Theme Leaders: Dr Thomas Szydlo & Dr Blesson Varghese

RT3 aims to find ways to make complex Edge AI models work smoothly on different types of edge computing systems. These systems can be very different from each other, which makes it hard for Edge AI models to work well on all of them.

One idea to make this easier is TinyML, a kind of AI model designed for edge computing. But there are still problems with TinyML. For example, it’s hard to know how well TinyML will work on different types of edge devices. Also, TinyML doesn’t always handle changes in the system well, like when there are problems with the internet connection or the devices are under attack.

To solve these problems, we’ll work on two main things. First, we will figure out how to test Edge AI models on different edge devices to see how well they work. This will help developers know which models are best for which devices. Second, we will create a new way for Edge AI models to adjust themselves based on what’s happening in the system. This will help them keep working well even when there are problems.

Our goal is to make it easier for developers to build and use Edge AI models on edge computing systems. We will create tools and techniques to help them do this, so Edge AI can be used in more places and work better for everyone.