Wi-Fi positioning system

Wi-Fi positioning system (WPS, WiPS or WFPS) is a geolocation system that uses the characteristics of nearby Wi‑Fi access points to discover where a device is located.[1]

It is used where satellite navigation such as GPS is inadequate due to various causes including multipath and signal blockage indoors, or where acquiring a satellite fix would take too long. [2] Such systems include assisted GPS, urban positioning services through hotspot databases, and indoor positioning systems.[3] Wi-Fi positioning takes advantage of the rapid growth in the early 21st century of wireless access points in urban areas.[4]

The most common technique for positioning using wireless access points is based on a rough proxy for the strength of the received signal (received signal strength indicator, or RSSI) and the method of "fingerprinting".[5][6][7] Typically a wireless access point is identified by its SSID and MAC address, and these data are compared to a database of supposed locations of access points so identified. The accuracy depends on the accuracy of the database (e.g. if an access point has moved its entry is inaccurate), and the precision depends on the number of discovered nearby access points with (accurate) entries in the database and the precisions of those entries. The access point location database gets filled by correlating mobile device location data (determined by other systems, such as Galileo or GPS) with Wi‑Fi access point MAC addresses.[8] The possible signal fluctuations that may occur can increase errors and inaccuracies in the path of the user. To minimize fluctuations in the received signal, there are certain techniques that can be applied to filter the noise.

In the case of low precision, some techniques have been proposed to merge the Wi-Fi traces with other data sources such as geographical information and time constraints (i.e., time geography).[9]

  1. ^ Lindner, Thomas; Fritsch, Lothar; Plank, Kilian; Rannenberg, Kai (2004). Lamersdorf, Winfried; Tschammer, Volker; Amarger, Stéphane (eds.). "Exploitation of Public and Private WiFi Coverage for New Business Models". Building the E-Service Society. IFIP International Federation for Information Processing. 146. Springer US: 131–148. doi:10.1007/1-4020-8155-3_8. ISBN 978-1-4020-8155-2.
  2. ^ Magda Chelly, Nel Samama. Detecting visibility in heterogeneous simulated environments for positioning purposes. IPIN 2010 : International Conference on Indoor Positioning and Indoor Navigation, Sep 2010, Hoenggerberg, Switzerland. ⟨hal-01345039⟩ [1]
  3. ^ Magda Chelly, Nel Samama. New techniques for indoor positioning, combining deterministic and estimation methods. ENC-GNSS 2009 : European Navigation Conference - Global Navigation Satellite Systems, May 2009, Naples, Italy. pp.1 - 12. hal-01367483 [2]
  4. ^ Magda Chelly, Anca Fluerasu, Nel Samama. A universal and autonomous positioning system based on wireless networks connectivity. ENC 2011 : European Navigation Conference, Nov 2011, London, United Kingdom. hal-01302215[3]
  5. ^ P. Bahl and V. N. Padmanabhan, “RADAR: an in-building RF-based user location and tracking system,” in Proceedings of 19th Annual Joint Conference of the IEEE Computer and Communications Societies (INFOCOM ’00), vol. 2, pp. 775–784, Tel Aviv.Israel, March 2000.
  6. ^ Y. Chen and H. Kobayashi, “Signal strength based indoor geolocation,” in Proceedings of the IEEE International Conference on Communications (ICC ’02), vol. 1, pp. 436–439, New York, NY, USA, April–May 2002.
  7. ^ Youssef, M. A.; Agrawala, A.; Shankar, A. Udaya (2003-03-01). "WLAN location determination via clustering and probability distributions". Proceedings of the First IEEE International Conference on Pervasive Computing and Communications, 2003. (PerCom 2003). pp. 143–150. CiteSeerX 10.1.1.13.4478. doi:10.1109/PERCOM.2003.1192736. ISBN 978-0-7695-1893-0. S2CID 2096671.
  8. ^ "Wi-Fi Positioning System". Archived from the original on 2014-12-19. Retrieved 2014-12-19.
  9. ^ Danalet, Antonin; Farooq, Bilal; Bierlaire, Michel (2014). "A Bayesian approach to detect pedestrian destination-sequences from WiFi signatures". Transportation Research Part C: Emerging Technologies. 44: 146–170. Bibcode:2014TRPC...44..146D. doi:10.1016/j.trc.2014.03.015.