Resource-aware on-line RFID localization using proximity data

Authors:
Christoph Scholz;Stephan Doerfel;Martin Atzmueller;Andreas Hotho;Gerd Stumme
Affiliations:
Knowledge & Data Engineering Group, University of Kassel, Kassel, Germany;Knowledge & Data Engineering Group, University of Kassel, Kassel, Germany;Knowledge & Data Engineering Group, University of Kassel, Kassel, Germany;Data Mining and Information Retrieval Group, University of Würzburg, Würzburg, Germany;Knowledge & Data Engineering Group, University of Kassel, Kassel, Germany
Venue:
ECML PKDD'11 Proceedings of the 2011 European conference on Machine learning and knowledge discovery in databases - Volume Part III
Year:
2011

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Abstract

This paper focuses on resource-aware and cost-effective indoor-localization at room-level using RFID technology. In addition to the tracking information of people wearing active RFID tags, we also include information about their proximity contacts. We present an evaluation using real-world data collected during a conference: We complement state-of-the-art machine learning approaches with strategies utilizing the proximity data in order to improve a core localization technique further.