LivingCare - An autonomously learning, human centered home automation system: Collection and preliminary analysis of a large dataset of real living situations

BIB
Eckert, Ralf Müller, Sebastian Glende, Sebastian Gerka, Alexander Hein, Andreas Welge, Ralph
Zukunft Lebensräume Kongress 2016 (ZL 2016)
Within the scope of LivingCare, a BMBF funded research project, a real senior residence was equipped with a large amount of home automation sensors. More than sixty sensors and actuators were installed in this apartment. This automa-tion system is working totally passive in the background. It doesn't perform any actions. All actions performed by hu-mans like switching light on or off, setting the temperature and the usage of electric devices like TVs will only be recorded as data and not performed by the system. This data is collected over a period of 18 months. Thus, one of the largest mobility and characteristics datasets based on home automation sensors will be acquired. This data will be the foundation for developing autonomously learning algorithms. During the second project phase these algorithms will start to control functions of the home automation system. The projects objective is to develop an autonomously learning home automation system that automatically adapts to the resident's behavior. The system will be able to grow with the users needs. With all the possible data collected it will be able to support daily actions, recognize behavior changes over timer and will be able to call help in emergency situations.
2016
inproceedings
549-557
LivingCare
An autonomously learning automation system for sustainable and age-appropriate living