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Adequate RSSI Determination Method by Making Use of SVM for Indoor Localization

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Book cover Knowledge-Based Intelligent Information and Engineering Systems (KES 2006)

Abstract

Context-aware computing that recognizes the context in which a user performs a task is one of the most important techniques for supporting user activity in ubiquitous computing. To realize context-aware computing, a computer needs to recognize the user’s location. This paper describes a technique for location detection inside a room using radio waves from a user’s computer. The proposed technique has to be sufficiently robust to cater for dynamic environments and should require only ordinary network devices, such as radio signal emitters, without the need for special equipment. We propose performing localization by relative values of RSSI (Received Signal Strength Indicator) among wireless nodes. Furthermore, we use SVM (Support Vector Machine) to find the criteria for classification (whether a node is inside or outside a given area), in the case where absolute RSSI values are used for localization.

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References

  1. Schilit, B., Adams, N., Want, R.: Context-Aware Computing Applications. In: IEEE Workshop on Mobile Computing Systems and Applications, Santa Cruz, CA, US (1994)

    Google Scholar 

  2. Harter, A., Hopper, A., Steggles, P., Ward, A., Webster, P.: The Anatomy of a Context-Aware Application. In: Proceedings of the Fifth Annual ACM/IEEE International Conference on Mobile Computing and Networking (MobiCom 1999), Seattle, Washington, USA, August 1999, pp. 59–68 (1999)

    Google Scholar 

  3. Priyantha, N.B., Chakraborty, A., Balakrishnan, H.: The Cricket location-support system. In: The 6th Annual ACM/IEEE International Conference on Mobile Computing and Networking (MobiCom 2000), Boston, MA, USA, August 2000, pp. 32–43 (2000)

    Google Scholar 

  4. http://www.tinyos.net/

  5. Iwaya, A., Nishio, N., Murase, M., Tokuda, H.: GOMASHIO: Proximity Based Localization In Wireless Ad-Hoc Sensor Networks. IPSJ SIG Mobile Computing and Ubiquitous Networking 108, 23–30 (2001) (in Japanese)

    Google Scholar 

  6. Kitasuka, T., Nakanishi, T., Fukuda, A.: Wireless LAN based Indoor Positioning System WiPS and Its Simulation. In: IEEE Pacific Rim Conference on Com-munications, Computers and Signal Processing (PACRIM 2003), August 2003, pp. 272–275 (2003)

    Google Scholar 

  7. Bulusu, N., Heidemann, J., Estrin, D.: GPS-less Low Cost Outdoor Localization for Very Small Devices. IEEE Personal Communications Magazine 7(5), 28–34 (2000)

    Article  Google Scholar 

  8. Ganesan, D., Estrin, D., Woo, A., Culler, D.: Complex Behavior at Scale: An Experimental Study of Low-Power Wireless Sensor Networks, Technical Report UCLA/CSD-TR 02-0013 (2002)

    Google Scholar 

  9. Ogawa, T., Yoshino, S., Shimizu, M.: The In-door Location Determination Method Using Learning Algorithms with Wireless Active Tags. IPSJ Ubiquitous Computing Systems (UBI) 2004(66), 31–38 (2004) (in Japanese)

    Google Scholar 

  10. He, T., Huang, C., Blum, B.M., Stankovic, J.A., Abdelzaher, T.F.: Range-Free Localization Schemes in Large Scale Sensor Networks. In: The Ninth Annual International Conference on Mobile Computing and Networking (MobiCom 2003), San Diego, CA (September 2003)

    Google Scholar 

  11. Brumitt, B., Shafer, S.: Topological World Modeling Using Semantic Spaces. In: Workshop Proceedings, UbiComp 2001, pp. 55–62 (2001)

    Google Scholar 

  12. Vapnik, V.: Statistical learning theory. John Wiley & Sons, New York (1998)

    MATH  Google Scholar 

  13. Sakamoto, J., Miura, H., Matsuda, N., Taki, H., Abe, N., Hori, S.: Indoor Location Determination Using a Topological Model. In: Khosla, R., Howlett, R.J., Jain, L.C. (eds.) KES 2005. LNCS (LNAI), vol. 3684, pp. 143–149. Springer, Heidelberg (2005)

    Chapter  Google Scholar 

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© 2006 Springer-Verlag Berlin Heidelberg

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Miura, H., Sakamoto, J., Matsuda, N., Taki, H., Abe, N., Hori, S. (2006). Adequate RSSI Determination Method by Making Use of SVM for Indoor Localization. In: Gabrys, B., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2006. Lecture Notes in Computer Science(), vol 4252. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11893004_81

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  • DOI: https://doi.org/10.1007/11893004_81

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-46537-9

  • Online ISBN: 978-3-540-46539-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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