Improved Weighted Centroid Localization in Smart Ubiquitous Environments

  • Authors:

  • Stephan Schuhmann;Klaus Herrmann;Kurt Rothermel;Jan Blumenthal;Dirk Timmermann

  • Affiliations:

  • Institute of Parallel and Distributed Systems (IPVS), University of Stuttgart, Germany;Institute of Parallel and Distributed Systems (IPVS), University of Stuttgart, Germany;Institute of Parallel and Distributed Systems (IPVS), University of Stuttgart, Germany;Institute of Applied Microelectronics and CE, University of Rostock, Germany;Institute of Applied Microelectronics and CE, University of Rostock, Germany

  • Venue:
  • UIC '08 Proceedings of the 5th international conference on Ubiquitous Intelligence and Computing
  • Year:
  • 2008

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Abstract

Location-awareness is highly relevant subject in ubiquitous computing, as many applications exploit location information to provide adequate services or adapt to a changing physical environment. While GPS provides reliable outdoor localization, indoor positioning systems present a bigger challenge. Many indoor localization systems have been proposed. However, most of them rely on customized hardware or presume some dedicated infrastructure. In this paper, we focus on WLAN-based localization in smart ubiquitous environments. We propose an improved scheme of the Weighted Centroid Localization(WCL) algorithm that is robust and provides higher location accuracy than the original WCL algorithm. The improvements are based on the use of dynamic weighting factors that are solely dependent on the correlation of the Received Signal Strength Indicators of the received beacon signals. Compared to the original WCL scheme, our approach does not increase requirements to the environment. Real-world experiments in a typical environment that we report on in this paper confirm that the increased location accuracy determined in previous calculations is reproducible in a realistic noisy environment. This provides a simple, cost-efficient, and battery-conserving, but yet adequate technique for getting the accurate location information of mobile devices.