Growing an organic indoor location system

  • Authors:

  • Jun-geun Park;Ben Charrow;Dorothy Curtis;Jonathan Battat;Einat Minkov;Jamey Hicks;Seth Teller;Jonathan Ledlie

  • Affiliations:

  • MIT CSAIL, Cambridge, MA, USA;MIT CSAIL, Cambridge, MA, USA;MIT CSAIL, Cambridge, MA, USA;MIT CSAIL, Cambridge, MA, USA;Nokia Research, Cambridge, MA, USA;Nokia Research, Cambridge, MA, USA;MIT CSAIL, Cambridge, MA, USA;Nokia Research, Cambridge, MA, USA

  • Venue:
  • Proceedings of the 8th international conference on Mobile systems, applications, and services
  • Year:
  • 2010

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Abstract

Most current methods for 802.11-based indoor localization depend on surveys conducted by experts or skilled technicians. Some recent systems have incorporated surveying by users. Structuring localization systems "organically," however, introduces its own set of challenges: conveying uncertainty, determining when user input is actually required, and discounting erroneous and stale data. Through deployment of an organic location system in our nine-story building, which contains nearly 1,400 distinct spaces, we evaluate new algorithms for addressing these challenges. We describe the use of Voronoi regions for conveying uncertainty and reasoning about gaps in coverage, and a clustering method for identifying potentially erroneous user data. Our algorithms facilitate rapid coverage while maintaining positioning accuracy comparable to that achievable with survey-driven indoor deployments.