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....

全面介绍

书目详细资料
发表在:ISIEA 2010 - 2010 IEEE Symposium on Industrial Electronics and Applications
主要作者: 2-s2.0-79251561241
格式: Conference paper
语言:English
出版: 2010
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
实物特征
总结: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.
ISSN:
DOI:10.1109/ISIEA.2010.5679411