RFID-based personalized behavior modeling

Hui Huang Hsu, Zixue Cheng, Timothy K. Shih, Chien Chen Chen

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Scopus citations

Abstract

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.

Original languageEnglish
Title of host publicationUIC-ATC 2009 - Symposia and Workshops on Ubiquitous, Autonomic and Trusted Computing in Conjunction with the UIC'09 and ATC'09 Conferences
Pages350-355
Number of pages6
DOIs
StatePublished - 2009
EventSymposia and Workshops on Ubiquitous, Autonomic and Trusted Computing in Conjunction with the UIC'09 and ATC'09 Conferences, UIC-ATC 2009 - Brisbane, Australia
Duration: 7 Jul 20099 Jul 2009

Publication series

NameUIC-ATC 2009 - Symposia and Workshops on Ubiquitous, Autonomic and Trusted Computing in Conjunction with the UIC'09 and ATC'09 Conferences

Conference

ConferenceSymposia and Workshops on Ubiquitous, Autonomic and Trusted Computing in Conjunction with the UIC'09 and ATC'09 Conferences, UIC-ATC 2009
Country/TerritoryAustralia
CityBrisbane
Period7/07/099/07/09

Keywords

  • Ambient intelligence
  • Clustering analysis
  • Elderly care
  • Machine learning
  • RFID

Fingerprint

Dive into the research topics of 'RFID-based personalized behavior modeling'. Together they form a unique fingerprint.

Cite this