Mobile Information Systems

Mobile Information Systems / 2010 / Article

Open Access

Volume 6 |Article ID 460103 |

Hui-Huang Hsu, Chien-Chen Chen, "RFID-Based Human Behavior Modeling and Anomaly Detection for Elderly Care", Mobile Information Systems, vol. 6, Article ID 460103, 14 pages, 2010.

RFID-Based Human Behavior Modeling and Anomaly Detection for Elderly Care

Received02 Dec 2010
Accepted02 Dec 2010


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.

Copyright © 2010 Hindawi Publishing Corporation. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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