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Estimating Common Pedestrian Routes through Indoor Path Networks using Position Traces

Research output: Contribution to book/anthology/report/proceedingArticle in proceedingsResearchpeer-review



  • Thor Siiger Prentow, Denmark
  • Henrik Blunck, Denmark
  • Kaj Grønbæk
  • Mikkel Baun Kjærgaard, Denmark
Abstract—Accurate information about how people commonly
travel in a given large-scale building environment and which
routes they take for given start and destination points is essential
for applications such as indoor navigation, route prediction,
and mobile work planning and logistics. In this paper, we
propose methods for detecting commonly used routes by robust
aggregation, clustering, and merging of indoor position traces.
The developed methods overcome three specific challenges for
detecting commonly used routes in an indoor setting based on position
data: i) a high ratio between path-density and positioningaccuracy,
ii) a flat path hierarchy, and iii) providing cost-effective
scalability. Through an evaluation based on data collected by staff
members at a hospital covering more than 10 hectare over three
floors, we show that the proposed methods detect routes that are
representative of the commonly used routes between locations.
These methods are sufficiently efficient to provide common routes
based on real-time data from thousands of devices simultaneously.
Furthermore, we show that the methods operate robustly even on
basis of noisy and coarse-grained position estimates as provided
by large-scale deployable indoor Wi-Fi positioning systems, and
with no prior information on building layout.
Original languageEnglish
Title of host publication15th IEEE International Conference on Mobile Data Management : Proceedings
EditorsMohammad Gaber, Rui Zhang
Number of pages6
PublisherIEEE Press
Publication year2014
Pages43-48 (vol.1)
ISBN (print)9781479957057
Publication statusPublished - 2014
EventInternational Conference on Mobile Data Management - Brisbane, Australia
Duration: 15 Jul 201418 Jul 2014


ConferenceInternational Conference on Mobile Data Management
SeriesI E E E International Conference on Mobile Data Management. Proceedings

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