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Issue title: Human-centred Ambient Intelligence: Cognitive Approaches, Reasoning and Learning
Guest editors: Zoe Falomir, Juan A. Ortega, Natividad Martínez and Hans Guesguen
Article type: Research Article
Authors: Torres-Sospedra, Joaquína; * | Belmonte-Fernández, Óscara | Montoliu, Raúla | Trilles, Sergioa | Calia, Andreab
Affiliations: [a] Institute of New Imaging Technologies, Universitat Jaume I, Castellón, Spain. E-mails: jtorres@uji.es, oscar.belmonte@uji.es, montoliu@uji.es, strilles@uji.es | [b] Department BE-OP, European Organization for Nuclear Research, CERN Cedex, France. E-mail: andrea.calia@cern.ch
Correspondence: [*] Corresponding author. E-mail: jtorres@uji.es.
Abstract: This paper presents an in-home monitoring system based on WiFi fingerprints for Ambient Assisted Living. WiFi fingerprints are used to continuously locate a patient at the different rooms in her/his home. The experiments performed provide a correctly location rate of 96% in the best case of all studied scenarios. The behavior obtained by location monitoring allows to detect anomalous behavior such as long stays in rooms out of the common schedule. The main characteristics of the presented system are: a) it is robust enough to work without an own WiFi access point, which in turn means a very affordable solution; b) low obtrusiveness, as it is based on the use of a mobile phone; c) highly interoperable with other wireless connections (bluetooth, RFID) present in current mobile phones; d) alarms are triggered when any anomalous behavior is detected.
Keywords: Ambient Assisted Living, in-home monitoring, Indoor positioning, WiFi fingerprinting
DOI: 10.3233/AIS-170450
Journal: Journal of Ambient Intelligence and Smart Environments, vol. 9, no. 5, pp. 543-560, 2017
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