Ambient Intelligence (AmI) defines a scenario involving people living in a smart environment enriched by pervasive sensory devices with the goal of assisting them in a proactive way to satisfy their needs. In a home scenario, an AmI system controls the environment according to a user's lifestyle and daily routine. To achieve this goal, one fundamental task is to recognize the user's activities in order to generate his daily activities profile. In this chapter,we present a simpleAMI system for a home scenario to recognize and predict users' activities.With this predictive capability, it is possible to anticipate their actions and improve their quality of life. Our approach uses a Hidden Markov Model (HMM) to recognize activities and deal with the intrinsic uncertainty of sensory information. The concepts of this domain have been formally defined to allow a higher-level system to enrich its knowledge base

Gaglio, S., Martorella, G. (2014). An AMI System for User Daily Routine Recognition and Prediction. In S. Gaglio, G. Lo Re (a cura di), Advances onto the Internet of Things: How Ontologies Make the Internet of Things Meaningful (pp. 33-45) [10.1007/978-3-319-03992-3_3].

An AMI System for User Daily Routine Recognition and Prediction

GAGLIO, Salvatore;Martorella, Gloria
2014-01-01

Abstract

Ambient Intelligence (AmI) defines a scenario involving people living in a smart environment enriched by pervasive sensory devices with the goal of assisting them in a proactive way to satisfy their needs. In a home scenario, an AmI system controls the environment according to a user's lifestyle and daily routine. To achieve this goal, one fundamental task is to recognize the user's activities in order to generate his daily activities profile. In this chapter,we present a simpleAMI system for a home scenario to recognize and predict users' activities.With this predictive capability, it is possible to anticipate their actions and improve their quality of life. Our approach uses a Hidden Markov Model (HMM) to recognize activities and deal with the intrinsic uncertainty of sensory information. The concepts of this domain have been formally defined to allow a higher-level system to enrich its knowledge base
2014
Settore ING-INF/05 - Sistemi Di Elaborazione Delle Informazioni
Gaglio, S., Martorella, G. (2014). An AMI System for User Daily Routine Recognition and Prediction. In S. Gaglio, G. Lo Re (a cura di), Advances onto the Internet of Things: How Ontologies Make the Internet of Things Meaningful (pp. 33-45) [10.1007/978-3-319-03992-3_3].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10447/97596
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