Indian Institute of Technology Bombay
Introduction to Internet of Things
Indian Institute of Technology Bombay

Introduction to Internet of Things

Taught in English


Gain insight into a topic and learn the fundamentals

Prof. Rajbabu Velmurugan
Prof. Laxmeesha Somappa
Prof. Gaurav S. Kasbekar

Instructors: Prof. Rajbabu Velmurugan

Intermediate level

Recommended experience

14 hours to complete
3 weeks at 4 hours a week
Flexible schedule
Learn at your own pace

What you'll learn

  • Recall the core principles and characteristics of the Internet of Things (IoT) discussed in the course lectures and materials.

  • Explain the various applications and domain areas of IoT, including home automation, by synthesizing information from the course modules.

  • Implement knowledge of IoT components, networking protocols, and data analysis methodologies to solve IoT-related problems.

  • Evaluate the challenges and design goals associated with IoT architecture and implementation, and propose strategies to address them effectively.

Details to know

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May 2024


17 assignments

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There are 4 modules in this course

Led by Prof. Rajbabu Velmurugan, in the "Internet of Things (IoT): An Introduction" module, learners will embark on a comprehensive journey into the fundamentals of IoT. Lesson 1 delves into the very essence of IoT, exploring its applications and distinct characteristics. Progressing to Lesson 2, participants will uncover the diverse models and components of IoT, enriched with real-world examples like home automation. Concluding with Lesson 3, the module offers an in-depth analysis of IoT architecture and its design goals, ensuring a holistic understanding of the subject. With a well-curated blend of videos and insights, this module serves as an essential primer for anyone keen on grasping the basics of the IoT realm.

What's included

14 videos4 readings4 assignments1 discussion prompt

Led by Prof. Laxmeesha Somappa, the "Sensors & Interfaces" module offers a comprehensive exploration into the intricate world of sensors, their characteristics, and their interfacing techniques. Lesson 1 serves as a foundational introduction to the realm of sensors, delving into their classifications and providing in-depth case studies on select sensor types like accelerometers, displacement/proximity sensors, and temperature sensors. Building on this foundation, Lesson 2 dives into the vital characteristics that define and differentiate sensors, covering aspects such as sensitivity, accuracy, and response time. The subsequent lessons shift focus to the crucial process of sensor readout, with Lesson 3 elucidating the concepts and design choices surrounding Analog to Digital Conversion (ADC) and quantization, and Lesson 4 highlighting the non-idealities one might encounter, including opamp specific issues.

What's included

17 videos4 readings5 assignments

Led by Prof. Gaurav S. Kasbekar, the "Networking of IoT Nodes" module delves deep into the mechanisms and challenges of connecting diverse IoT nodes, ensuring seamless communication and data exchange. Lesson 1 lays the foundation by introducing the concept of IoT nodes, their diverse applications in sectors like agriculture, healthcare, smart homes, and infrastructure, and outlines the challenges in their networking. Lesson 2 ventures into low power, low data rate networks, illuminating participants on the IEEE 802.15.4 standard, as well as cutting-edge technologies like LoRa and SigFox. In Lesson 3, the spotlight is on the integration of constrained devices, offering insights into 6LoWPAN, header compression, fragmentation, and routing protocols. Rounding off the module, Lesson 4 dives into messaging protocols essential for IoT, with a comprehensive overview of CoAP and MQTT, their formats, and communication intricacies.

What's included

22 videos4 readings5 assignments

Led by Prof. Rajbabu Velmurugan, in the "Data Analysis for IoT" module, learners delve into the critical aspects of analyzing vast amounts of data generated by IoT devices. Beginning with an exploration of the significance of data analysis specifically for IoT in Lesson 1, participants will be introduced to the components, feasibility, and various types of learning methods tailored for IoT datasets, with hands-on Python-based implementations. Lesson 2 offers a deeper dive into specific data analysis techniques, encompassing linear regression, time-series models, and clustering methodologies. With a blend of theoretical insights and practical demonstrations, this module ensures that learners are well-equipped to harness the power of data in the IoT domain. Concluding with a special message from the CEO of TIH-IoT. This module is a blend of theoretical knowledge, practical insights, and real-world applications, ensuring learners are well-equipped to navigate the networking landscape of IoT.

What's included

13 videos4 readings3 assignments


Prof. Rajbabu Velmurugan
Indian Institute of Technology Bombay
1 Course157 learners

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