Abstract
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. All actions performed by humans like switching light on or off, setting the temperature and the usage of electric devices like TVs will be recorded. 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 project’s objective is to develop an autonomously learning home automation system that automatically adapts to the residents’ 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 time and will be able to call help in emergency situations.
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Eckert, R., Müller, S., Glende, S., Gerka, A., Hein, A., Welge, R. (2017). LivingCare—An Autonomously Learning, Human Centered Home Automation System: Collection and Preliminary Analysis of a Large Dataset of Real Living Situations. In: Wichert, R., Mand, B. (eds) Ambient Assisted Living. Advanced Technologies and Societal Change. Springer, Cham. https://doi.org/10.1007/978-3-319-52322-4_4
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DOI: https://doi.org/10.1007/978-3-319-52322-4_4
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