Our paper on exchange of learned interaction patterns to support networked living has been accepted for publication at AmI 2019 (European Conference on Ambient Intelligence). We investigate the reduction of the cold start problem by distribute already learned interaction patterns between different smart homes. In this way, Smart Homes should actually be able to act intelligently with the help of the collective. The Paper results from the master thesis of Edgar Gellert.
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Abstract: The adoption of smart homes is steadily increasing and users expect their homes to act in intelligent ways. One core question is how to learn from user behavior to gain smartness that can be adopted by the system. This paper has a twofold contribution: first, we propose a new approach for letting smart homes learn collaboratively. Second, we present a prototype implementation and discuss challenges learned from this version. This approach should serve as an initiator for the development of intelligent smart home systems outside isolated solutions and on the basis of human needs.
Edgar Gellert, Matthias Böhmer: Collaborative Homes: Exchange of learned interaction patterns to support networked living.
In: Poster Proceedings of European Conference on Ambient Intelligence 2019
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