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Improving Location Fingerprinting through Motion Detection and Asynchronous Interval Labeling

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Location and Context Awareness (LoCA 2009)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 5561))

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Abstract

Wireless signal strength fingerprinting has become an increasingly popular technique for realizing indoor localization systems using existing WiFi infrastructures. However, these systems typically require a time-consuming and costly training phase to build the radio map. Moreover, since radio signals change and fluctuate over time, map maintenance requires continuous re-calibration. We introduce a new concept called “asynchronous interval labeling” that addresses these problems in the context of user-generated place labels. By using an accelerometer to detect whether a device is moving or stationary, the system can continuously and unobtrusively learn from all radio measurements during a stationary period, thus greatly increasing the number of available samples. Movement information also allows the system to improve the user experience by deferring labeling to a later, more suitable moment. Initial experiments with our system show considerable increases in data collected and improvements to inferred location likelihood, with negligible overhead reported by users.

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Author information

Authors and Affiliations

  1. Institute for Pervasive Computing, ETH Zurich, Switzerland

    Philipp Bolliger

  2. Palo Alto Research Center, Palo Alto, CA, USA

    Kurt Partridge & Maurice Chu

  3. Faculty of Informatics, University of Lugano, Switzerland

    Marc Langheinrich

Authors
  1. Philipp Bolliger
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  2. Kurt Partridge
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  3. Maurice Chu
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  4. Marc Langheinrich
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Editor information

Editors and Affiliations

  1. Computer Science Department, NH 03755, Dartmouth, Hanover, USA

    Tanzeem Choudhury

  2. Complex & Adaptive Systems Laboratory, School of Computer Science & Informatics, University College Dublin, Belfield Office Park, Dublin 4, Ireland

    Aaron Quigley

  3. Institute of Communications and Navigation, German Aerospace Center, 82234 Wessling/Oberpfaffenhofen, Germany, and Digital Enterprise Research Institute (DERI), University of Innsbruck, 6020, Innsbruck, Austria

    Thomas Strang

  4. Semiconductor Group R&D Division, Sony Corporation, 1-11-1 Osaki, Shinagawa-ku, 141-0032, Tokyo, Japan

    Koji Suginuma

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© 2009 Springer-Verlag Berlin Heidelberg

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Bolliger, P., Partridge, K., Chu, M., Langheinrich, M. (2009). Improving Location Fingerprinting through Motion Detection and Asynchronous Interval Labeling. In: Choudhury, T., Quigley, A., Strang, T., Suginuma, K. (eds) Location and Context Awareness. LoCA 2009. Lecture Notes in Computer Science, vol 5561. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01721-6_3

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  • DOI: https://doi.org/10.1007/978-3-642-01721-6_3

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-01720-9

  • Online ISBN: 978-3-642-01721-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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