CS 537

Spring 2026 All Classes

All Classes

Advanced Topics in Internet of Things (IoT)

SHOW FINAL EXAM SCHEDULE

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.

My Favorites

My Schedule

Section Status updates every 10 minutes.

CS 537 class schedule data for spring 2026
CRN	Type	Section	Time	Day	Location	Instructor	Section Details
78199	Lecture-Discussion	B	2:00PM -3:15PM	TR	0216 Siebel Center for Comp Sci	Abdelzaher, T	Part of Term: 1 Date Range: 01/20/26-05/06/26 Section Title: AI of Things (AIoT) Section Info: In contrast to more general introductions to the Internet of Things (IoT), this advanced topic course focuses specifically on research challenges in edge AI motivated by the introduction of machine intelligence into IoT applications. Recent advances in AI culminate a shift in science and engineering away from strong reliance on algorithmic and symbolic knowledge towards new data-driven approaches. The course discusses how the emerging intelligent data-centric world impacts research on IoT and embedded computing. It organizes these effects around the types of bottlenecks that arise. At training time, in intelligent IoT applications, the bottlenecks are generally data related. IoT applications often exploit scarce data modalities (such as heterogeneous sensor data), unlike those commonly addressed in mainstream AI, necessitating solutions for efficient learning from scarce sensor data. At inference time, the bottlenecks are resource-related, calling for smaller models (such as small language models and application-specific foundation models) and improved resource economy (thanks to a variety of optimization techniques including quantization, caching, early exit networks, and mixture-of-expert scheduling policies). Furthermore, the convergence of AI around specific model architectures introduces additional model-related challenges in IoT contexts. The class discusses the research directions that arise in the data-centric world of intelligent IoT, covering data-, resource-, and model-related challenges, and overviews recent solutions emerging in this important domain. For up-to-date information about CS course restrictions, please see the following link: http://go.cs.illinois.edu/csregister Restriction(s): Restricted to Graduate - Urbana-Champaign. Not intended for MCS: Computer Sci OFF - UIUC or MCS:Computer Sci Online -UIUC. Not intended for First Time Freshman students.
74384	Lecture-Discussion Online	I I	9:30AM -10:45AM 9:30AM -10:45AM	F W	0220 Siebel Center for Comp Sci ARR Illini Center	Nahrstedt, K Nahrstedt, K	Part of Term: 1 Date Range: 01/20/26-05/06/26 Section Title: Multimedia Systems Section Info: 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 Graduate - Urbana-Champaign. Not intended for MCS: Computer Sci OFF - UIUC or MCS:Computer Sci Online -UIUC. Not intended for First Time Freshman students.
78198	Lecture-Discussion Online	MCS MCS	9:30AM -10:45AM 9:30AM -10:45AM	W F	ARR Illini Center n.a.	Nahrstedt, K Nahrstedt, K	Part of Term: 1 Date Range: 01/20/26-05/06/26 Section Title: Multimedia Systems Section Info: 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 Graduate - Urbana-Champaign. Restricted to MCS: Computer Sci OFF - UIUC.