In this research, we aim at building an intelligent system that can detect abnormal behavior for the elderly at home. Deployment of RFID tags at home helps us collect the daily movement data of the elderly. The clustering technique is then used to build a personalized model of normal behavior based on these RFID data. After the model is built, any incoming datum outside the model can be seen as abnormal. In this paper, we present the design of the system architecture and show the preliminary results for data collection and preprocessing.
Relation:
Proceedings of the Symposia and Workshops on Ubiquitous, Autonomic and Trusted Computing (UIC-ATC 2009), pp.350-355
