To construct a WiFi positioning system, dedicated individuals usually gather radio scans with ground truth data. This laborious operation limits the widespread use of WiFi-based locating system. Off-the-shelf smartphones have the capability to scan radio signals from WiFi Access Points (APs). In this paper we propose a scheme to construct a map of WiFi AP positions autonomously without ground truth information. From radio scans, we extract dissimilarities between pairs of WiFi APs, then analyze the dissimilarities to produce a geometric configuration of WiFi APs based on a multidimensional scaling technique. To validate our scheme, we conducted experiments on five floors of an office building that has an area of 50 m by 35 m in each floor. WiFi APs were located within a 10m error range, and floors of APs are recognized without error.
|Title of host publication||Pervasive Computing - 9th International Conference, Pervasive 2011, Proceedings|
|Number of pages||18|
|Publication status||Published - 2011|
|Event||9th International Conference on Pervasive Computing, Pervasive 2011 - San Francisco, CA, United States|
Duration: 2011 Jun 12 → 2011 Jun 15
|Name||Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)|
|Other||9th International Conference on Pervasive Computing, Pervasive 2011|
|City||San Francisco, CA|
|Period||11/6/12 → 11/6/15|
Bibliographical noteFunding Information:
This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MEST) (No.2010-0000405).
Acknowledgments. This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MEST) (No.2010-0000405).
All Science Journal Classification (ASJC) codes
- Theoretical Computer Science
- Computer Science(all)