Classification and detection of intelligent house resident activities using multiagent - , Mohd. Marufuzzaman; M. B. I., Raez; M. A. M., Ali; Rahman, Labonnah F. (2013)
The intelligent home research requires understanding of the human behavior and recognizing patterns of activities of daily living (ADL).However instead of understand the psychosomatic nature of human early projects in this area simply employed intelligence to the household appliance.This paper proposed an algorithm for detecting ADL.The proposed method is based on two opposite state entity extraction.The method reflects on the common data flow of smart home event sequence.The developed algorithm clusters the smart home events by isolating opposite status of home appliance. Result shows that, the algorithm can successfully identify 135 unique tasks of different lengths.This algorithm is surely being an alternate way of pattern recognition in intelligent home.