Teaching a Freshman Seminar on the IoT

I am teaching a Freshman Seminar on the IoT for the Winter 2022 Quarter. Please check it out and tell your friends. You can find it on the UC Davis First-Year Seminars website.

All course material will be open-source and available on GitHub at iot-winter-2022.

The Internet of Things: What is it and how can you contribute?

Description

The Internet of Things (IoT) is a paradigm shift where interconnected “things” begin to populate the internet rather than “people”. This IoT has become massive with billions of “things” collecting sensor data and sending it to centralized data dashboards which aggregate this information and make it browsable on the web. The IoT is being used by many companies, governments, and local communities. The scope of IoT data is equally broad ranging from smart-homes, personal biometrics, weather and air quality, agricultural and industrial monitoring, and community data such as bike- and ride- share and traffic patterns.

In this seminar, we will explore the IoT through a series of discussions, lectures, invited speakers, and hands-on experiments. We will learn how IoT networks work including remote sensors, network connections, and cloud processing of aggregated data. We will build simple sensors (light, temperature, motion) using WIFI enabled Arduino microprocessors that will transmit data to cloud based dashboards. We will learn the basics of a cloud dashboard that aggregates sensor data and displays it on a website. Students will work individually or together on a final project implementing an IoT of their own design or an in depth IoT review. No experience in programming or circuit design is required.

Seminar Goals

• Students will develop life-long learning and deep cognitive skills to address complex problems by breaking them down into simple interconnected components.
• Through discussions, readings, and presentations, students will learn how to approach a multi-dimensional topic and distill the most important dimensions into a concise and simple to explain framework.
• Students will develop critical thinking and ethics skills in the context of privacy issues when personalized data is collected in an IoT setting such as biometric data, cell phone usage, home-automation, and surveillance cameras.
• Students will learn how to wire basic circuits to connect sensors to Arduino microcontrollers. For example, sensors such as temperature/humidity, light, motion, and sound.
• Students will learn simple programming in C to read sensor data and how to use IoT network protocols to transmit data from remote sensors to be aggregated on a cloud platform.
• For a final project, individuals or groups of students will either (i) design and implement an IoT system or (ii) perform an in-depth review of an IoT topic.
• Students will gain both oral and written communication skills through a final presentation and paper describing their IoT system or review. All final papers will be done individually by each student.

Assignments

• There will be out-of-class reading assignments (5-7 pages per week) that address technical and social topics of the IoT.
• During class, working individually or in groups of 2, students will wire a sensor to an Arduino and write C code to acquire data and transmit to a cloud dashboard.
• Working in groups of 1-4, students will design and construct their own personal IoT system. The design of the IoT system will be done outside of class. IoT systems will be constructed during class.
• As an alternative to designing an IoT system, students can independently perform an IoT review where they research an IoT topic in greater depth. Research will be done outside of class and will be discussed during class.
• Students will independently write a final paper describing their IoT system or review following the format of a method or review journal article. For IoT systems, 5 double-spaced pages and for IoT reviews 7 double-spaced pages is required.
• In the final class, each group or individual will present their IoT system or review to the class (10 minute presentation).
• Total work for the class is expected to be 6 hours per week including the 2 hour class participation.

Instructor Bio

Robert Cudmore is an Assistant Professor in the Department of Physiology and Membrane Biology, School of Medicine at UC Davis. His research revolves around building image analysis software pipelines for complex 3D bio-imaging data and employing cutting-edge microscopy to understand both neuronal and vascular function. Robert began his career in Computer Science and Engineering before going on to obtain a PhD from Brandeis University in Neuroscience and then postdoctoral research in both France and at Johns Hopkins University in Baltimore. He really enjoys building things in the lab to collect data and to automate otherwise complex tasks.