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Geo Referenced Dynamic Bayesian Networks for User Positioning on Mobile Systems

  • Boris Brandherm
  • Tim Schwartz
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3479)

Abstract

The knowledge of the position of a user is valuable for a broad range of applications in the field of pervasive computing. Different techniques have been developed to cope with the problem of uncertainty, noisy sensors, and sensor fusion.

In this paper we present a method, which is efficient in time- and space-complexity, and that provides a high scalability for in- and outdoor-positioning. The so-called geo referenced dynamic Bayesian networks enable the calculation of a user’s position on his own small hand-held device (e.g., Pocket PC) without a connection to an external server. Thus, privacy issues are considered and completely in the hand of the user.

Keywords

Bayesian Network Time Slice Pervasive Computing Sensor Fusion Dynamic Bayesian Network 
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 2005

Authors and Affiliations

  • Boris Brandherm
    • 1
  • Tim Schwartz
    • 1
  1. 1.Department of Computer ScienceSaarland UniversitySaarbrückenGermany

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