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    題名: RFID-Based Human Behavior Modeling and Anomaly Detection for Elderly Care
    其他題名: 基於RFID的人類行為塑模與異常偵測於老人照護
    作者: Hsu, Hui-Huang;Chen, Chien-Chen
    貢獻者: 淡江大學資訊工程學系
    關鍵詞: RFID;behavior modeling;anomaly detection;elderly care;clustering
    日期: 2010-12
    上傳時間: 2011-10-01 12:01:05 (UTC+8)
    出版者: Amsterdam: I O S Press
    摘要: This research aimed at building an intelligent system that can detect abnormal behavior for the elderly at home. Active RFID tags can be deployed at home to help collect daily movement data of the elderly who carries an RFID reader. When the reader detects the signals from the tags, RSSI values that represent signal strength are obtained. The RSSI values are reversely related to the distance between the tags and the reader and they are recorded following the movement of the user. The movement patterns, not the exact locations, of the user are the major concern. With the movement data (RSSI values), the clustering technique is then used to build a personalized model of normal behavior. After the model is built, any incoming datum outside the model can be viewed as abnormal and an alarm can be raised by the system. In this paper, we present the system architecture for RFID data collection and preprocessing, clustering for anomaly detection, and experimental results. The results show that this novel approach is promising.
    關聯: Mobile Information Systems 6(4), pp.341-354
    DOI: 10.3233/MIS-2010-0107
    顯示於類別:[資訊工程學系暨研究所] 期刊論文


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