This article describes the development of an assistive sociotechnical system aimed at supporting active and healthy aging based on personalization and application of sensor measurements. In this work we rely on both historical and real-time data coming from environmental, behavioral and biomedical measures. Further, this data is analyzed to highlight patterns and to identify undesirable situations based on deviations from recognized patterns. This way the user’s state and lifestyle trends can be determined based on data from several sensors located in and around the home. Our results promise to increase the safety of aging populations via assistive technology stack integration with personal AI-assistants that have started to fit into everyday life and modern households.