According to the latest IPCC report, human-induced climate change already impacts many global weather and climate extremes. IEEE India office, in association with RadioStudio, is planning to offer a course on applying AIoT (Artificial Intelligence (AI) combined with the Internet of Things (IoT)) technologies to address climate change problems through its Blended Learning Program (BLP). IEEE BLP combines the latest eLearning techniques with extensive hands-on practice. It takes the best of virtual learning and face-to-face training to provide a flexible yet comprehensive learning experience.
The target audience for this AIoT course is college students (sophomores and above) and professionals with a background in STEM (Science, Technology, Engineering, and Mathematics). The course will consist of the following modules:
- The first module will present an overview of climate change and the five main causes of greenhouse gas emissions;
- Making things (cement, steel, plastic)
- Generating and consuming
- Growing things (plants and animals)
- Getting around (planes, trucks, cargo ships)
- Heating, cooling, and refrigeration.
- The second module will discuss the problem areas that can be addressed through AIoT technologies without a laboratory or expensive infrastructure. For instance, distributed energy resources and hydroponics would be addressed, but not the greening of cement and steel production.
- The third module will discuss a hardware module we built to interface with sensors. The hardware module will enable access to the data from different kinds of sensors with relative ease. The hardware and the data transport architecture is designed in such a way that a non-technical student should be able to get a feel for the data with very little effort while the more technically inclined may use it for exploring and deploying other sensors based upon particular needs, not necessarily provided as part of the course.
- The fourth module will present the software modules required to interface with the sensors and actuators and analyze the collected time series data. For this purpose, the Python programming language and Jupyter notebooks will be used.
- The fifth and final module will be a capstone project the students must build to complete the course.
This course is inspired by Open-Source software and Amateur Radio movements, where grassroots efforts of a large number of volunteers resulted in large-scale benefits for humanity. We are confident that this course will increase students’ awareness of climate change and, more importantly, inspire and equip them to build effective solutions for mitigating it. Visit blp.ieee.org for more information.