Feasibility of WiFi Site-Surveying Using Crowdsourced Data

  • Sylvain Leirens
  • Christophe Villien
  • Bruno Flament
Conference paper
First Online:
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10169)

Abstract

Pedestrian dead reckoning (PDR) trajectories suffer from a significant amount of drift over time, especially when relying on low-cost commercial sensors. For indoor positioning, high level fusion algorithms refine trajectories thanks to kind of map information: e.g. WiFi fingerprinting, and blue prints. Map availability is then of great concern for efficient use of positioning algorithms in practical situations, and could rely on crowdsourced data, i.e. big quantities of data shared by users. In this paper, crowdsourced data include uncertain estimated positions and noisy RSSI (Received Signal Strength Indicator) measurements in order to estimate the spatial distribution of RSSI levels. Using a simple model for a PDR trajectory, we study how a WiFi map can be derived. Simulation results on a corridor use-case illustrate the approach.

Keywords

Crowdsourcing Site survey Pedestrian dead reckoning 
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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Sylvain Leirens
    • 1
  • Christophe Villien
    • 1
  • Bruno Flament
    • 2
  1. 1.Comissariat à l’Énergie Atomique et aux Énergies AlternativesGrenoble CedexFrance
  2. 2.InvenSenseGrenobleFrance

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