AI in Assistance
Intelligent Monitoring and Assistance in Health Care
Prof. Dr.-Ing. Thomas Kirste
Human behavior creates complex dynamic systems that are fundamentally hard to track. Making sense of ambiguous and noisy sensor data thus becomes a core challenge in providing reliable intelligent assistance and monitoring for health care applications in Smart Home and Smart Hospital environments. We discuss the underlying causes for this complexity and we look at recent approaches using hybrid AI methods that aim to solve this, combining symbolic, probabilistic, and neural reasoning. Finally, we show how these hybrid AI methods can be translated to further important application areas in Life Science and Medicine, broadening their impact.