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LuxTrace - indoor positioning using building illumination

Julian Randall, Oliver Amft, Jürgen Bohn, and Martin Burri. LuxTrace - indoor positioning using building illumination. Personal Ubiquitous Comput, 11(6):417–428, August 2007.

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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.

BibTeX

@ARTICLE{Randall2007-J_PUC,
  author = {Julian Randall and Oliver Amft and J\"urgen Bohn and Martin Burri},
  title = {LuxTrace - indoor positioning using building illumination},
  journal = {Personal Ubiquitous Comput},
  year = {2007},
  volume = {11},
  pages = {417--428},
  number = {6},
  month = {August},
  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.},
  doi = {10.1007/s00779-006-0097-0},
  file = {Randall2007-J_PUC.pdf:Randall2007-J_PUC.pdf:PDF},
  owner = {oam},
  timestamp = {2007/03/15}
}

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