Development of an embedded system course to teach the Internet-of-Things

In this paper, we present the development of new course modules in the field of embedded systems, dedicated to teaching students about the internet-of-things. We discuss important issues in creating hands-on labs for students in such a course, along with the experience of teaching this course at the graduate level. We expect other instructors interested in this area to benefit from our experience. We also offer suggestions for adapting this course at the undergraduate level. Our main finding is that students are very excited to learn about cutting-edge technologies, including fast growing programming languages and platforms. Specific hands-on laboratory exercises were developed on the Raspberry Pi platform in Python to teach students about the end-to-end processing involved in acquiring, analyzing, storing and transmitting temperature sensor data. These lab exercises provided students with a detailed understanding of the end-to-end processing involved in internet-of-things applications, including sensory data acquisition, storage, transmission, retrieval and analytics. The lab exercises made the course material accessible and engaging. This addresses one of the barriers to students entering and staying in STEM fields, which is the perceived dullness of the material taught.