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Course Detail

Course Name Internet of Things
Course Code 23CSE365
Program B. Tech. in Computer Science and Engineering (CSE)
Credits 3
Campus Amritapuri ,Coimbatore,Bengaluru, Amaravati, Chennai

Syllabus

PROFESSIONAL ELECTIVES

Electives in Cyber Physical Systems

Unit I

Introduction to M2M, WSN, loT, CPS and Web of Things – loT definition – Characteristics – Things in loT – loT Complete Architectural Stack – loT enabling Technologies – loT Challenges – loT Levels – Industrial IoT – Case studies with architectural analysis: Smart City – Smart Water – Smart Agriculture – Smart Energy – Smart Healthcare – Smart Transportation – Connected Vehicles- Smart Retail -Smart waste management – Activity Monitoring.

Sensors and Hardware for loT – Accelerometer, Proximity Sensor, lR sensor, Gas Sensor, Temperature Sensor, Chemical Sensor, Motion Detection Sensor. Hardware Kits – Arduino, Raspberry Pi, Node MCU / ESP 32. A Case study with any one of the boards and data acquisition from sensors.

Unit II

Protocols for loT – Data Protocols: HTTP long polling, short polling, SSE, server push, CoAP, webSockets, MQTT, AQMP – infrastructure protocol (IPV4/V6|RPL) – service discovery and management- Identifier in IoT -Connectivity protocols: BLE, ZigBee, WiFi, NB-IoT, LoRa – Device Management Protocols: TR-369, OMA-DM.

Unit III

Introduction to SDN, SDN for IoT – Cloud and Data analytics- Types of Cloud – loT with cloud challenges – Selection of cloud for loT applications – Fog and Edge computing for loT – Data Handling and IoT Data Analytics – Case study with AWS / AZURE / Adafruit / GCP – security aspects for loT applications.

Objectives and Outcomes

Pre-Requisite(s): 23CSEXXX Embedded Systems and 23CSEXXX Computer Networks

Course Objectives

  • This course covers the fundamentals of IoT and provides skills for IoT based product development.
  • The skills students acquire in this subject include the selection of sensors, protocols, hardware boards, interfacing, and implementation for product building. Real life case studies are introduced in this course.

Course Outcomes

CO1: Understand the key techniques and theory behind Internet of Things.

CO2: Apply effectively the various enabling technologies (both hardware and software ) for IoT.

CO3: Understand the integration of Cloud and IoT , Edge and Fog Computing.

CO4: Apply various techniques for Data Accumulation, Storage and Analytics.

CO5: Design and build IoT system for any one interesting Use case.

CO-PO Mapping

PO/PSO PO1 PO2 PO3 PO4 PO5 PO6 PO7 PO8 PO9 PO10 PO11 PO12 PSO1 PSO2
CO
CO1 3 2 2 2 3 2
CO2 3 3 2 2 3 3 2 2 2 2 2 3 2
CO3 3 3 2 3 3 2 3 2 2 2 2 2 3 2
CO4 3 3 2 3 3 2 3 2 2 2 2 2 3 2
CO5 3 3 2 3 3 2 3 2 2 2 2 2 3 2

Evaluation Pattern

Evaluation Pattern: 70:30

Assessment Internal End Semester
Mid Term Exam 20
Continuous Assessment Theory (*CAT) 10
Continuous Assessment Lab (*CAL) 40
**End Semester 30 (50 Marks; 2 hours exam)

*CAT – Can be Quizzes, Assignments, and Reports

*CAL – Can be Lab Assessments, Project, and Report

**End Semester can be theory examination/ lab-based examination/ project presentation

Text Books / References

Textbook(s)

  1. Misra, A. Mukherjee, and A. Roy, 2020. “Introduction to IoT”. Cambridge University Press, 2020.

Reference(s)

Bahga A, Madisetti V. “Internet of Things: A hands-on approach”; 2015.

Shriram K Vasudevan, Abhishek SN and Sundaram RMD. “Internet of Things”, First Edition,Wiley India;2019.

Raj P, Raman AC. “The Internet of things: Enabling Technologies, Platforms, and Use-cases”. Auerbach Publications; 2017.

  1. Misra, C. Roy, and A. Mukherjee, 2020. “Introduction to Industrial Internet of Things and Industry 4.0”. CRC Press

Adrian McEwen. “Designing the Internet of Things”, Wiley;2015.

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