M.Sc. (Information Technology) Advanced IoT Practical Syllabus - Mumbai University

• 1. Load Raspbian and Windows IoT Core on Raspberry Pi and execute applications on it [OC1] using Python and node.js. 2. Create a home automation system and control the devices remotely. Control 4 devices [OC2] with the system. 3. Interface fingerprint module with raspberry Pi to capture and store fingerprints. [OC3] Interface 16X2 LCD with the same Pi and display whether the fingerprint is valid or invalid. 4. Interface RFID module with Raspberry Pi. Write and read RFID cards. Map the with [OC4] student Roll no. Read the card and display the information of the student. 5. Interface GPS module with Raspberry Pi. Display the latitude and longitude on the [OC5] 16X2 LCD display.

• 6. Interface Pi Camera with Raspberry Pi. Capture and store faces along with their names. Scan the face and display the Name of the person. 7. a. Create a private Ethereum blockchain with Raspberry Pi.
• b Integrate Node Red with MQTT on Raspberry Pi. 8. Interface fingerprint module with Raspberry Pi. Control different devices with fingerprint. If the finger print is registered and valid, the device should function, else Access denied should be displayed on LCD 16X2 display. 9. Create a full-featured Kubernetes application on a Pi cluster
• i Setup Raspberry Pi Cluster ii. Install Kubernetes on Raspberry Pi Cluster iii. Install Kubernetes Ingress on Raspberry Pi Cluster iv. Perform Kubernetes application monitoring on Raspberry Pi cluster
• v Install MairaDB on Raspberry Pi vi. Develop Application using the above installations Interface 10. stepper motor with Raspberry Pi. Use the motor to rotate an item clockwise and anticlockwise in steps. 11. Build AI Powered Auto Billing System for Fast Checkout in Retail Stores with Raspberry Pi. 12. Send telemetry from a device to an IoT hub and read it with a service application. 13. Use the Azure CLI and Azure portal to configure IoT Hub message routing. Use 14. Microsoft Speech API to
• a Transcribe audible speech into readable, searchable text.
• b Convert text to lifelike speech for more natural interfaces.
• c Integrate real-time speech translation into your apps.
• a Identify and verify the person speaking by using voice characteristics. 15. Use Microsoft Language API to
• a Identify commonly used and domain-specific terms.
• b Automatically detect sentiments and opinions in text.
• c Distill information into easy-to-navigate questions and answers.
• d Enable your apps to interact with users through natural language.
• e Translate more than 100 languages and dialects. 16. Use Microsoft Vision API to
• a Identify and analyze content in images and video.
• b Customize image recognition to fit your business needs. Use Microsoft Language API to
• c Identify potential problems early. (Decision services / Anomaly Detector)
• d Detect potentially offensive or unwanted content. (Decision services / Content Moderator)
• e Create rich, personalized experiences for every user. (Decision services / Personalizer) 17. Develop a project for Condition monitoring for Industrial IoT (Case Study and [OC19] Implementation) 18. Develop a project for Predictive maintenance for Industrial IoT (Case Study and [OC20] Implementation) 19. Develop a project for Real-time asset tracking and management (Case Study and [OC21] Implementation) 20. Create a digital model of your physical space or assets (Case Study and [OC22] Implementation)

References

• 1 https://www.raspberrypi.org/
• 2 https://betterprogramming.pub/develop-and-deploy-kubernetes-applications-on-a-raspberry- pi-cluster-fbd4d97a904c
• 3 https://learn.microsoft.com/en-us/azure/iot/tutorial-iot-industrial-solution-architecture
• 4 https://azure.microsoft.com/en-in/solutions/iot
• 5 https://circuitdigest.com/microcontroller-projects/raspberry-pi-based-automatic-library- management-system