments
2 Journal must include at least 2 assignments based on Theory and Practical
3 The final certification and acceptance of term work ensures satisfactory performance of
laboratory work and minimum passing marks in term work.
4 Total 25 Marks (Experiments: 15-marks, Attendance Theory & Practical: 05 -marks,
Assignments: 05 -marks)

Oral exam:
Based on the entire syllabus of IOTL802 Cyber Security Lab

Page 140

Course
Code: Course Title Credit
CSP801 Major Project 2 6

Course Objectives:
1 To acquaint with the process of identifying the needs and converting it into the problem.
2 To familiarize the process of solving the problem in a group.
3 To acquaint with the process of applying basic engineering fundamentals to attempt solutions
to the
problems.
4 To inculcate the process of self -learning and research.
Course Outcomes:
1 Identify problems based on societal /research needs.
2 Apply Knowledge and skill to solve societal problems in a group
3 Draw the proper inferences from available results through theoretical/
experimental/simulations
4 Analyse the impact of solutions in societal and environmental context for sustainable
development.
5 Demonstrate capabilities of self -learning in a group, which leads to lifelong learning.
6 Demonstrate project management principles during project work.

Guidelines:
1. Internal guide has to keep track of the progress of the project and also has to maintain
attendance report. This progress report can be used for awarding term work marks.
2. Project Report Format:

Page 141

At the end of semester, each group needs to prepare a project report as per the guidelines
issued by the University of Mumbai. Report should be submitted in hardcopy. Also, each
group should submit softcopy of the report along with project documentation,
implementation code, required utilities, software and user Manuals.

A project report should preferably contain at least following details:
o Abstract
o Introduction
o Literature Survey/ Existing system
o Limitati on Existing system or research gap
o Problem Statement and Objective
o Proposed System
o Analysis/Framework/ Algorithm
o Design details
o Methodology (your approach to solve the problem) Proposed System
o Experimental Set up

o Details of Database or details about input to systems or selected data
o Performance Evaluation Parameters (for Validation)
o Software and Hardware Setup
o Results and Discussion
o Conclusion and Future Work
o References
o Appendix – List of Publications or certificates

Desirable:
Students should be encouraged -
o to participate in various project competitions.
o to write minimum one technical paper & publish in a good journal.
o to participate in national / international conferences.

Page 142

3. Term Work:
Distribution of marks for term work shall be done based on following:
a. Weekly Log Report
b. Completeness of the project and Project Work Contribution
c. Project Report (Black Book) (both side print)
d. Term End Presentation (Internal)
The final certification and acceptance of TW ensures the satisfactory performance on the
above aspects.

4. Oral & Practical:
Oral & Practical examination (Final Project Evaluation) of Project 2 should be conducted by
Intern al and External examiners approved by University of Mumbai at the end of the semester.
Suggested quality evaluation parameters are as following:
a. Relevance to the specialization / industrial trends
b. Modern tools used
c. Innovation
d. Quali ty of work and completeness of the project
e. Validation of results
f. Impact and business value
g. Quality of written and oral presentation
h. Individual as well as teamwork

Page 143

# Institute Level Optional Course (ILO)

Every student is required to take one Institute Elective Course for Semester VII, which
is
not closely allied to their disciplines. Different sets of courses will
run in the both the semesters.




ILO801X Institute Optional Course – 2 ( Common for all br anches will be notified )
ILO8011 Project Management
ILO8012 Finance Management
ILO8013 Entrepreneurship Development
and Management
ILO8014 Human Resource Management
ILO8015 Professional Ethics and CSR
ILO8016 Research Methodology
ILO8017 IPR and Patenting
ILO8018 Digital Business Management
ILO8019 Environmental Management

Page 144

Course
Code Course Name Credits
ILO8011 Project Management 03


Objectives:
1. To familiarize the students with the use of a structured methodology/approach
for each and every unique project undertaken, including utilizing project
management concepts, tools and techniques.
2. To appraise the students with the project management life cycle and make
them knowledgeable about the various phases from project initiation through
closure.

Outcomes: Learner will be able to…
1. Apply selection criteria and select an appropriate project from different options.
2. Write work break down structure for a project and develop a schedule based on it.
3. Identify opportunities and threats to the project and decide an approach to deal
with them strategically.
4. Use Earned value technique and determine & predict status of the project.
5. Capture lessons learned during project phases and document them for future reference


a
Detailed
Contents
Hrs


01 Project Management Foundation:
Definition of a project, Project Vs Operations, Necessity of project management,
Triple constraints, Project life cycles (typical & atypical) Project phases and stage
gate process. Role of project manager. Negotiations and resolving conflicts. Project
management in various organization structures. PM knowledge
areas as per Project Management Institute (PMI).

5


02 Initiating Projects:
How to get a project started, Selecting project strategically, Project selection models
(Numeric /Scoring Models and Non -numeric models), Project portfolio process,
Project sponsor and creating charter; Project proposal. Effective project team,
Stages of team development & growth (forming, stor ming, norming &
performing), team dynamics.

6


03 Project Planning and Scheduling:
Work Breakdown structure (WBS) and linear responsibility chart, Interface
Co-ordination and concurrent engineering, Project cost estimation and budgeting,
Top down and bottoms up budgeting, Networking and Scheduling techniques.
PERT, CPM, GANTT chart. Introduction to Project Management
Information System (PMIS).

8

Page 145

04 Planning Projects:
Crashing project time, Resource loading and leveling, Goldratt's critical chain,
Project Stakeholders and Communication plan.
Risk Management in projects: Risk management planning, Risk identification
and risk register. Qualitative and quantitative risk assessment, Probability and
impact matrix. Risk response strategies for positive an d negative risks

6
05 5.1 Executing Projects:
Planning monitoring and controlling cycle. Information needs and reporting, 8
engaging with all stakeholders of the projects.
Team management, communication and project meetings.
Monitoring and Controlling Projects:
Earned Value Management techniques for measuring value of work completed;
Using milestones for measurement; change requests and scope creep. Project audit.
Project Contracting
Project procurement management, contracting and outsourcing,




06 Project Leadership and Ethics:
Introduction to project leadership, ethics in projects.
Multicultural and virtual projects.
Closing the Project:
Customer acceptance; Reasons of project termination, Various types of project
terminations (Extinction, Additio n, Integration, Starvation), Process of project
termination, completing a final report; doing a lessons learned analysis;
acknowledging successes and failures; Project management templates and other
resources; Managing without authority; Areas of further study.



6

Page 146

REFERENCES:

1. Jack Meredith & Samuel Mantel, Project Management: A managerial approach, Wiley India, 7thEd.
2. A Guide to the Project Management Body of Knowledge (PMBOK® Guide), 5th Ed, Project
Management Institute PA, USA
3. Gido Clements, Project Management, Cengage Learning.
4. Gopalan, Project Management, , Wiley India
5. Dennis Lock, Project Management, Gower Publishing England, 9 th Ed.

Assessment :

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

End Semester Theory Examination:
Some guidelines for setting up the question paper. Minimum 80% syllabus should be covered in question papers of
end semester examination. In question paper weightage of each module will be proportional to number of
respective lecture hours as mention in th e syllabus.
1. Question paper will comprise of total six question
2. All question carry equal marks
3. Questions will be mixed in nature (for example supposed Q.2 has part (a) from module 3 then part (b) will
be from any module other than module 3)
4. Only Four question need to be solved.

Page 147

Course
Code Course Name Credi
ts
ILO8012 Finance Management 03


Objectives:
1. Overview of Indian financial system, instruments and market
2. Basic concepts of value of money, returns and risks, corporate finance, working capital and its management
3. Knowledge about sources of finance, capital structure, dividend policy

Outcomes: Learner will be able to…
1. Understand Indian finance system and corporate finance
2. Take investment, finance as well as dividend decisions



Modu
le
Detailed
Contents
Hrs





01 Overview of Indian Financial System: Characteristics, Components and Functions
of Financial System.
Financial Instruments: Meaning, Characteristics and Classification of Basic
Financial Instruments — Equity Shares, Preference Shares, Bonds -Debentures,
Certificates of Deposit, and Treasury Bills.
Financial Markets: Meaning, Characteristics and Classification of Financial
Markets — Capital Market, Money Market and Foreign Currency Market Financial
Institutions: Meaning , Characteristics and Classification of Financial Institutions —
Commercial Banks, Investment -Merchant Banks and Stock
Exchanges



06



02 Concepts of Returns and Risks: Measurement of Historical Returns and Expected
Returns of a Single Security and a Two-security Portfolio; Measurement of
Historical Risk and Expected Risk of a Single Security and a Two -security Portfolio.
Time Value of Money: Future Value of a Lump Sum, Ordinary Annuity, and
Annuity Due; Present Value of a Lump Sum, Ordinary Annuity, and Annuity
Due; Continuous Compounding and Continuous Discounting.


06



03 Overview of Corporate Finance: Objectives of Corporate Finance; Functions of
Corporate Finance —Investment Decision, Financing Decision, and Dividend
Decision.
Financial Ratio Analysis: Overview of Financial Statements —Balance Sheet, Profit
and Loss Account, and Cash Flow Statement; Purpose of Financial Ratio Analysis;
Liquidity Ratios; Efficiency or Activity Ratios; Profitability Ratios;
Capital Structure Ratios ; Stock Market Ratios; Limitations of Ratio Analysis.


09

Page 148

04 Capital Budgeting: Meaning and Importance of Capital Budgeting; Inputs for
Capital Budgeting Decisions; Investment Appraisal Criterion —Accounting Rate of
Return, Payback Period, Discounted Payback Period, Net Present Value(NPV),
Profitability Index, Internal Rate of Return ( IRR), and Modified
Internal Rate of Return (MIRR)

10

Page 149

Working Capital Management: Concepts of Meaning Working Capital;
Importance of Working Capital Management; Factors Affecting an Entity’s Working
Capital Needs; Estimation of Working Capital Requirements; Management of
Inventories; Management of Receivables; and Management of Cash and Marketable
Securities.



05 Sources of Finance: Long Term Sources —Equity, Debt, and Hybrids; Mezzanine
Finance; Sources of Short Term Finance —Trade Credit, Bank Finance, Commercial
Paper; Project Finance.
Capital Structure: Factors Affecting an Entity’s Capital Structure; Overview of
Capital Structure Theories and Approaches — Net Income Approach, Net Operating
Income Approach; Tradition al Approach, and Modigliani -Miller Approach. Relation
between Capital Structure and Corporate Value; Concept of
Optimal Capital Structure


05

06 Dividend Policy: Meaning and Importance of Dividend Policy; Factors Affecting an
Entity’s Dividend Decision; Overview of Dividend Policy Theories and
Approaches —Gordon’s Approach, Walter’s Approach, and Modigliani -
Miller Approach
03



REFERENCES:

1. Fundamentals of Financial Management, 13th Edition (2015) by Eugene F. Brigham and Joel F. Houston;
Publisher: Cengage Publications, New Delhi.
2. Analysis for Financial Management, 10th Edition (2013) by Robert C. Higgins; Publishers: McGraw
Hill Education, New Delhi.
3. Indian Financial System, 9th Edition (2015) by M. Y. Khan; Publisher: McGraw Hill Education,
New Delhi.
4. Financial Management, 11th Edition (2015) by I. M. Pandey; Publisher: S. Chand (G/L) & Company
Limited, New Delhi.

Assessment :

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

End Semester Theory Examination:
Some guidelines for setting up the question paper. Minimum 80% syllabus should be covered in question papers of
end semester examination. In question paper weightage of each module will be proportional to number of
respective lecture hours as mention in th e syllabus.
1. Question paper will comprise of total six question
2. All question carry equal marks
3. Questions will be mixed in nature (for example supposed Q.2 has part (a) from module 3 then part (b) will
be from any module other than module 3)
4. Only Four questi on need to be solved.

Page 150

Course
Code Course Name Credi
ts
ILO8013 Entrepreneurship Development and Management 03


Objectives:
1. To acquaint with entrepreneurship and management of business
2. Understand Indian environment for entrepreneurship
3. Idea of EDP, MSME

Outcomes: Learner will be able to…
1. Understand the concept of business plan and ownerships
2. Interpret key regulations and legal aspects of entrepreneurship in India
3. Understand government policies for entrepreneurs



Modu
le
Detailed
Contents
Hrs


01 Overview Of Entrepreneurship: Definitions, Roles and Functions/Values of
Entrepreneurship, History of Entrepreneurship Development, Role of
Entrepreneurship in the National Economy, Functions of an Entrepreneur,
Entrepreneurship and Forms of Business Ownership
Role of Money and Capital Markets in Entrepreneurial Development:
Contribution of Government Agencies in Sourcing information for Entrepreneurship

04



02 Business Plans And Importance Of Capital To Entrepreneurship: Preliminary
and Marketing Plans, Management and Personnel, Start -up Costs and Financing as
well as Projected Financial Statements, Legal Section, Insurance, Suppliers and
Risks, Assumptions and Conclusion, Capital and its Importance to the Entrepreneur
Entrepreneurship An d Business Development: Starting a New Business,
Buying an Existing Business, New Product Development, Business Growth and the
Entrepreneur Law and its Relevance to Business Operations


09

03 Women’s Entrepreneurship Development, Social entrepreneurship -role and need,
EDP cell, role of sustainability and sustainable development for SMEs,
case studies, exercises 05


04 Indian Environment for Entrepreneurship: key regulations and legal aspects ,
MSMED Act 2006 and its implications, schemes and policies of the Ministry of
MSME, role and responsibilities of various government organisations, departments,
banks etc., Role of State governments in terms of infrastructure developments and
support etc., Public private partnerships, National Skill
development Mission, Credit Guarantee Fund, PMEGP, discussions, group exercises
etc

08

Page 151

05 Effective Management of Business: Issues and problems faced by micro and small
enterprises and effective management of M and S enterprises (risk
management, credit availability, technology innovation, supply
chain management, linkage with large industries), exercises, e -
Marketing
08

06 Achieving Success In The Small Business: Stages of the small business life cycle,
four types of firm -level growth strategies, Options – harvesting or closing small
business Critical Success factors of small business
05

Page 152

REFERENCES:

1. Poornima Charantimath, Entrepreneurship development - Small Business Enterprise, Pearson
2. Education Robert D Hisrich, Michael P Peters, Dean A Shapherd, Entrepreneurship, latest edition, The
McGrawHill Company
3. Dr TN Chhabra, Entrepreneurship Development, Sun India Publications, New Delhi
4. Dr CN Prasad, Small and Medium Enterprises in Global Perspective, New century Publications, New Delhi
5. Vasant Desai, Entrepreneurial development and management, Himalaya Publishing House
6. Maddhurima Lall, Shikah Sahai, Entrepreneurship, Excel Books
7. Rashmi B ansal, STAY hungry STAY foolish, CIIE, IIM Ahmedabad
8. Law and Practice relating to Micro, Small and Medium enterprises, Taxmann Publication Ltd.
9. Kurakto, Entrepreneurship - Principles and Practices, Thomson Publication
10. Laghu Udyog Samachar
11. www.msme.gov.in
12. www.dcmesme.gov.in
13. www.msmetraining.gov.in


Assessment :

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

End Semester Theory Examination:
Some guidelines for setting up the question paper. Minimum 80% syllabus should be covered in question papers o f
end semester examination. In question paper weightage of each module will be proportional to number of
respective lecture hours as mention in the syllabus.
1. Question paper will comprise of total six question
2. All question carry equal marks
3. Questions will b e mixed in nature (for example supposed Q.2 has part (a) from module 3 then part (b) will
be from any module other than module 3)
4. Only Four question need to be solved.

Page 153

Course
Code Course Name Credi
ts
ILO8014 Human Resource Management 03


Objectives:
1. To introduce the students with basic concepts, techniques and practices of the human resource management.
2. To provide opportunity of learning Human resource management (HRM) processes, related with the
functions, and challenges in the emerging p erspective of today’s organizations.
3. To familiarize the students about the latest developments, trends & different aspects of HRM.
4. To acquaint the student with the importance of inter -personal & inter -group behavioral skills in an
organizational setting re quired for future stable engineers, leaders and managers.

Outcomes: Learner will be able to…
1. Understand the concepts, aspects, techniques and practices of the human resource management.
2. Understand the Human resource management (HRM) processes, functions, changes and challenges in
today’s emerging organizational perspective.
3. Gain knowledge about the latest developments and trends in HRM.
4. Apply the knowledge of behavioral skills learnt and integrate it with in inter personal and intergroup
environment emerging as future stable engineers and managers.



Modu
le
Detailed
Contents
H
rs



01 Introduction to HR
● Human Resource Management - Concept, Scope and Importance,
Interdisciplinary Approach Relationship with other Sciences,
Competencies of HR Manager, HRM functions.
● Human resource development (HRD): changing role of HRM – Human
resource Planning, Technological change, Restructuring and rightsizing,
Empowerment, TQM, Managing ethical issues.


5

Page 154

02 Organizational Behavior (OB)
● Introduction to OB Origin, Nature and Scope of Organizational Behavior,
Relevance to Organizational Effectiveness and Contemporary issues
● Personality: Meaning and Determinants of Personality, Personality
development, Personality Types, Assessment of Personality Traits for
Increasing Self Awareness
● Perception: Attitude and Value, Effect of perception on Individual
Decision -making, Attitude and Behavior.
● Motivation: Theories of Motivation and their Applications for
Behavioral Change (Maslow, Herzberg, McGregor);
● Group Behavior and Group Dynamics: Work groups formal and informal
groups and stages of group development. Team Effectiveness: High
performing teams, Team Roles, cross functional and self -directed team.
● Case study





7

03 Organizational Structure &Design
● Structure, size, technology, Environment of organization; Organizational
Roles & conflicts: Concept of roles; role dynamics; role conflicts and
6

Page 155

stress.
● Leadership: Concepts and skills of leadership, Leadership and
managerial roles, Leadership styles and contemporary issues in
leadership.
● Power and Politics: Sources and uses of power; Politics at workplace,
Tactics and strategies.



04 Human resource Planning
● Recruitment and Selection process, Job -enrichment, Empowerment -
Job-Satisfaction, employee morale.
● Performance Appraisal Systems: Traditional & modern methods,
Performance Counseling, Career Planning.
● Training & Development: Identification of Training Needs, Training
Methods


5



05 Emerging Trends in HR
● Organizational development; Business Process Re -engineering (BPR),
BPR as a tool for organizational development , managing processes &
transformation in HR. Organizational Change, Culture, Environment
● Cross Cultural Leadership and Decision Making : Cross Cu ltural
Communication and diversity at work , Causes of diversity, managing
diversity with special reference to handicapped, women and ageing
people, intra company cultural difference in employee motivation.


6




06 HR & MIS
Need, purpose, objective and role of information system in HR, Applications in HRD
in various industries (e.g. manufacturing R&D, Public Transport, Hospitals, Hotels
and service industries
Strategic HRM
Role of Strategic HRM in the modern business world, Concept of Strategy,
Strategi c Management Process, Approaches to Strategic Decision Making;
Strategic Intent – Corporate Mission, Vision, Objectives and Goals
Labor Laws & Industrial Relations
Evolution of IR, IR issues in organizations, Overview of Labor Laws in India;
Industrial Dis putes Act, Trade Unions Act, Shops and Establishments Act



10


REFERENCES:

1. Stephen Robbins, Organizational Behavior, 16th Ed, 2013
2. V S P Rao, Human Resource Management, 3rd Ed, 2010, Excel publishing
3. Aswathapa, Human resource management: Text & cases, 6th edition, 2011
4. C. B. Mamoria and S V Gankar, Dynamics of Industrial Relations in India, 15th Ed, 2015, Himalaya
Publishing, 15thedition, 2015
5. P. Subba Rao, Essentials of Human Resource management and Industrial relations, 5th Ed, 2013, Himalaya
Publishing
6. Laurie Mullins, Management & Organizational Behavior, Latest Ed, 2016, Pearson Publications

Assessment :

Internal:

Page 156

Assessment consists of two tests out of which; one should be compulsory class test and the other is either a class
test or assignment on live problems or course project.

Page 157

End Semester Theory Examination:
Some guidelines for setting up the question paper. Minimum 80% syllabus should be covered in question papers of
end semester examination. In question paper weight age of each module will be proportional to number of
respective lecture hours as mention in the syllabus.
1. Question paper will comprise of total six question
2. All question carry equal marks
3. Questions will be mixed in nature (for example supposed Q.2 has part (a) from module 3 then part (b) will
be from any module other than module 3)
4. Only Four question need to be solved.

Page 158

Course
Code Course Name Credi
ts
ILO8015 Professional Ethics and Corporat Social Responsibility (CSR) 03

Objectives:
1. To understand professional ethics in business
2. To recognized corporate social responsibility

Outcomes: Learner will be able to…
1. Understand rights and duties of business
2. Distinguish different aspects of corporate social responsibility
3. Demonstrate professional ethics
4. Understand legal aspects of corporate social responsibility


Modu
le
Detailed
Contents
Hrs

01 Professional Ethics and Business: The Nature of Business Ethics; Ethical
Issues in Business; Moral Responsibility and Blame; Utilitarianism: Weighing
Social Costs and Benefits; Rights and Duties of Business 04


02 Professional Ethics in the Marketplace: Perfect Competition; Monopoly
Competition; Oligopolistic Competition; Oligopolies and Public Policy Professional
Ethics and the Environment: Dimensions of Pollution and Resource Depletion;
Ethics of Pollution Control; Ethics of Conserving
Depletable Resources

08


03 Professional Ethics of Consumer Protection: Markets and Consumer Protection;
Contract View of Business Firm’s Duties to Consumers; Due Care Theory;
Advertising Ethics; Consumer Privacy
Professional Ethics of Job Discrimination: Nature of Job Discrimination;
Extent of Discrimination; Reservation of Jobs.

06

04 Introduction to Corporate Social Responsibility: Potential Business Benefits —
Triple bottom line, Human resources, Risk management, Supplier relations;
Criticisms and concerns —Nature of business; Motives; Misdirection.
Trajectory of Corporate Social Responsibility in India
05

05 Corporate Social Responsibility: Articulation of Gandhian Trusteeship Corporate
Social Responsibility and Small and Medium Enterprises (SMEs) in India,
Corporate Social Responsibility and Public -Private Partnership (PPP) in
India
08

Page 159

06 Corporate Social Responsibility in Globalizing India: Corporate Social
Responsibility Voluntary Guidelines, 2009 issued by the Ministry of Corporate
Affairs, Government of India, Legal Aspects of Corporate Social
Responsibility —Companies Act, 2013.
08

Page 160

REFERENCES:

1. Business Ethics: Texts and Cases from the Indian Perspective (2013) by Ananda Das Gupta; Publisher:
Springer.
2. Corporate Social Responsibility: Readings and Cases in a Global Context (2007) by Andrew Crane, Dirk
Matten, Laura Spence; Publisher: Routledge.
3. Business Ethics: Concepts and Cases, 7th Edition (2011) by Manuel G. Velasquez; Publisher: Pearson, New
Delhi.
4. Corporate Social Responsibility in India (2015) by BidyutChakrabarty, Routledge, New Delhi.
Assessment :

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

End Semester Theory Examination:
Some guidelines for setting up the question paper. M inimum 80% syllabus should be covered in question papers of
end semester examination. In question paper weightage of each module will be proportional to number of
respective lecture hours as mention in the syllabus.
1. Question paper will comprise of total si x question
2. All question carry equal marks
3. Questions will be mixed in nature (for example supposed Q.2 has part (a) from module 3 then part (b) will
be from any module other than module 3)
4. Only Four question need to be solved.

Page 161

Course
Code Course Name Credi
ts
ILO8016 Research Methodology 03


Objectives:
1. To understand Research and Research Process
2. To acquaint students with identifying problems for research and develop research strategies
3. To familiarize students with the techniques of data collection, analysis of data and interpretation
Outcomes: Learner will be able to…
1. Prepare a preliminary research design for projects in their subject matter areas
2. Accurately collect, analyze and report data
3. Present complex data or situations clearly
4. Review and analyze research findings



Modu
le
Detailed
Contents
Hrs



01 Introduction and Basic Research Concepts
Research – Definition; Concept of Construct, Postulate, Proposition, Thesis,
Hypothesis, Law, Principle.Research methods vs Methodology
Need of Research in Business and Social Sciences
Objectives of Research
Issues and Problems in Research
Characteristics of Research:Systematic, Valid, Verifiable, Empirical and Critical


09


02 Types of Research
Basic Research
Applied Research
Descriptive Research
Analytical Research
Empirical Research
2.6 Qualitative and Quantitative Approaches

07

03 Research Design and Sample Design
Research Design – Meaning, Types and Significance
Sample Design – Meaning and Significance Essentials of a good sampling Stages in
Sample Design Sampling methods/techniques Sampling Errors
07

Page 162

04 Research Methodology
4.1 Meaning of Research Methodology
4.2. Stages in Scientific Research Process:
a. Identification and Selection of Research Problem
b. Formulation of Research Problem
c. Review of Literature
d. Formulation of Hypothesis
e. Formulation of research Design
f. Sample Design
g. Data Collection
h. Data Analysis
i. Hypothesis testing and Interpretation of Data




08

Page 163

j. Preparation of Research Report

05 Formulating Research Problem
5.1 Considerations: Relevance, Interest, Data Availability, Choice of data, Analysis
of data, Generalization and Interpretation of analysis
04

06 Outcome of Research
Preparation of the report on conclusion reached
Validity Testing & Ethical Issues
Suggestions and Recommendation
04




REFERENCES:

1. Dawson, Catherine, 2002, Practical Research Methods, New Delhi, UBS Publishers Distributors.
2. Kothari, C.R.,1985, Research Methodology -Methods and Techniques, New Delhi, Wiley Eastern Limited.
3. Kumar, Ranjit, 2005, Research Methodology -A Step -by-Step Guide for Beginners, (2nded), Singapore,
Pearson Education



Assessment :

Internal:
Assessment consists of two tests out of which; one should be compulsory class test and the other is either a class
test or at least 6 assignment on complete syllabus or course project.

End Semester Theory Examination:
Some guidelines for setting up the question paper. Minimum 80% syllabus should be covered in question papers of
end semester examinati on. In question paper weightage of each module will be proportional to number of
respective lecture hours as mention in the syllabus.
1. Question paper will comprise of total six question
2. All question carry equal marks
3. Questions will be mixed in nature (for e xample supposed Q.2 has part (a) from module 3 then part (b) will
be from any module other than module 3)
4. Only Four question need to be solved.

Page 164

Course
Code Course Name Credi
ts
ILO8017 IPR and Patenting 03

Objectives:
1. To understand intellectual property rights protection system
2. To promote the knowledge of Intellectual Property Laws of India as well as International treaty procedures
3. To get acquaintance with Patent search and patent filing procedure and applications

Outcomes: Learner will be able to…
1. understand Intellectual Property assets
2. assist individuals and organizations in capacity building
3. work for development, promotion, protection, compliance, and enforcement of Intellectual Property and
Patenting

Module
Detailed
Contents
Hr



01 Introduction to Intellectual Property Rights (IPR) : Meaning of IPR, Different
category of IPR instruments - Patents, Trademarks,Copyrights, Industrial Designs,
Plant variety protection, Geographical indications,Transfer of technology etc.
Importance of IPR in Modern Global Economic Environment: Theories of IPR,
Philosophical aspects of IPR laws, Need for IPR, IPR as an instrument of
development


05



02 Enforcement of Intellectual Property Rights: Introduction, Magnitude of problem,
Factors that create and sustain counterfeiting/piracy, International agreements,
International organizations (e.g. WIPO, WTO) activein IPR enforcement
Indian Scenario of IPR: Introduction, History of IPR in India, Overvie w of IP laws
in India, Indian IPR, Administrative Machinery, Major international treaties signed
by India, Procedure for submitting patent and Enforcement of IPR at
national level etc.


07
03 Emerging Issues in IPR: Challenges for IP in digital economy, e -commerce,
human genome,biodiversity and traditional knowledge etc. 05


04 Basics of Patents: Definition of Patents, Conditions of patentability, Patentable and
non-patentable inventions, Types of patent applications (e.g. Patent of addition etc),
Process Patent and Product Patent, Precautions while patenting, Patent specification
Patent claims, Disclosures and non -disclosures, Patent rights
and infringement, Method of getting a patent

07

05 Patent Rules: Indian patent act, European scenario, US scenario, Australia scenario,
Japan scenario, Chinese scenario, Multilateral treaties where India is a
member (TRIPS agreement, Paris convention etc.)
08

Page 165

06 Procedure for Filing a Patent (National and International): Legislation and
Salient Features, Patent Search, Drafting and Filing Patent Applications, Processing
of patent, Patent Litigation, Patent Publicationetc, Time frame and
cost, Patent Licensing, Patent Infringement
07

Page 166

Patent databases: Important websites, Searching international databases


REFERENCE BOOKS:

1. Rajkumar S. Adukia, 2007, A Handbook on Laws Relating to Intellectual Property Rights in India, The
Institute of Chartered Accountants of India
2. Keayla B K, Patent system and related issues at a glance, Published by National Working Group on Patent
Laws
3. T Sengupta, 2011, Intellectual Property Law in India, Kluwer Law International
4. Tzen Wong and Graham Dutfield, 2010, Intellectual Property and Human Development: Current Trends
and Future Scenario, Cambridge University Press
5. Cornish, William Rodolph & Llewelyn, David. 2010, Intellectual Property: Patents, Copyrights , Trade
Marks and Allied Right, 7th Edition, Sweet & Maxwell
6. Lous Harns, 2012, The enforcement of Intellactual Property Rights: A Case Book, 3rd Edition, WIPO
7. Prabhuddha Ganguli, 2012, Intellectual Property Rights, 1st Edition, TMH
8. R Radha Krishnan & S Balasubramanian, 2012, Intellectual Property Rights, 1st Edition, Excel Books
9. M Ashok Kumar and mohd Iqbal Ali, 2 -11, Intellectual Property Rights, 2nd Edition, Serial Publications
10. Kompal Bansal and Praishit Bansal, 2012, Fundamentals of IPR for Engineers, 1st Edition, BS Publications
11. Entrepreneurship Development and IPR Unit, BITS Pilani, 2007, A Manual on Intellectual Property Rights,
12. Mathew Y Maa, 2009, Fundamentals of Patenting and Licensing for Scientists and Engineers, World
Scientific Publishing Comp any
13. N S Rathore, S M Mathur, Priti Mathur, Anshul Rathi , IPR: Drafting,Interpretation of Patent Specifications
and Claims , New India Publishing Agency
14. Vivien Irish, 2005, Intellectual Property Rights for Engineers,IET
15. Howard B Rockman, 2004, Intellectual Property Law for Engineers and scientists, Wiley -IEEE Press
Assessment :

Internal:
Assessment consists of two tests out of which; one should be compulsory class test and the other is either a class
test or at least 6 assignment on complete syllabus or cour se project.

End Semester Theory Examination:
Some guidelines for setting up the question paper. Minimum 80% syllabus should be covered in question papers of
end semester examination. In question paper weightage of each module will be proportional to numbe r of
respective lecture hours as mention in the syllabus.
1. Question paper will comprise of total six question
2. All question carry equal marks
3. Questions will be mixed in nature (for example supposed Q.2 has part (a) from module 3 then part (b) will
be from any module other than module 3)
4. Only Four question need to be solved.

Page 167

Course Code Course Name Credi
ts
ILO8018 Digital Business Management 03

Objectives:
1. To familiarize with digital business concept
2. To acquaint with E -commerce
3. To give insights into E -business and its strategies

Outcomes: The learner will be able to …..
1. Identify drivers of digital business
2. Illustrate various approaches and techniques for E -business and management
3. Prepare E -business plan

Modu
le Detailed
content Hours





1 Introduction to Digital Business -

Introduction, Background and current status, E -market places, structures,
mechanisms, economics and impacts
Difference between physical economy and digital economy,

Drivers of digital business - Big Data & Analytics, Mobile, Cloud Computing,
Social media, BYOD, and Internet of Things(digitally intelligent
machines/services)
Opportunities and Challenges in Digital Business,




09

Page 168

2 Overview of E -Commerce

E-Commerce - Meaning, Retailing in e-commerce -products and services,
consumer behavior, market research and advertisement
B2B-E-commerce -selling and buying in private e -markets, public B2B
exchanges and support services, e -supply chains, Collaborative Commerce,
Intra business EC and Corp orate portals
Other E -C models and applications, innovative EC System -From E - government
and learning to C2C, mobile commerce and pervasive computing
EC Strategy and Implementation -EC strategy and global EC, Economics and
Justification of EC, Using Affilia te marketing to promote your e - commerce
business, Launching a successful online business and EC project, Legal, Ethics
and Societal impacts of EC






06

Page 169

3 Digital Business Support services : ERP as e –business backbone, knowledge
Tope Apps, Information and referral system
Application Development: Building Digital business Applications and
Infrastructure
06




4 Managing E -Business -Managing Knowledge, Management skills for e -
business, Managing Risks in e –business

Security Threats to e-business -Security Overview, Electronic Commerce
Threats, Encryption, Cryptography, Public Key and Private Key Cryptography,
Digital Signatures, Digital Certificates, Security Protocols over Public
Networks: HTTP, SSL, Firewall as Security Control, Pu blic Key Infrastructure
(PKI) for Security, Prominent Cryptographic Applications



06


5 E-Business Strategy -E-business Strategic formulation - Analysis of
Company’s Internal and external environment, Selection of strategy, E -
business strategy into Action, challenges and E -Transition (Process of
Digital Transformation)

04
6 Materializing e -business: From Idea to Realization -Business plan
preparation

Case Studies and presentations
08


References:

1. A textbook on E -commerce , Er Arunrajan Mishra, Dr W K Sarwade,Neha Publishers & Distributors, 2011
2. E-commerce from vision to fulfilment, Elias M. Awad, PHI -Restricted, 2002
3. Digital Business and E -Commerce Management, 6th Ed, Dave Chaffey, Pearson, August 2014
4. Introduction to E -business -Management and Strategy, Colin Combe, ELSVIER, 2006
5. Digital Business Concepts and Strategy, Eloise Coupey, 2nd Edition, Pearson
6. Trend and Challenges in Digital Business Innovation, VinocenzoMorabito, Springer
7. Digital Business Dis course Erika Darics, April 2015, Palgrave Macmillan
8. E-Governance -Challenges and Opportunities in : Proceedings in 2nd International Conference theory and
practice of Electronic Governance
9. Perspectives the Digital Enterprise –A framework for Transformation, TCS consulting journal Vol.5
10. Measuring Digital Economy -A new perspective -DOI: 10.1787/9789264221796 -enOECD Publishing

Assessment :

Internal:
Assessment consists of two tests out of which; one should be compulsory class test and the other is either a class

Page 170

test or at least 6 assignment on complete syllabus or course project.

Page 171

End Semester Theory Examination:
Some guidelines for sett ing up the question paper. Minimum 80% syllabus should be covered in question papers of
end semester examination. In question paper weightage of each module will be proportional to number of
respective lecture hours as mention in the syllabus.
1. Question pap er will comprise of total six question
2. All question carry equal marks
3. Questions will be mixed in nature (for example supposed Q.2 has part (a) from module 3 then part (b) will
be from any module other than module 3)
4. Only Four question need to be solved.

Page 172

Course
Code Course Name Credi
ts
ILO8019 Environmental Management 03


Objectives:
1. Understand and identify environmental issues relevant to India and global concerns
2. Learn concepts of ecology
3. Familiarise environment related legislations

Outcomes: Learner will be able to…
1. Understand the concept of environmental management
2. Understand ecosystem and interdependence, food chain etc.
3. Understand and interpret environment related legislations



Modu
le
Detailed
Contents
Hrs

01 Introduction and Definition of Environment: Significance of Environment
Management for contemporary managers, Career opportunities.
Environmental issues relevant to India, Sustainable Development, The Energy
scenario.
10

02 Global Environmental concerns : Global Warming, Acid Rain, Ozone Depletion,
Hazardous Wastes, Endangered life -species, Loss of Biodiversity, Industrial/Man -
made disasters, Atomic/Biomedical hazards, etc.
06
03 Concepts of Ecology: Ecosystems and interdependence between living
organisms, habitats, limiting factors, carrying capacity, food chain, etc. 05

04 Scope of Environment Management, Role & functions of Government as a
planning and regulating agency.
Environment Quality Management and Corporate Environmental Responsibility
10
05 Total Quality Environmental Management, ISO -14000, EMS certification. 05

06 General overview of major legislations like Environment Protection Act, Air (P &
CP) Act, Water (P & CP) Act, Wildlife Protection Act, Forest Act, Factories Act,
etc.
03


REFERENCES:

1. Environmental Management: Principles and Practice, C J Barrow, Routledge Publishers London,
1999
2. A Handbook of Environmental Management Edited by Jon C. Lovett and David G. Ockwell, Edward
Elgar Publishing

Page 173

3. Environmental Management, T V Ramachandra and Vijay Kulkarni, TERI Press
4. Indian Standard Environmental Management Systems — Requirements With Guidance For Use,
Bureau Of Indian Standards, February 2005
5. Environmental Management: An Indian Perspective, S N Ch ary and Vinod Vyasulu, Maclillan India, 2000

Page 174

6. Introduction to Environmental Management, Mary K Theodore and Louise Theodore,
CRC Press
7. Environment and Ecology, Majid Hussain, 3rd Ed. Access Publishing.2015



Assessment :

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

End Semester Theory Examination:
Some guidelines for setting up the question paper. Minimum 80% syllabus should be covered in
question papers of end semester examination. In question paper weightage of each module will be
proportional to number of respective lecture hours as mention in the syllabus.
1. Question paper will comprise of total six question
2. All question carry equal marks
3. Questions will be mixed in nature (for example supposed Q.2 has part (a) from module 3 then
part (b) will be from any module other than module 3)
4. Only Four question need to be solved.

Page 175