2011 | OriginalPaper | Buchkapitel
Smart Sweet Home… A Pervasive Environment for Sensing our Daily Activity?
verfasst von : Norbert Noury, Julien Poujaud, Anthony Fleury, Ronald Nocua, Tareq Haddidi, Pierre Rumeau
Erschienen in: Activity Recognition in Pervasive Intelligent Environments
Verlag: Atlantis Press
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Humans deeply modified their relationship to their housings during the past centuries. Once a shelter where humans could find protection and have rest, the living place successfully evolved to become the midpoint of the family, the expression of own culture and nowadays a more self centered place where individuals develop their own personal aspirations and express their social position. With the introduction of communication technologies, humans may become nomads again with the ability to stay connected with others in any place at any time but, as a paradox, we can observe a wide movement for “cocooning”. Among all the services a living place can bring to inhabitants, we may list comfort, security, wellness and also health services. Thus a new living place is to be invented, becoming the “witness” of our breath, perceiving the inhabitants rhythms of activities, habits, tastes and wishes. Eventually, the “smart home” become the “Health Smart Home” to enable the follow up of physical and health status and meet the new concepts of “Aging in place” and “citizen health care”. We listed some of the research projects in Health Smart Home, which were launched worldwide to discover they are mostly based on very basic sensors and simple algorithms. We experienced our own Health Smart Home to prove that temporal analysis of data output from simple presence sensors is already worthwhile. We first produced “ambulatograms”, a temporal representation of the daily activity gathered from the presence sensors, and then discovered regular patterns of activities which we named “circadian activity rhythms (car)”, the direct relationship between night and day level of activities and also the information contained in periods of inactivity. We now concentrate on the automatic recognition of the daily Activities with multiple sensor fusions methods.