Abstract
Aging of population and increasing complexity of domestic equipment justify the growth of scientific interest in surveillance of independent older adults at home. Our proposal focuses on imperceptibility of a sensing network which, besides detection of complex actions, analyses their irregularity and issues control commands to a safety-oriented active environment for living. The investigated design of mixed residential and wearable sensor network includes domestic equipment-embedded usage sensors and accelerometer-fitted footwear with a presence message broadcast. Synchronously detected events contribute to recognizing complex activities of daily living and to building personalized behavioral patterns. A short- or long-time variation of these patterns may be understood as a deterioration of psychophysiological status and, in context of particular device operation error, modifies the home automation algorithms accordingly. An implementation case study supported by results of volunteers-based experiment confirms the correctness of actions recognition and feasibility of the automatic system for user behavior-dependent safety prevention .
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Acknowledgment
The scientific work supported by the AGH University of Science and Technology in Krakow, under the grant No. 11.11.120.612.
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Augustyniak, P. (2018). Imperceptible Sensor Infrastructure for Rule-Based Active Safety Prevention in the Household. In: Hippe, Z., Kulikowski, J., Mroczek, T. (eds) Human-Computer Systems Interaction. Advances in Intelligent Systems and Computing, vol 551. Springer, Cham. https://doi.org/10.1007/978-3-319-62120-3_1
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