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....
| 发表在: | ISIEA 2010 - 2010 IEEE Symposium on Industrial Electronics and Applications |
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| 主要作者: | |
| 格式: | Conference paper |
| 语言: | English |
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2010
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| 在线阅读: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-79251561241&doi=10.1109%2fISIEA.2010.5679411&partnerID=40&md5=14e545a6efcf56a6a92116fa4dfa4c4e |
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Alam M.R.; Reaz M.B.I.; Mohd Ali M.A.; Samad S.A.; Hashim F.H.; Hamzah M.K. |
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Alam M.R.; Reaz M.B.I.; Mohd Ali M.A.; Samad S.A.; Hashim F.H.; Hamzah M.K. 2-s2.0-79251561241 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 |
2-s2.0-79251561241 |
| spellingShingle |
2-s2.0-79251561241 Human activity classification for smart home: A multiagent approach |
| author_facet |
2-s2.0-79251561241 |
| author_sort |
2-s2.0-79251561241 |
| 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 |
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| container_issue |
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| 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 |
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| issn |
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| language |
English |
| format |
Conference paper |
| accesstype |
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| record_format |
scopus |
| collection |
Scopus |
| _version_ |
1828987884290441216 |