The demographic change is no longer a prognosis, but a reality seen in everyday life situations and requires mechanisms to make the public and private space elderly-adequate. These required mechanisms need to consider the varying aging process for each individual as well as adapt to the dynamic daily life of individuals characterized by spatial, temporal and activity variance. Developing assistance systems that are user-adaptive within dynamic environments is a challenging task. AI-based cyber-physical assistance systems enable such adaptive, flexible and individual assistance by processing acquired data from the physical environment using cyber resources and delivering intelligent assistance as well as interfaces to further medical services. This contribution discusses a flexible, reusable, and user-specific concept for AI-based assistance systems. Relying on distributed and heterogeneous data, the user’s context is continuously modeled and reasoned over to infer actionable knowledge within a middleware between the data layer and the application layer. To demonstrate the applicability of the concept, the use case of intelligently supporting patients’ medication adherence is shown.
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