Course

Unit 1

Introduction to loT – loT definition – Characteristics – Things in loT IoT Components – loT Complete Architectural Stack – loT enabling Technologies – loT Challenges – loT Levels – A Case Study to realise the stack

Unit 2

Sensors and Hardware for loT – Arduino Software (IDE) – Installation of Arduino Software (IDE) LEDS Sensors – Accelerometer, Proximity Sensor, Light, lR sensor, Soil Moisture, Gas Sensor, Temperature and Humidity Sensor, Water, Chemical Sensor, Motion Detection Sensor. Hardware Kits – Arduino, Raspberry Pi, Node MCU. A Case study with any one of the boards and data acquisition from sensors (Lab Component)

Unit 3

Protocols for loT – infrastructure protocol IPV4/V6|RPL), Identification (URLs), Transport (Wi-Fi, Li-Fi, BLE), Discovery, Data Protocols, Device Management Protocols. – A Case Study with MQTT/CoAP usage. (Lab Component)

Unit 4

Cloud and Data analytics – loT with cloud challenges – Selection of cloud for IoT applications – Fog computing for loT – Edge computing for loT – Cloud security aspects for loT applications – RFM for Data Analytics – Case study with AWS / AZURE / Adafruit / IBM Bluemix (Lab Component).

Unit 5

Case studies with architectural analysis: loT applications – Smart City – Smart Water – Smart Agriculture – Smart Energy – Smart Healthcare – Smart Transportation – Smart Retail -Smart waste management. (Lab Component – As a project)

Text Books / References

Text and Reference Books

1. “lnternet of Things: A Hands-on Approach”, by ArshdeepBahga and Vijay Madisetti (UniversitiesPress) lnfosys Training E Materials.
2. “The Internet of Things: Enabling Technologies, Platforms, and Use Cases’, by pethuruRajand Anupama C. Raman (CRC press)
3. Adrian McEwen, Designing the internet of Things, Wiley (B November 2Ot3), ISBN13:978-.11-L1,8430620,
4. NPTEL Reference:https://onlinecourses.nptel.ac.in/noc17_cs22/preview

The Internet of Things (IoT) course provides a foundational yet comprehensive overview of interconnected devices, emphasizing the seamless integration of sensors, microcontrollers, and communication networks. It elucidates core architectural paradigms, fundamental protocols, and introduces hands-on development using platforms such as Arduino and Raspberry Pi. The course further acquaints students with cloud integration, data visualization, and essential security considerations, enabling them to conceptualize and implement rudimentary yet impactful IoT-driven solutions for real-world applications.

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

• CO1: Explain the fundamental concepts, characteristics, architecture, enabling technologies, and challenges of the Internet of Things (IoT).
• CO2: Identify and interface various sensors and hardware platforms such as Arduino, Raspberry Pi, and NodeMCU for data acquisition in IoT systems.
• CO3: Analyze and apply IoT communication protocols, including IPv4/IPv6, RPL, MQTT, and CoAP, for efficient device connectivity and data exchange.
• CO4: Evaluate cloud and edge computing paradigms for IoT applications and implement basic data analytics using IoT cloud platforms.
• CO5: Design and develop IoT-based solutions for real-world applications such as smart cities, healthcare, agriculture, and transportation through case studies and projects.

CO-PO Mapping: