We illustrate the PERSONA context-awareness framework applied to a ma jor problem in Ambient Intelligence, namely user activ- ity monitoring, that requires to infer new knowledge from collected and fused sensor data, dealing with highly dynamic environments where de- vices continuously change their availability and (or) physical location. We describe the Sensor Abstraction and Integration Layer (SAIL), we intro- duce the Human Posture Classification component, which is one partic- ular context information provider, and finally we describe the Activity Monitor, which is a reasoner that delivers aggregated/derived context events in terms of the context ontology.

Sensor data fusion for activity monitoring in ambient assisted living environments

Furfari F;Lenzi S;Chessa S
2009

Abstract

We illustrate the PERSONA context-awareness framework applied to a ma jor problem in Ambient Intelligence, namely user activ- ity monitoring, that requires to infer new knowledge from collected and fused sensor data, dealing with highly dynamic environments where de- vices continuously change their availability and (or) physical location. We describe the Sensor Abstraction and Integration Layer (SAIL), we intro- duce the Human Posture Classification component, which is one partic- ular context information provider, and finally we describe the Activity Monitor, which is a reasoner that delivers aggregated/derived context events in terms of the context ontology.
2009
Istituto di Scienza e Tecnologie dell'Informazione "Alessandro Faedo" - ISTI
978-3-528-08030-3
Ambient Intelligence
Context Awareness
Data Fusion
Artificial Vision
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/62356
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