Interactive Edge
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Edge computing distributes applications between the cloud, data producing devices, and devices at the edges of wireless and fixed networks. Edge computing brings AI methods closer to the physical environment. This enables deep integration of AI with applications supporting humans in their activities and with machines to realise autonomous systems. AI is integrated with the edge computing platform as well, for example, to decide optimal locations for computations
We study situation-aware, self-organizing and self-managing software platforms that use efficiently edge computing infrastructures for 5G and beyond. We enable trust with distributed ledger technologies and privacy-by-design methods. We push edge computing to the limits by embedding computations and AI into physical objects that are digitally fabricated to fit to their purpose. We use distributed artificial intelligence, big data tools, and machine learning methods to explore situation awareness for both end-user applications and the edge computing platform. We implement AI methods in ethical manner and emphasise testing in real environments. We expect our research to shed light on how humans can benefit from edge computing and how it can be used to realise resource-efficient systems.