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Indoor Position Detection Using BLE Signals Based on Voronoi Diagram

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Intelligent Software Methodologies, Tools and Techniques (SoMeT 2015)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 532))

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Abstract

Bluetooth Low Energy (BLE) is a Bluetooth standard with low energy consumption. Beacons using BLE transmit BLE signals, which can be received by smart phones running iOS or Android OS. At present, demonstration experiments are conducted.

An indoor position detection using an ordered order-k Voronoi diagram was proposed. Beacons were installed in a building of Tokai University. Experiments are conducted to investigate position detection using the proposed approach. We have two results using the proposed system: (1) a floor decision success rate of 99.6 %; and (2) indoor position detection success rates of 85.5 % (first neighbor) and 48.9 % (second neighbor). Finally, we present some ideas for improving the proposed approach.

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Notes

  1. 1.

    Immediate, Near, Far and Unknown are the return values for a method in the iOS SDK.

  2. 2.

    Two Voronoi polygons are adjacent when the polygons share a segment.

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Acknowledgments

The author would like to thank Professor Yoshimi ISHIHARA, Dean of the School of Science, Tokai University, for allowing the installation of beacons on Building 18 and for providing the opportunity to conduct the present study. Thanks are also due to Professor Masanori ITAI for suggesting the beacon installation and to the Open Beacon Field Trial (OBFT) (http://openbeacon.android-group.jp/) for providing beacons as well as the opportunity to conduct the present study. Special thanks are due to Daiki KANAI, a student in my laboratory, for measuring the RSSIs of the beacons.

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Authors and Affiliations

  1. Tokai University, 4-1-1 Kitakaname, Hiratsuka, Kanagawa, 259-1292, Japan

    Kensuke Onishi

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  1. Kensuke Onishi
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Correspondence to Kensuke Onishi .

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Editors and Affiliations

  1. Iwate Prefectural University, Takizawa, Japan

    Hamido Fujita

  2. University of Naples "Federico II", Napoli, Italy

    Guido Guizzi

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Onishi, K. (2015). Indoor Position Detection Using BLE Signals Based on Voronoi Diagram. In: Fujita, H., Guizzi, G. (eds) Intelligent Software Methodologies, Tools and Techniques. SoMeT 2015. Communications in Computer and Information Science, vol 532. Springer, Cham. https://doi.org/10.1007/978-3-319-22689-7_2

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  • DOI: https://doi.org/10.1007/978-3-319-22689-7_2

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-22688-0

  • Online ISBN: 978-3-319-22689-7

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