AAL Middleware Infrastructure for Green Bed Activity Monitoring
This paper describes a service-oriented middleware platform for ambient assisted living and its use in two different bed activity services: bedsore prevention and sleeping monitoring. A detailed description of the middleware platform, its elements and interfaces, as well as a service that is able to...
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Series: | Journal of Sensors |
Online Access: | http://dx.doi.org/10.1155/2013/510126 |
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doaj-167925c57d6242ebb5711604f87d57482020-11-25T00:57:14ZengHindawi LimitedJournal of Sensors1687-725X1687-72682013-01-01201310.1155/2013/510126510126AAL Middleware Infrastructure for Green Bed Activity MonitoringFilippo Palumbo0Paolo Barsocchi1Francesco Furfari2Erina Ferro3ISTI-CNR, Pisa Research Area, Via G.Moruzzi 1, 56124 Pisa, ItalyISTI-CNR, Pisa Research Area, Via G.Moruzzi 1, 56124 Pisa, ItalyISTI-CNR, Pisa Research Area, Via G.Moruzzi 1, 56124 Pisa, ItalyISTI-CNR, Pisa Research Area, Via G.Moruzzi 1, 56124 Pisa, ItalyThis paper describes a service-oriented middleware platform for ambient assisted living and its use in two different bed activity services: bedsore prevention and sleeping monitoring. A detailed description of the middleware platform, its elements and interfaces, as well as a service that is able to classify some typical user's positions in the bed is presented. Wireless sensor networks are supposed to be widely deployed in indoor settings and on people's bodies in tomorrow's pervasive computing environments. The key idea of this work is to leverage their presence by collecting the received signal strength measured among fixed general-purpose wireless sensor devices, deployed in the environment, and wearable ones. The RSS measurements are used to classify a set of user's positions in the bed, monitoring the activities of the user, and thus supporting the bedsores and the sleep monitoring issues. Moreover, the proposed services are able to decrease the energy consumption by exploiting the context information coming from the proposed middleware.http://dx.doi.org/10.1155/2013/510126 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Filippo Palumbo Paolo Barsocchi Francesco Furfari Erina Ferro |
spellingShingle |
Filippo Palumbo Paolo Barsocchi Francesco Furfari Erina Ferro AAL Middleware Infrastructure for Green Bed Activity Monitoring Journal of Sensors |
author_facet |
Filippo Palumbo Paolo Barsocchi Francesco Furfari Erina Ferro |
author_sort |
Filippo Palumbo |
title |
AAL Middleware Infrastructure for Green Bed Activity Monitoring |
title_short |
AAL Middleware Infrastructure for Green Bed Activity Monitoring |
title_full |
AAL Middleware Infrastructure for Green Bed Activity Monitoring |
title_fullStr |
AAL Middleware Infrastructure for Green Bed Activity Monitoring |
title_full_unstemmed |
AAL Middleware Infrastructure for Green Bed Activity Monitoring |
title_sort |
aal middleware infrastructure for green bed activity monitoring |
publisher |
Hindawi Limited |
series |
Journal of Sensors |
issn |
1687-725X 1687-7268 |
publishDate |
2013-01-01 |
description |
This paper describes a service-oriented middleware platform for ambient assisted living and its use in two different bed activity services: bedsore prevention and sleeping monitoring. A detailed description of the middleware platform, its elements and interfaces, as well as a service that is able to classify some typical user's positions in the bed is presented. Wireless sensor networks are supposed to be widely deployed in indoor settings and on people's bodies in tomorrow's pervasive computing environments. The key idea of this work is to leverage their presence by collecting the received signal strength measured among fixed general-purpose wireless sensor devices, deployed in the environment, and wearable ones. The RSS measurements are used to classify a set of user's positions in the bed, monitoring the activities of the user, and thus supporting the bedsores and the sleep monitoring issues. Moreover, the proposed services are able to decrease the energy consumption by exploiting the context information coming from the proposed middleware. |
url |
http://dx.doi.org/10.1155/2013/510126 |
work_keys_str_mv |
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