CS 537 Fall 2022 - Advanced Topics in IoT (Internet of Things)

Location: 1302 SC

Class Time: Tuesdays and Thursdays 12:30:00-1:45pm

Office Hours (Instructor): Tuesdays and Thursdays: 2:00-3:00 pm (in person 3104 Siebel Center or via zoom)

Instructor: Prof. Klara Nahrstedt (klara@illinois.edu)

Teaching Assistant: No TA

Reading List:  reading list will be posted by September 25

Course Details:  Introduction

Course Overview: 

Goal: Advanced topics in Internet of Things (IoT) algorithms, protocols, architectures, systems, and infrastructures, selected from areas of current research such as: IoT sensors representations and compression,  IoT analytics and feature learning, IoT Systems, IoT-edge-cloud computing infrastructures, resource optimization for multi-modal IoT systems, IoT networks, IoT application services and human perception of IoT. Students will read and discuss recent research papers and conduct a semester-long research project. 

Course Elements:  We will take the end-to-end approach and explore an integrated view of multi-modal IoT sensing, networking, system architectures, and evaluations , focused on time-series IoT data streams such as video, audio, and other time-sensitive IoT streams. The topics will include (1)  IoT data representation for IOT devices including 2D and 360 video cameras, 1D audio, and other 1D IoT devices (e.g., temperature, humidity),  (2) advanced compression techniques for IoT streams, including H.264/H.265, MPEG4/HVEC, MP3, (3) Machine Learning Techniques for IoT Data Analytics, (4) IoT network and transport protocols such as DASH, Zigbee, (5) edge-cloud computing systems for IoT Data Analytics, and (6)  subjective and objective Quality of Experience (QoE) evaluation methods for next generation multi-modal and immersive IoT applications.

Expected Workload: The students will present research paper(s), work individually on take-home midterm exam, and participate in discussion of presented papers. Furthermore, students will work on a semester-long project and present their results in a research paper format and via final presentation. Students can define their own project. Sample projects: design and development of multi-view  IoT  distribution algorithms, design and validation of QoE evaluation methodology for diverse wireless multi-modal IoT applications; development of DASH Adaptive control algorithms, QoS analytics algorithms and tool(s) for IoT systems, caching  in edge-cloud computing of IoT data, and others. 

Lecture Slides and Course discussion  are going to be available on  campuswire as we progress during the semester. 

Statement on CS CARES and CS Values and Code of Conduct

All members of the Illinois Computer Science department - faculty, staff, and students - are expected to adhere to the CS Values and Code of Conduct. The CS CARES Committee is available to serve as a resource to help people who are concerned about or experience a potential violation of the Code. If you experience such issues, please contact the CS CARES Committee. The instructors of this course are also available for issues related to this class.