Human activity classification for smart home: A multiagent approach

Human activity classification for smart home: A multiagent approach

Smart home research requires study of psychological characteristics of home user. People follow some specific patterns in their life style. Inhabitant activity classification plays a vital role to predict smart home events. The paper proposed a multiagent system to track the user for task isolation....

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Published in:ISIEA 2010 - 2010 IEEE Symposium on Industrial Electronics and Applications
Main Author: Alam M.R.; Reaz M.B.I.; Mohd Ali M.A.; Samad S.A.; Hashim F.H.; Hamzah M.K.
Format: Conference paper
Language:English
Published: 2010
Online Access:https://www.scopus.com/inward/record.uri?eid=2-s2.0-79251561241&doi=10.1109%2fISIEA.2010.5679411&partnerID=40&md5=14e545a6efcf56a6a92116fa4dfa4c4e
id 2-s2.0-79251561241
spelling 2-s2.0-79251561241
Alam M.R.; Reaz M.B.I.; Mohd Ali M.A.; Samad S.A.; Hashim F.H.; Hamzah M.K.
Human activity classification for smart home: A multiagent approach
2010
ISIEA 2010 - 2010 IEEE Symposium on Industrial Electronics and Applications


10.1109/ISIEA.2010.5679411
https://www.scopus.com/inward/record.uri?eid=2-s2.0-79251561241&doi=10.1109%2fISIEA.2010.5679411&partnerID=40&md5=14e545a6efcf56a6a92116fa4dfa4c4e
Smart home research requires study of psychological characteristics of home user. People follow some specific patterns in their life style. Inhabitant activity classification plays a vital role to predict smart home events. The paper proposed a multiagent system to track the user for task isolation. The system is composed of cooperative agents which works by sharing local views of individual agents. An algorithm is derived based on opposite entity state extraction for activity classification. The algorithm clusters the smart home events by isolating opposite status of home appliance. Result shows that the proposed algorithm can successfully identify inhabitant activities of various lengths. ©2010 IEEE.


English
Conference paper
author Alam M.R.; Reaz M.B.I.; Mohd Ali M.A.; Samad S.A.; Hashim F.H.; Hamzah M.K.
spellingShingle Alam M.R.; Reaz M.B.I.; Mohd Ali M.A.; Samad S.A.; Hashim F.H.; Hamzah M.K.
Human activity classification for smart home: A multiagent approach
author_facet Alam M.R.; Reaz M.B.I.; Mohd Ali M.A.; Samad S.A.; Hashim F.H.; Hamzah M.K.
author_sort Alam M.R.; Reaz M.B.I.; Mohd Ali M.A.; Samad S.A.; Hashim F.H.; Hamzah M.K.
title Human activity classification for smart home: A multiagent approach
title_short Human activity classification for smart home: A multiagent approach
title_full Human activity classification for smart home: A multiagent approach
title_fullStr Human activity classification for smart home: A multiagent approach
title_full_unstemmed Human activity classification for smart home: A multiagent approach
title_sort Human activity classification for smart home: A multiagent approach
publishDate 2010
container_title ISIEA 2010 - 2010 IEEE Symposium on Industrial Electronics and Applications
container_volume
container_issue
doi_str_mv 10.1109/ISIEA.2010.5679411
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-79251561241&doi=10.1109%2fISIEA.2010.5679411&partnerID=40&md5=14e545a6efcf56a6a92116fa4dfa4c4e
description Smart home research requires study of psychological characteristics of home user. People follow some specific patterns in their life style. Inhabitant activity classification plays a vital role to predict smart home events. The paper proposed a multiagent system to track the user for task isolation. The system is composed of cooperative agents which works by sharing local views of individual agents. An algorithm is derived based on opposite entity state extraction for activity classification. The algorithm clusters the smart home events by isolating opposite status of home appliance. Result shows that the proposed algorithm can successfully identify inhabitant activities of various lengths. ©2010 IEEE.
publisher
issn
language English
format Conference paper
accesstype
record_format scopus
collection Scopus
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