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Detecting activities for assisted living

Monekosso, Dorothy; Remagnino, Paolo

Authors

Dorothy Monekosso

Paolo Remagnino



Abstract

The objective is to detect activities taking place in a home for the purpose of creating models of behavior for the occupant. An array of sensors captures the status of appliances used in the home. Models for the occupant’s activities are built from the captured data using unsupervised learning techniques. Predictive models can be used in a number of ways: to enhance user experience, to maximize resource usage efficiency, for safety and for security. This work focuses on supporting independent living and enhancing quality of life for older persons. The goal is for the system to distinguish between normal and anomalous behavior. In this paper, we present the results of unsupervised classification techniques applied to the problem of modeling activity.

Citation

Monekosso, D., & Remagnino, P. (2008). Detecting activities for assisted living. Communications in Computer and Information Science, 11, 228-237. https://doi.org/10.1007/978-3-540-85379-4_28

Journal Article Type Conference Paper
Conference Name Ambient Assisted Living Systems
Conference Location Technische Universität Darmstadt, Germany
Publication Date Aug 17, 2008
Journal Communications in Computer and Information Science
Print ISSN 1865-0929
Electronic ISSN 1865-0937
Publisher Springer Verlag (Germany)
Peer Reviewed Not Peer Reviewed
Volume 11
Pages 228-237
ISBN 9783540853787
DOI https://doi.org/10.1007/978-3-540-85379-4_28
Keywords activities, assisted living
Public URL https://uwe-repository.worktribe.com/output/1010171
Additional Information Title of Conference or Conference Proceedings : Ambient Assisted Living Systems


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