Automatic Mitigation of Sensor Variations for Signal Strength Based Location Systems

  • Mikkel Baun Kjærgaard
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3987)


In the area of pervasive computing a key concept is context-awareness. One type of context information is location information of wireless network clients. Research in indoor localization of wireless network clients based on signal strength is receiving a lot of attention. However, not much of this research is directed towards handling the issue of adapting a signal strength based indoor localization system to the hardware and software of a specific wireless network client, be it a tag, PDA or laptop. Therefore current indoor localization systems need to be manually adapted to work optimally with specific hardware and software. A second problem is that for a specific hardware there will be more than one driver available and they will have different properties when used for localization. Therefore the contribution of this paper is twofold. First, an automatic system for evaluating the fitness of a specific combination of hardware and software is proposed. Second, an automatic system for adapting an indoor localization system based on signal strength to the specific hardware and software of a wireless network client is proposed. The two contributions can then be used together to either classify a specific hardware and software as unusable for localization or to classify them as usable and then adapt them to the signal strength based indoor localization system.


Signal Strength Period Analyzer Pervasive Computing Sensor Variation Average Likelihood 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Mikkel Baun Kjærgaard
    • 1
  1. 1.Department of Computer ScienceUniversity of AarhusAarhus NDenmark

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