Inferring Locations of Mobile Devices from Wi-Fi Data
- 1 Faculty of Engineering and Applied Science, University of Ontario Institute of Technology, Oshawa, Canada
- 2 Faculty of Engineering and Applied Science, University of Ontario Institute of Technology, Oshawa, Canada
Abstract
Mobile phones are becoming a primary platform for information access. A major aspect of ubiquitous computing is context-aware applications which collect information about the environment that the user is in and use this information to provide better service and improve user experience. Location awareness makes certain applications possible, e.g., recommending nearby businesses and tracking estimated routes. An Android application is able to collect useful Wi-Fi information without registering a location listener with a network-based provider. We passively collected the data of the IDs of Wi-Fi access points and the received signal strengths. We developed and implemented an algorithm to analyse the data; and designed heuristics to infer the location of the device over time—all without ever connecting to the network thus maximally preserving the privacy of the user.
- Lock (2013) Documentation on the java.util.concurrent.locks.Lockclass. http://developer.android.com/reference/java/util/concurrent/locks/Lock.html
- Schilit, B.N., Adams, N. and Want, R. (1994) Context-Aware Computing Applications. 1st Workshop on Mobile Computing Systems and Applications, IEEE, WMCSA 1994, 85-90.
- Castro, P., et al. (2001) A Probabilistic Room Location Service for Wireless Networked Environments. Ubicomp 2001: Ubiquitous Computing. Springer Berlin Heidelberg, Berlin.
- Bahl, P. and Padmanabhan, V.N. (2000) RADAR: An In-Building RF-Based User Location and Tracking System. INFOCOM 2000, 19th Annual Joint Conference of the IEEE Computer and Communications Societies. Proceedings of IEEE, 2, 775-784.
- Yang, J. and Chen, Y.Y. (2009) Indoor Localization Using Improved rss-Based Lateration Methods. Global Telecommunications Conference, GLOBECOM 2009, Honolulu, 1-6.
- Gwon, Y., Jain, R. and Kawahara, T. (2004) Robust Indoor Location Estimation of Stationary and Mobile Users. INFOCOM 2004, 23rd Annual Joint Conference of the IEEE Computer and Commu-nications Societies, Hongkong, 1032-1043.
- Small, J., et al. (2000) Determining a User Location for Context Aware Computing through the Use of a Wireless LAN Infrastructure. Project Aura Report. http://www.cs.cmu.edu/~aura/docdir/small00.pdf
- Grossmann, U., Schauch, M. and Hakobyan, S. (2007) RSSI Based WLAN Indoor Positioning with Personal Digital Assistants. Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications, 2007. 4th IEEE Workshop on IDAACS, Dortmund, 653-656.
- Ladd, A.M., et al. (2005) Robotics-Based Location Sensing Using Wireless Ethernet. Wireless Net-works, 11, 189-204.
- Retscher, G., et al. (2006) Performance and Accuracy Test of the WLAN Indoor Positioning System “ipos”. Proceedings of the 3rd Workshop on Positioning, Navigation and Communication, University of Hanover, Germany.
- Teuber, A. and Eissfeller, B. (2006) WLAN Indoor Positioning Based on Euclidean Distances and Fuzzy Logic. Proceedings of the 3rd Workshop on Positioning, Navigation and Communication, University of Hanover, Germany, 159-168.
- Quan, M., Navarro, E. and Peuker, B. (2010) Wi-Fi Localization Using RSSI Fingerprinting. California Polytechnic Uni- versity, Technical Report.
- Prasithsangaree, P., Krishnamurthy, P. and Chrysanthis, P.K. (2002) On Indoor Position Location with Wireless LANs. Proceedings of the 13th IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, Lisbon, 15-18 September 2002, 720-724.