No need to war-drive: unsupervised indoor localization

  • Authors:

  • He Wang;Souvik Sen;Ahmed Elgohary;Moustafa Farid;Moustafa Youssef;Romit Roy Choudhury

  • Affiliations:

  • Duke University, Durham, NC, USA;Duke University, Durham, NC, USA;EJUST, Alexandria, Egypt;EJUST, Alexandria, Egypt;EJUST, Alexandria, Egypt;Duke University, Durham, NC, USA

  • Venue:
  • Proceedings of the 10th international conference on Mobile systems, applications, and services
  • Year:
  • 2012

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Abstract

We propose UnLoc, an unsupervised indoor localization scheme that bypasses the need for war-driving. Our key observation is that certain locations in an indoor environment present identifiable signatures on one or more sensing dimensions. An elevator, for instance, imposes a distinct pattern on a smartphone's accelerometer; a corridor-corner may overhear a unique set of WiFi access points; a specific spot may experience an unusual magnetic fluctuation. We hypothesize that these kind of signatures naturally exist in the environment, and can be envisioned as internal landmarks of a building. Mobile devices that "sense" these landmarks can recalibrate their locations, while dead-reckoning schemes can track them between landmarks. Results from 3 different indoor settings, including a shopping mall, demonstrate median location errors of 1:69m. War-driving is not necessary, neither are floorplans the system simultaneously computes the locations of users and landmarks, in a manner that they converge reasonably quickly. We believe this is an unconventional approach to indoor localization, holding promise for real-world deployment.