An Adaptive System for Home Monitoring Using a Multiagent Classification of Patterns

This research takes place in the S(MA)2D project which proposes software architecture to monitor elderly people in their own homes. We want to build patterns dynamically from data about activity, movements, and physiological information of the monitored people. To achieve that, we propose a multiage...

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Bibliographic Details
Main Authors: Ali Rammal, Sylvie Trouilhet, Nicolas Singer, Jean-Marie Pécatte
Format: Article
Language:English
Published: Wiley 2008-01-01
Series:International Journal of Telemedicine and Applications
Online Access:http://dx.doi.org/10.1155/2008/136054
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Summary:This research takes place in the S(MA)2D project which proposes software architecture to monitor elderly people in their own homes. We want to build patterns dynamically from data about activity, movements, and physiological information of the monitored people. To achieve that, we propose a multiagent method of classification: every agent has a simple know-how of classification. Data generated at this local level are communicated and adjusted between agents to obtain a set of patterns. The patterns are used at a personal level, for example to raise an alert, but also to evaluate global risks (epidemic, heat wave). These data are dynamic; the system has to maintain the built patterns and has to create new patterns. So, the system is adaptive and can be spread on a large scale.
ISSN:1687-6415
1687-6423