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Sensor Network Infrastructure for a Home Care Monitoring System
Istituto di Scienza e Tecnologie dell’Informazione (ISTI), Natl Res Council, Pisa, Italy; Dept Comp Sci, Univ Pisa, Pisa, Italy.
Örebro University, School of Science and Technology. (AASS)
XLAB Doo, XLAB Res, Ljubljana, Slovenia.
Istituto di Scienza e Tecnologie dell’Informazione (ISTI), Natl Res Council, Pisa, Italy.
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2014 (English)In: Sensors, ISSN 1424-8220, E-ISSN 1424-8220, Vol. 14, no 3, p. 3833-3860Article in journal (Refereed) Published
Abstract [en]

This paper presents the sensor network infrastructure for a home care system that allows long-term monitoring of physiological data and everyday activities. The aim of the proposed system is to allow the elderly to live longer in their home without compromising safety and ensuring the detection of health problems. The system offers the possibility of a virtual visit via a teleoperated robot. During the visit, physiological data and activities occurring during a period of time can be discussed. These data are collected from physiological sensors (e.g., temperature, blood pressure, glucose) and environmental sensors (e.g., motion, bed/chair occupancy, electrical usage). The system can also give alarms if sudden problems occur, like a fall, and warnings based on more long-term trends, such as the deterioration of health being detected. It has been implemented and tested in a test environment and has been deployed in six real homes for a year-long evaluation. The key contribution of the paper is the presentation of an implemented system for ambient assisted living (AAL) tested in a real environment, combining the acquisition of sensor data, a flexible and adaptable middleware compliant with the OSGistandard and a context recognition application. The system has been developed in a European project called GiraffPlus.

Place, publisher, year, edition, pages
Basel: MDPI AG , 2014. Vol. 14, no 3, p. 3833-3860
Keywords [en]
middleware; sensor architecture; ambient assisted living; monitoring; elderly
National Category
Computer Sciences
Research subject
Computer Science
Identifiers
URN: urn:nbn:se:oru:diva-34124DOI: 10.3390/s140303833ISI: 000336783300002PubMedID: 24573309Scopus ID: 2-s2.0-84896864841OAI: oai:DiVA.org:oru-34124DiVA, id: diva2:704187
Funder
EU, FP7, Seventh Framework Programme, 288173Available from: 2014-03-11 Created: 2014-03-11 Last updated: 2018-06-05Bibliographically approved

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Ullberg, JonasKarlsson, LarsCoradeschi, Silvia

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