IoT is a fast growing technology sector that is estimated to be valued at 100’s of billions in US dollars for 2023. The number of IoT connected devices is growing at an annual rate of 20%/year with billions of devices connected. Accordingly, there is much need for foundational IoT engineering courses in our educational institutions to prepare engineers for this technology sector. The challenge for course developers is that IoT technical foundations are exceedingly broad - ranging from smart sensors to low power computing to cloud infrastructure. Most universities focus on one or two aspects of IoT technical foundations, specifically those associated with the computing aspects of IoT. We have developed a novel approach for an IoT course by segmenting the course into three fundamental technology areas. These areas are respectively (1) foundations of sensing, (2) IoT communication and networking, and (3) IoT computing models and architectures. Each module is taught by a different professor with technical expertise in that module. This paper will focus on course objectives, design, and outcomes. We use the Module 2 IoT communication and networking as an example of the type of content. In this module, we cover fundamental knowledge of networking including layered-architecture, protocols, wireless communication and propagation. Then we introduce two common communication protocols, i.e., Hypertext Transfer Protocol (HTTP) and Message Queuing Telemetry Transport (MQTT), which are widely used for IoT systems. Further, Node.js programming is taught and students learned how to use node.js for HTTP and MQTT implementation. Hands-on experiments using Arduino WiFi1010 board and grove sensors are designed to help deepen students’ understanding for developing a small-scale IoT system as well. The term project of building an IoT-enabled smart Heating, Ventilation, and Air Conditioning (HVAC) will be introduced. Instructor observations and anecdotal student feedback on the course design and delivery are presented as well. Lessons learned will be discussed and modifications are proposed for future improvement.
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