About the project
Concerns about the environmental impact of electronics are increasing, and the IoT will deploy billions of devices. Choices made about power supplies, edge AI algorithms, and processors influence their use of materials, carbon footprint, and longevity. In this PhD, you will explore design-time approaches to enhance sustainability of devices.
Wireless edge computing devices operate efficiently by using lightweight on-device AI algorithms, consuming orders of magnitude less energy for communication. Whilst they may be powered by batteries, energy harvesting offers a sustainable alternative, promising to power devices indefinitely from ambient energy such as indoor light.
But just how sustainable is an energy harvester, and how does its environmental impact compare to a battery? How does the edge AI algorithm you choose affect the design of the rest of the system, and how can we design systems to have a longer useful life?
This PhD project will be at the forefront of sustainable electronics design. It will explore design-time approaches to understand and enhance the sustainability of devices. It will initially involve reviewing the known impact and performance of system components, before exploring design decisions and evaluating them through prototypes. This work will allow future engineers to design-in sustainability for edge computing IoT devices.
The project will adapt to the skills and interests of the successful candidate, but is likely to involve electronic hardware (embedded systems/computer engineering), embedded software (in C), and experimental analysis (prototyping using development boards).
The successful candidate will be based in the Smart Electronic Materials & Systems group in the School of Electronics and Computer Science, and affiliated with the Cyber Physical Systems group and Centre for IoT and Pervasive Systems. They will be supported to attend international conferences, and develop a wide range of technical and transferable skills.
