Eurofuse 2011 pp 363-374 | Cite as

Indoor Location Using Fingerprinting and Fuzzy Logic

  • Pedro Mestre
  • Luís Coutinho
  • Luís Reigoto
  • João Matias
  • Aldina Correia
  • Pedro Couto
  • Carlos Serodio
Part of the Advances in Intelligent and Soft Computing book series (AINSC, volume 107)


Indoor location systems cannot rely on technologies such as GPS (Global Positioning System) to determine the position of a mobile terminal, because its signals are blocked by obstacles such as walls, ceilings, roofs, etc. In such environments the use of alternative techniques, such as the use of wireless networks, should be considered. The location estimation is made by measuring and analysing one of the parameters of the wireless signal, usually the received power. One of the techniques used to estimate the locations using wireless networks is fingerprinting. This technique comprises two phases: in the first phase data is collected from the scenario and stored in a database; the second phase consists in determining the location of the mobile node by comparing the data collected from the wireless transceiver with the data previously stored in the database. In this paper an approach for localisation using fingerprinting based on Fuzzy Logic and pattern searching is presented. The performance of the proposed approach is compared with the performance of classic methods, and it presents an improvement between 10.24% and 49.43%, depending on the mobile node and the Fuzzy Logic parameters.


Mobile Phone Membership Function Fuzzy Logic Mobile Node Access Point 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Audet, C.: Convergence results for pattern search algorithms are tight. Optimization and Engineering 2(5), 101–122 (2004)MathSciNetCrossRefGoogle Scholar
  2. 2.
    Audet, C., Bchard, V., Digabel, S.L.: Nonsmooth optimization through mesh adaptive direct search and variable neighborhood search. J. Global Opt. (41), 299–318 (2008)zbMATHCrossRefGoogle Scholar
  3. 3.
    Audet, C., Dennis Jr., J.E.: Analysis of generalized pattern searches. SIAM Journal on Optimization 13(3), 889–903 (2002)MathSciNetCrossRefGoogle Scholar
  4. 4.
    Audet, C., Dennis Jr., J.E.: Mesh adaptive direct search algorithms for constrained optimization. SIAM Journal on Optimization (17), 188–217 (2006)MathSciNetzbMATHCrossRefGoogle Scholar
  5. 5.
    Audet, C., Dennis Jr., J.E.: A mads algorithm with a progressive barrier for derivative-free nonlinear programming. Tech. Rep. G-2007-37, Les Cahiers du GERAD, cole Polytechnique de Montral (2007)Google Scholar
  6. 6.
    Audet, C., Dennis Jr., J.E., Digabel, S.L.: Globalization strategies for mesh adaptative direct search. Tech. Rep. G-2008-74, Les Cahiers du GERAD, cole Polytechnique de Montral (2008)Google Scholar
  7. 7.
    Bahl, P., Padmanabhan, V.: RADAR: an in-building RF-based user location and tracking system. In: INFOCOM 2000, Proceedings of IEEE Nineteenth Annual Joint Conference of the IEEE Computer and Communications Societies, vol. 2, pp. 775–784 (2000); doi:10.1109/INFCOM.2000.832252Google Scholar
  8. 8.
    Conn, A.R., Scheinberg, K., Vicente, L.N.: Introduction to Derivative-Free Optimization. In: MPS-SIAM Series on Optimization. SIAM, USA (2009)Google Scholar
  9. 9.
    Cricket Project: Cricket v2 User Manual. MIT Computer Science and Artificial Intelligence Lab, Cambridge, ma 02139 edn, 9-11 (2005)Google Scholar
  10. 10.
    Hightower, J., Borriello, G.: Location sensing techniques. Tech. rep., University of Washington, Department of Computer Science and Engineering, Seattle (2001)Google Scholar
  11. 11.
    Jang, J.S.R., Sun, C.T., Mizutani, E.: Neuro-fuzzy and soft computing. In: USENIX Systems Administration Conference (1997)Google Scholar
  12. 12.
    Lin, C.T., Lee, C.S.G.: Neural fuzzy systems: a neuro-fuzzy synergism to intelligent systems. Prentice-Hall, Inc., Upper Saddle River (1996)Google Scholar
  13. 13.
    Liu, H., Darabi, H., Banerjee, P., Liu, J.: Survey of wireless indoor positioning techniques and systems. IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews 37(6), 1067–1080 (2007); doi:10.1109/TSMCC.2007.905750CrossRefGoogle Scholar
  14. 14.
    Mestre, P., Pinto, H., Serodio, C., Monteito, J., Couto, C.: A multi-technology framework for LBS using fingerprinting. In: 35th Annual Conference of IEEE Industrial Electronics, IECON 2009, pp. 2693–2698 (2009)Google Scholar
  15. 15.
    Orr, R.J., Abowd, G.D.: The smart floor: a mechanism for natural user identification and tracking. In: CHI 2000: Extended Abstracts on Human Factors in Computing Systems, pp. 275–276. ACM, New York (2000), CrossRefGoogle Scholar
  16. 16.
    Otsason, V., Varshavsky, A., LaMarca, A., de Lara, E.: Accurate GSM indoor location. In: Mobile Computing, Ubi Comp 2005 (2005)Google Scholar
  17. 17.
    Prasithsangaree, P., Krishnamurthy, P., Chrysanthis, P.: On indoor position location with wireless LANs. In: The 13th IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, vol. 2, pp. 720–724 (2002)Google Scholar
  18. 18.
    Silva, P.M., Paralta, M., Caldeirinha, R., Rodrigues, J., Serodio, C.: Traceme - indoor real-time location system. In: 35th Annual Conference of IEEE Industrial Electronics, IECON 2009, pp. 2721–2725 (2009)Google Scholar
  19. 19.
    Want, R., Hopper, A., Veronica Falc, A., Gibbons, J.: The active badge location system. ACM Trans. Inf. Syst. 10(1), 91–102 (1992), CrossRefGoogle Scholar
  20. 20.
    Ward, A., Jones, A., Hopper, A.: A new location technique for the active office. IEEE Personal Communications 4(5), 42–47 (1997)CrossRefGoogle Scholar
  21. 21.
    Zadeh, L.: Fuzzy sets. Information Control 8, 338–353 (1965)MathSciNetzbMATHCrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Pedro Mestre
    • 1
  • Luís Coutinho
    • 2
  • Luís Reigoto
    • 2
  • João Matias
    • 3
  • Aldina Correia
    • 4
  • Pedro Couto
    • 1
  • Carlos Serodio
    • 1
  1. 1.CITAB-UTADVila RealPortugal
  2. 2.UTADVila RealPortugal
  3. 3.CM-UTADVila RealPortugal
  4. 4.CM-UTAD and CIICESI/ESTGF/IPPFelgueirasPortugal

Personalised recommendations