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Personal and Ubiquitous Computing

, Volume 11, Issue 6, pp 417–428 | Cite as

LuxTrace: indoor positioning using building illumination

  • Julian RandallEmail author
  • Oliver Amft
  • Jürgen Bohn
  • Martin Burri
Original Article

Abstract

Tracking location is challenging due to the numerous constraints of practical systems including, but not limited to global cost, device volume and weight, scalability and accuracy; these constraints are typically more severe for systems that should be wearable and used indoors. We investigate the use of wearable solar cells to track changing light conditions (a concept that we named LuxTrace) as a source of user displacement and activity data. We evaluate constraints of this approach and present results from an experimental validation of displacement and activity estimation. The results indicate that a distance estimation accuracy of 21 cm (80% quantile) can be achieved. A simple method to combine LuxTrace with complementary absolute location estimation methods is also presented. We apply carpet-like distributed RFID tags to demonstrate online learning of new lighting environments.

Keywords

Solar Cell Radiant Intensity Combine System Solar Module Displacement Estimation 
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 London Limited 2007

Authors and Affiliations

  • Julian Randall
    • 1
    Email author
  • Oliver Amft
    • 1
  • Jürgen Bohn
    • 2
  • Martin Burri
    • 1
  1. 1.Wearable Computing LabETH ZürichSwitzerland
  2. 2.Institute for Pervasive ComputingETH ZürichSwitzerland

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