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Erschienen in: Artificial Life and Robotics 3/2017

29.03.2017 | Original Article

Simple observation sensor system and local community network model: Real society experiment on solitary death prevention for low-income single elderly residents in collective housing

verfasst von: Takeshi Morishita, Shinjiro Mochida

Erschienen in: Artificial Life and Robotics | Ausgabe 3/2017

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Abstract

This paper proposes a sensor system for monitoring elderly residents living alone in low-income housing, and a local community network model to support these residents. This observation sensor system estimates living conditions by detecting entry point door movement, and safety information on the target residents is delivered to family and support staff via e-mail. In addition, the sensor unit is equipped with a networked flash-lighting and e-mail warning function to notify those in the community about accidents. Design and development costs were minimized by dispersing the flash light-emitting unit of the sensor unit on multiple units, making this a feasible option for low-income elderly residents. In addition, we implemented this sensor system and operated the local community network model at a collective housing to test its efficacy as a new system in real-world conditions. We present that this community network prevents the isolation of the elderly residents using the sensor system installed in their community, and improves communication between residents, their families, and their neighbors, thereby improving their safety. We also show that the community network prevents the isolation of elderly people by quietly keeping constant involvement with people in broader society, and is a social network system aimed at preventing solitary death.

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Metadaten
Titel
Simple observation sensor system and local community network model: Real society experiment on solitary death prevention for low-income single elderly residents in collective housing
verfasst von
Takeshi Morishita
Shinjiro Mochida
Publikationsdatum
29.03.2017
Verlag
Springer Japan
Erschienen in
Artificial Life and Robotics / Ausgabe 3/2017
Print ISSN: 1433-5298
Elektronische ISSN: 1614-7456
DOI
https://doi.org/10.1007/s10015-017-0363-4

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