No need to war-drive: unsupervised indoor localization


We propose <i>UnLoc</i>, 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 <i>landmarks</i> 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 1:69<i>m</i>. 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.

DOI: 10.1145/2307636.2307655

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@inproceedings{Wang2012NoNT, title={No need to war-drive: unsupervised indoor localization}, author={He Wang and Souvik Sen and Ahmed Elgohary and Moustafa Farid and Moustafa Youssef and Romit Roy Choudhury}, booktitle={MobiSys}, year={2012} }