mailto:uumlib@uum.edu.my 24x7 Service; AnyTime; AnyWhere

Classification and detection of intelligent house resident activities using multiagent

,, Mohd. Marufuzzaman and M. B. I., Raez and M. A. M., Ali and Rahman, Labonnah F. (2013) Classification and detection of intelligent house resident activities using multiagent. In: 4th International Conference on Computing and Informatics (ICOCI 2013), 28 -30 August 2013, Kuching, Sarawak, Malaysia.

[thumbnail of PID60.pdf] PDF
Restricted to Registered users only

Download (476kB) | Request a copy

Abstract

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.

Item Type: Conference or Workshop Item (Paper)
Additional Information: ISBN: 9789832078791 Organized by: Universiti Utara Malaysia
Uncontrolled Keywords: Smart home, pattern recognition, activities of daily living (ADL), activity classification, multiagent system
Subjects: Q Science > QA Mathematics > QA76 Computer software
Divisions: School of Computing
Depositing User: Mrs. Norazmilah Yaakub
Date Deposited: 25 Aug 2014 00:32
Last Modified: 28 Apr 2016 02:24
URI: https://repo.uum.edu.my/id/eprint/12008

Actions (login required)

View Item View Item