Multi-sensor data fusion within the belief functions framework - application to smart home services

Bastien Pietropaoli 1 Michele Dominici 1 Frédéric Weis 1
1 ACES - Ambient computing and embedded systems
IRISA - Institut de Recherche en Informatique et Systèmes Aléatoires, Inria Rennes – Bretagne Atlantique
Abstract : In Smart Home, understanding the environment and what is going on is the basis of all adapted services. Unfortunately, inferring situations and activity recognition directly from raw data is way too complex to be applied. Firstly, we present a layered architecture we are building to process raw data into abstract situations and activities. Secondly, data fusion tools using the belief functions theory are introduced as a general framework to provide a first level of abstraction from raw data given by sensors to a more complex context model. Then a methodology to apply the model to our Smart Home within the belief functions framework, a first implementation and the encountered issues in modeling are discussed.
Type de document :
Communication dans un congrès
Springer. RUSMART 2011 : 4th International Conference on Smart Space and next generation wired/wireless networking s, Aug 2011, Saint Petersburg, Russia. Springer, pp.123-134, 2011, 〈10.1007/978-3-642-22875-9_11〉
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https://hal.inria.fr/hal-00702188
Contributeur : Ist Rennes <>
Soumis le : mardi 29 mai 2012 - 15:08:01
Dernière modification le : mercredi 16 mai 2018 - 11:23:01

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Bastien Pietropaoli, Michele Dominici, Frédéric Weis. Multi-sensor data fusion within the belief functions framework - application to smart home services. Springer. RUSMART 2011 : 4th International Conference on Smart Space and next generation wired/wireless networking s, Aug 2011, Saint Petersburg, Russia. Springer, pp.123-134, 2011, 〈10.1007/978-3-642-22875-9_11〉. 〈hal-00702188〉

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