Acta Univ. Agric. Silvic. Mendelianae Brun. 2018, 66(6), 1565-1571 | DOI: 10.11118/actaun201866061565

Wi-Fi Indoor Localisation: a Deeper Insight Into Patterns in the Fingerprint Map Data

Mikuláš Muroň, David Procházka
Department of Informatics, Faculty of Business and Economics, Mendel University in Brno, Zemědělská 1, 613 00 Brno, Czech Republic

Localisation via Wi-Fi networks is one of the possible techniques which can be used for positioning inside buildings or in other places without the GPS signal. The accurate indoor positioning system can help users with localisation or navigation within unfamiliar places. Almost all buildings are covered with the Wi-Fi signal. Using the currently existing infrastructure will minimise cost for construction other types of indoor positioning systems. Among other reasons, usage of Wi-Fi for positioning is also convenient because almost every mobile device has a Wi-Fi capability and therefore the system can be easily used by everyone. However, an important factor is the precision of such a solution. The article is focused on the evaluation of Wi-Fi localisation precision within the university grounds.

Keywords: Wi-Fi indoor localization, Wi-Fi navigation
Grants and funding:

This work was supported by grant IGA FBE_TP_2017006 (SmartPEF: smart faculty).

Published: December 19, 2018  Show citation

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Muroň, M., & Procházka, D. (2018). Wi-Fi Indoor Localisation: a Deeper Insight Into Patterns in the Fingerprint Map Data. Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis66(6), 1565-1571. doi: 10.11118/actaun201866061565
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References

  1. BAHL, P. and PADMANABHAN, V. N. 2000. RADAR: an in-building RF-based user location and tracking system. In: Proceedings IEEE INFOCOM 2000. Conference on Computer Communications. 26 - 30 March 2000, Tel Aviv, Israel, pp. 775-784.
  2. BOLLIGER, P. 2008. Redpin - Adaptive, Zero-configuration Indoor Localization Through User Collaboration. In: Proceedings of the First ACM International Workshop on Mobile Entity Localization and Tracking in GPS-less Environments (MELT '08). San Francisco, California, USA - September 19, 2008, pp. 55-60. Go to original source...
  3. MURON, M. 2014. Building Wi-Fi based indoor geolocation system for Android. In: PEFnet - European scientific conference of doctoral students. Mendel University in Brno.
  4. RAHMAN, M., HABIBI, D. and AHMAD, I. 2008. Source localisation in wireless sensor networks based on optimised maximum likelihood. In: Telecommunication Networks and Applications Conference. ATNAC 2008. Adelaide, Australia: IEEE Press, pp. 235-239. Go to original source...
  5. SO, J. 2013. An improved location estimation method for wifi fingerprint-based indoor localization. International Journal of Software Engineering and Its Applications, 7(3): 77-86.
  6. ZANCA, G., ZORZI, F., ZANELLA, A. and ZORZI, M. 2008. Experimental Comparison of RSSI-based Localization Algorithms for Indoor Wireless Sensor Networks. In: Proceedings of the Workshop on Real-world Wireless Sensor Networks (REALWSN '08). ACM, New York, NY, USA, pp. 1-5. Go to original source...
  7. ZHU, X. and FENG, Y. 2013. RSSI-based Algorithm for Indoor Localization. Communications and Network. 5.02: 37. DOI: 10.4236/cn.2013.52B007 Go to original source...

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