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http://dx.doi.org/10.5302/J.ICROS.2007.13.6.542

Intelligent Modeling of User Behavior based on FCM Quantization for Smart home  

Chung, Woo-Yong (연세대학교 전기전자공학과)
Lee, Jae-Hun (연세대학교 전기전자공학과)
Yon, Suk-Hyun (연세대학교 전기전자공학과)
Cho, Young-Wan (서경대학교 컴퓨터공학과)
Kim, Eun-Tai (연세대학교 전기전자공학과)
Publication Information
Journal of Institute of Control, Robotics and Systems / v.13, no.6, 2007 , pp. 542-546 More about this Journal
Abstract
In the vision of ubiquitous computing environment, smart objects would communicate each other and provide many kinds of information about user and their surroundings in the home. This information enables smart objects to recognize context and to provide active and convenient services to the customers. However in most cases, context-aware services are available only with expert systems. In this paper, we present generalized activity recognition application in the smart home based on a naive Bayesian network(BN) and fuzzy clustering. We quantize continuous sensor data with fuzzy c-means clustering to simplify and reduce BN's conditional probability table size. And we apply mutual information to learn the BN structure efficiently. We show that this system can recognize user activities about 80% accuracy in the web based virtual smart home.
Keywords
activity recognition; context-awareness; Bayesian network; smart home; fuzzy clustering;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
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