Advertisement

Offline Beacon Selection-Based RSSI Fingerprinting for Location-Aware Shopping Assistance: A Preliminary Result

  • Wan Mohd Yaakob Wan BejuriEmail author
  • Mohd Murtadha Mohamad
  • Raja Zahilah Raja Mohd Radzi
Part of the Studies in Computational Intelligence book series (SCI, volume 598)

Abstract

The location determination in an obstructed area can be extremely challenging particularly when the Global Positioning System (GPS) is blocked. When this happens, users will encounter difficulty in navigating directly on-site, especially within an indoor environment. Occasionally, there is a need to integrate with other sensors in order to establish the location with greater intelligence, reliability, and ubiquity. The use of positioning integration may be useful since it involves as many beacons as necessary to determine positioning. However, the implementation of the integration in the mobile devices platform may lead high computation which in turn could increase power consumption. In this paper, an offline beacon selection-based RSSI fingerprinting is proposed in order to lessen the computation task during the location determination process, as it may cause huge power consumption in mobile devices. By reducing the number of beacons that will be processed, the number of RSSI fingerprinting searches of the location in the spatial database also reduced. Lastly, the preliminary results are presented to illustrate the performance of an indoor environment set-up.

Keywords

Global Navigation System Wireless LAN and Beacon Selection 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Othmane, L.B., Weffers, H., Ranchal, R., Angin, P., Bhargava, B., Mohamad, M.M.: A Case for Societal Digital Security Culture. In: Janczewski, L.J., Wolfe, H.B., Shenoi, S. (eds.) SEC 2013. IFIP Advances in Information and Communication Technology, vol. 405, pp. 391–404. Springer, Heidelberg (2013)CrossRefGoogle Scholar
  2. 2.
    Kheirabadi, M.T., Mohamad, M.M.: Greedy Routing in Underwater Acoustic Sensor Networks: A Survey. International Journal of Distributed Sensor Networks, 2013, Article ID 701834, pages (2013)Google Scholar
  3. 3.
    Schougaard, K.R., Grønbæk, K., Scharling, T.: Indoor Pedestrian Navigation Based on Hybrid Route Planning and Location Modeling. In: Kay, J., Lukowicz, P., Tokuda, H., Olivier, P., Krüger, A. (eds.) Pervasive 2012. LNCS, vol. 7319, pp. 289–306. Springer, Heidelberg (2012)CrossRefGoogle Scholar
  4. 4.
    Roth, S.P., Tuch, A.N., Mekler, E.D., Bargas-Avila, J.A., Opwis, K.: Location Matters, Especially for Non-Salient Features–An Eye-Tracking Study on the Effects of Web Object Placement on Different Types of Websites. International Journal Human-Computer Studies 71(3), 228–235 (2013)CrossRefGoogle Scholar
  5. 5.
    Yang, X.M., Li, X.Y.: Research on Data Preprocessing Technology in Location Based Service. Advanced Materials Research 740, 134–139 (2013)CrossRefGoogle Scholar
  6. 6.
    Kourogi, M., Sakata, N., Okuma, T., Kurata, T.: Indoor/Outdoor Pedestrian Navigation with an Embedded GPS/RFID/Self-contained Sensor System. In: Pan, Z., Cheok, D.A.D., Haller, M., Lau, R., Saito, H., Liang, R. (eds.) ICAT 2006. LNCS, vol. 4282, pp. 1310–1321. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  7. 7.
    Schmidt, A., Fularz, M., Kraft, M., Kasiński, A., Nowicki, M.: An Indoor RGB-D Dataset for the Evaluation of Robot Navigation Algorithms. In: Blanc-Talon, J., Kasinski, A., Philips, W., Popescu, D., Scheunders, P. (eds.) ACIVS 2013. LNCS, vol. 8192, pp. 321–329. Springer, Heidelberg (2013)CrossRefGoogle Scholar
  8. 8.
    Evennou, F., Marx, F.: Advanced Integration of WiFi and Inertial Navigation Sys-tems for Indoor Mobile Positioning. EURASIP Journal on Applied Signal Processing 2006, 164–164 (2006)Google Scholar
  9. 9.
    Popleteev, A.: Indoor positioning using FM radio signals. University of Trento (2011)Google Scholar
  10. 10.
    Wu, Y., Pan, X.: Velocity/Position Integration Formula Part I: Application to In-Flight Coarse Alignment. IEEE Transactions on Aerospace and Electronic Systems 49(2), 1006–1023 (2013)CrossRefGoogle Scholar
  11. 11.
    Fang, S.-H., Wang, C.-H., Chiou, S.-M., Lin, P.: Calibration-Free Approaches for Robust Wi-Fi Positioning against Device Diversity: A Performance Comparison. In: 75th IEEE Vehicular Technology Conference, pp. 1–5. IEEE Press, New York (2012)Google Scholar
  12. 12.
    Bejuri, W.M.Y.W., Saidin, W.M.N.W.M., Bin Mohamad, M.M., Sapri, M., Lim, K.S.: Ubiquitous Positioning: Integrated GPS/Wireless LAN Positioning for Wheelchair Navigation System. In: Selamat, A., Nguyen, N.T., Haron, H. (eds.) ACIIDS 2013, Part I. LNCS, vol. 7802, pp. 394–403. Springer, Heidelberg (2013)CrossRefGoogle Scholar
  13. 13.
    Bejuri, W.M.Y.W., Mohamad, M.M.: Performance Analysis of Grey-World-based Feature Detection and Matching for Mobile Positioning Systems. Sensing & Imaging 15(1), 1–24 (2014)CrossRefGoogle Scholar
  14. 14.
    Bejuri, W.M.Y.W., Mohamad, M.M., Sapri, M., Rosly, M.A.: Ubiquitous WLAN/Camera Positioning using Inverse Intensity Chromaticity Space-based Feature Detection and Matching: A Preliminary Result. ArXiv Prepr. ArXiv12042294, 2012. In: International Conference on Man-Machine Systems, UniMAP, Penang (2012)Google Scholar
  15. 15.
    Bejuri, W.M.Y.W., Mohamad, M.M., Sapri, M., Rosly, M.A.: Performance Evaluation of Mobile U-Navigation Based on GPS/WLAN Hybridization. Journal of Convergence Information Technology 7(12), 235–246 (2012)CrossRefGoogle Scholar
  16. 16.
    Bejuri, W.M.Y.W., Mohamad, M.M., Sapri, M., Rosly, M.A.: Investigation of color constancy for ubiquitous wireless LAN/Camera positioning: an initial outcome. International Journal of Advancements in Computing Technology 4(7), 269–280 (2012)CrossRefGoogle Scholar
  17. 17.
    Bejuri, W.M.Y.W., Mohamad, M.M., Sapri, M., Rahim, M.S.M., Chaudry, J.A.: Performance Evaluation of Spatial Correlation-based Feature Detection and Matching for Automated Wheelchair Navigation System. International Journal of Intelligent Transportation Systems Research 12(1), 9–19 (2014)CrossRefGoogle Scholar
  18. 18.
    Bejuri, W.M.Y.W., Mohamad, M.M., Sapri, M.: Ubiquitous positioning: A taxonomy for location determination on mobile navigation system. Signal & Image Processing: An International Journal (SIPIJ) 2(1), 24–34 (2011)Google Scholar
  19. 19.
    Bejuri, W.M.Y.W., Mohamad, M.M.: Wireless LAN/FM Radio-based Robust Mobile Indoor Positioning: An Initial Outcome. International Journal of Software Engineering & Its Applications 8(2) (2014)Google Scholar
  20. 20.
    Narzullaev, A., Park, Y., Yoo, K., Yu, J.: A Fast and Accurate Calibration Algo-rithm for Real-Time Locating Systems Based on The Received Signal Strength Indica-tion. AEU - International Journal of Electronics and Communications 65(4), 305–311 (2011)CrossRefGoogle Scholar
  21. 21.
    Chen, Y., Yang, Q., Yin, J., Chai, X.: Power-efficient access-point selection for indoor location estimation. IEEE Transactions Knowledge Data Engineering 18(7), 877–888 (2006)CrossRefGoogle Scholar
  22. 22.
    Laoudias, C., Michaelides, M.P., Panayiotou, C.G.: Fault detection and mitigation in WLAN RSS fingerprint-based positioning. Journal of Location Based Services 6(2), 101–116 (2012)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Wan Mohd Yaakob Wan Bejuri
    • 1
    • 2
    Email author
  • Mohd Murtadha Mohamad
    • 1
  • Raja Zahilah Raja Mohd Radzi
    • 1
  1. 1.Faculty of ComputingUniversiti Teknologi MalaysiaJohor BahruMalaysia
  2. 2.Faculty of Information and Communication TechnologyUniversiti Teknikal MalaysiaMelakaMalaysia

Personalised recommendations