Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 30234
An Enhanced Floor Estimation Algorithm for Indoor Wireless Localization Systems Using Confidence Interval Approach

Authors: Kriangkrai Maneerat, Chutima Prommak

Abstract:

Indoor wireless localization systems have played an important role to enhance context-aware services. Determining the position of mobile objects in complex indoor environments, such as those in multi-floor buildings, is very challenging problems. This paper presents an effective floor estimation algorithm, which can accurately determine the floor where mobile objects located. The proposed algorithm is based on the confidence interval of the summation of online Received Signal Strength (RSS) obtained from the IEEE 802.15.4 Wireless Sensor Networks (WSN).We compare the performance of the proposed algorithm with those of other floor estimation algorithms in literature by conducting a real implementation of WSN in our facility. The experimental results and analysis showed that the proposed floor estimation algorithm outperformed the other algorithms and provided highest percentage of floor accuracy up to 100% with 95-percent confidence interval.

Keywords: floor estimation algorithm, floor determination, multi-floor building, indoor wireless systems

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1093870

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2682

References:


[1] G. Yanying, A. Lo, and I. Niemegeers, "A survey of indoor positioning systems for wireless personal networks,” IEEE Communications Surveys & Tutorials, vol. 11, pp. 13–32, Mar. 2009.
[2] S. Gansemer, U. Grossmann, and S. Hakobyan, "RSSI-based euclidean distance algorithm for indoor positioning adapted for the use in dynamically changing WLAN environments and multi-level buildings,” in2010 Int. Conf. Indoor Positioning and Indoor Navigation, pp. 1–6.
[3] L. Hung-Huan and Y. Yu-Non, "WiFi-based indoor positioning for multi-floor Environment,” in 2011 IEEE Region 10 Conf. TENCON, pp. 597–601.
[4] A. S. Al-Ahmadi, T. A. Rahman, M. R. Kamarudin, M. H. Jamaluddin, and A. I. Omer, "Single-phase wireless LAN based multi-floor indoor location determination system,” in2011 IEEE 17th Int. Conf. Parallel and Distributed Systems, pp. 1057–1062.
[5] N. Marques, F. Meneses, and A. Moreira, "Combining similarity functions and majority rules for multi-building, multi-floor, WiFi positioning,” in2012Int. Conf. Indoor Positioning and Indoor Navigation, pp. 1–9.
[6] U. Ruppel, K. M. Stubbe, and U.Z winger, "Indoor navigation integration platform for firefighting purposes,” in 2010Int. Conf. Indoor Positioning and Indoor Navigation, pp. 1–6.
[7] IEEE Std 802.15.4e-2012, "IEEE standard for local and metropolitan area networks-part 15.4: Low-Rate Wireless Personal Area Networks (LR-WPANs),”IEEE Standards, Sept. 2011, pp. 1–314.
[8] G. Mao, B. Fidan, and B.D.O. Anderson, "Wireless sensor network localization techniques,” Computer Networks, vol. 51, pp. 2529–2553, July 2007.
[9] M. Bal, H. Xue, W. Shen, and H. Ghenniwa, "A 3-D indoor location tracking and visualization system based on wireless sensor networks,” in 2010 IEEE Int. Conf. Systems Man and Cybernetics, pp. 1584–1590.
[10] F. Alsehly, T. Arslan, and Z. Sevak, "Indoor positioning with floor determination in multi story buildings,”in 2011Int. Conf. Indoor Positioning and Indoor Navigation, pp. 1–7.
[11] K. Maneerat, C. Prommak, and K. Kaemarungsi, "Floor estimation algorithm for indoor multi-story positioning system using IEEE 802.15.4 network,” in 2014 Int. Conf. Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology, to be published.
[12] R. K. Jain,The Art of Computer Systems Performance Analysis: Techniques for Experimental Design, Measurement, Simulation, and Modeling. Wiley- Interscience, New York, 1991, pp. 213–215.