IoT and Cognitive Computing credit:

4 Hours

Offers in-depth coverage on existing and emerging IoT and cognitive computing topics. Detailed topics include definition and characteristics of IoT; IoT enabling technologies; smart domains and applications; IoT systems; IoT design methodology; machine learning and deep learning; embedded GPU and FPGA for IoT; IoT servers and cloud; data analytics for IoT; cognitive computing; cognitive systems design; cognitive application workloads; IoT security; hands-on learning experience to build IoT systems; and various case studies such as smart city, smart home, and IoT for healthcare. Three lab-based machine problems working with actual IoT computing devices together with homework assignments will be given to reinforce students' understanding and learning of the techniques and topics. 4 undergraduate hours. 4 graduate hours. Prerequisite: ECE 220 or CS 225 .