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| Content Provider | ACM Digital Library |
|---|---|
| Author | Choudhury, Romit Roy Farid, Moustafa Wang, He Elgohary, Ahmed Sen, Souvik Youssef, Moustafa |
| 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. |
| Starting Page | 197 |
| Ending Page | 210 |
| Page Count | 14 |
| File Format | |
| ISBN | 9781450313018 |
| DOI | 10.1145/2307636.2307655 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2012-06-25 |
| Publisher Place | New York |
| Access Restriction | Subscribed |
| Subject Keyword | Mobile phones Landmarks Sensing Recursion Location |
| Content Type | Text |
| Resource Type | Article |
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