Abstract
As the population is aging, the need for assistance systems in the ambient assisted living domain is high. With the increased availability of data provided by ambient sensors, devices, wearables and the improvements in the artificial intelligence field, there lies great potential for inferring knowledge about the elderly and the context, in which assistance is provided by a system. Being able to correlate and learn from dynamic and variable data enables a continuously optimized, individualized and effective assistance. The goal of this research is to develop an underlying, reusable concept for intelligent and user-centered assistance. Therefore, we experiment with several automation systems as use cases for elderly assistance.
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