In this paper, we propose the human behavior detection and activity support environment Vivid Room. Human behaviors in Vivid Room are detected by many kinds of sensors embedded in the room (i. e. magnet sensors for doors/drawers, micro-switches for chairs, ID-tags for humans.) and those information are collected by sensor server via RF-tag system and LAN. In order to recognize meaningful human behaviors (i. e. studying, eating, resting, etc.), we've employed ID4 based learning system. Also we've developed human activity support system by using sound and voice by taking account of human behaviors in the room. The experimental results, which denote the accuracy of human behavior recognition and the quality of human support, are also shown.
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