CS 537

Fall 2026 All Classes

All Classes

Advanced Topics in Internet of Things (IoT)

Credit: 4 hours.

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, streaming and caching of IoT data, IoT analytics and feature learning, IoT-edge-cloud computing infrastructures, resource optimization for multi-modal IoT systems, applications and human perception of IoT. Students will read and discuss recent research papers and conduct a semester-long research project.

May be repeated, if topics vary. Credit towards a degree from multiple offerings of this course is not given if those offerings have significant overlap, as determined by the CS department. Prerequisite: One of CS 425 or ECE 428; one of CS 438 or ECE 438. Additional prerequisites may be specified each term. See section information.

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CS 537 class schedule data for fall 2026
	Status		CRN	Type	Section	Time	Day	Location	Instructor	Section Details
			75892	Lecture-Discussion	K	9:30AM -10:45AM	TR	305 Materials Science & Eng Bld	Vasisht, D	Availability: Open (Restricted) Part of Term: 1 Date Range: 08/24/26-12/09/26 Credit: 4 hours Section Title: IoT Wireless Systems Section Info: Internet of Things (I0T) encompasses many different sensing, computing, and networking capabilities to build complex distributed multi-modal IoT systems. In this section of the Advanced IoT Systems, we will explore the IoT systems in distributed immersive environments as we see more and more advanced IoT devices such as 2D, 360, 3D cameras, spatial audio and microphone arrays, accelerometers, and other sensors becoming part of head-mounted displays, tele-conference environments, remote surveillance services and other immersive applications. We will take a system-centric approach where we will discuss through lectures and student presentations of international top conference publications the end-to-end system path of 1D and 2D IOT data, including the IoT data representation, their compression algorithms, network streaming protocols over different wired and wireless networks, machine-learning-based IoT data analytics to extract important features for advanced resource management optimizations, and we will end with discussions of important concepts and metrics to be considered when viewing content by people in immersive environments such as the multi-modal synchronization and Quality of Experience. Prerequisite: cs425, cs438, cs437 or agreement of instructor (strong system/network background) For up-to-date information about CS course restrictions, please see the following link: http://go.cs.illinois.edu/csregister Restriction(s): Restricted to Computer Science or Bioinformatics major(s). Restricted to Graduate - Urbana-Champaign. Not intended for MCS: Computer Sci OFF - UIUC, MCS:Computer Sci Online -UIUC, or NDEG:Computer Science Onl-UIUC. Not intended for First Time Freshman students.