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Postgraduate Elective

CS6650: Smart Sensing for Internet of Things

A systems-oriented introduction to sensing in IoT, covering the algorithms, signal-processing primitives, and implementation perspectives behind real applications such as indoor localization, gesture recognition, health sensing, and embedded intelligence.

CS6650 course image
Latest Campus Offering Holi'23 (Jan - Apr, 2023)
Instructor Ayon Chakraborty
Web M.Tech Offerings Sep-Dec 2023, Sep-Dec 2024
Format Hands-on projects and programming

Teaching Feedback

IoT systems today perform a wide variety of sensing tasks. This course unpacks what goes under the hood by introducing systems concepts, algorithms, and signal-processing tools that power modern IoT applications ranging from indoor location tracking and gesture recognition to healthcare sensing.

The course follows a first-principles approach with a gradual ramp-up toward real systems and applications. The emphasis is on enabling students to appreciate and build real IoT applications, while keeping theoretical depth focused on what is necessary for working knowledge and implementation.

Prerequisites. Relevant background in basic electronics, digital systems, and computer organization helps. Students should be comfortable with programming in C, C++, or Python and should be willing to work patiently with hardware, interfacing, and debugging. Mobile programming experience is useful depending on the project.

Detailed Syllabus

CS6650 syllabus

Assignments / Grading

The course emphasizes learning by doing. Assessment includes two quizzes (20%), two programming assignments or homeworks (30%), one major course project with presentation (40%), and interaction or class participation (10%).

References

Readings and project material are shared during the course according to the topic cluster being covered, with a stronger emphasis on systems papers, implementation-oriented notes, and research-driven application examples than on a single textbook.