This course covers existing and emerging IoT application domains, high-level programming for IoT devices, machine learning algorithms, and various computing systems that facilitate the rapid realization and growth of IoT. Topics include definition and characteristics of IoT; IoT enabling technologies; smart domains and applications; IoT systems; IoT design methodology; embedded GPU and FPGA for IoT; IoT servers and cloud; data analytics for IoT, cognitive computing, cognitive systems design, cognitive application workload, and various case studies such as smart city, smart agriculture, machine translation, and video captioning. Machine problems working with Raspberry Pi, hardware (FPGA and GPU), Amazon cloud, and IBM Node-RED and TJBot, together with homework assignments will be given to reinforce the understanding of the techniques and topics and train the students with practical skills.
Lecture Time: Tuesdays and Thursdays 11 am - 12:20 pm
Lecture Location: ECEB 1013
Location: ECEB 4022
- Session 1: Mondays 10 am - 11:55 am. TA: Qin Li.
- Session 2: Mondays 1 pm - 2:55 pm. TA: Vibhakar V Vemulapati.
- Session 3: Wednesdays 10 am - 11:55 am. TA: Anand Ramachandran, Xiaofan Zhang.
- Session 4: Wednesdays 1 pm - 2:55 pm. TA: Ashutosh Dhar, Yuhong Li.
|Jan. 15||Introduction to IoT and Cognitive Computing||[slides]|
|Jan. 17||Introduction to Raspberry Pi and Python||[slides]|
We use Piazza for Q & A.