Today aging of society is becoming increasingly important. Many people want to live at home as long as possible. Very often this leads to accidents at home, which are unnoticed for a long time and therefore cause severe complications. We propose a cyber-physical system consisting of sensors for motion, light, temperature, and so on, which monitors the behavior of elderly people but is non-invasive in the sense that the persons are not observed by a camera and must not wear certain sensors on their body. Unusual behavior or accidents are registered in-time by a change point detection algorithm based on Markov chains, which does not store any data with the exception of the last datum, so that also the integrity of the elderly people is preserved. For verification of this algorithm, a cyber-physical test environment has been programmed which allows to simulate human common and uncommon behavior in house during day and night. This simulation environment is based on behavior trees and decision theory. The verification results suggest that the implemented cyber-physical system for change point and anomaly detection could be successfully used in the real environment of elderly people to give them help in-time when an accident occurs.
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