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Different Approaches to Indoor Localization Based on Bluetooth Low Energy Beacons and Wi-Fi

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Computational Collective Intelligence (ICCCI 2017)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10449))

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Abstract

Thanks to Global Navigation Satellite Systems, the position of a smartphone equipped with the particular receiver can be determined with an accuracy of a few meters outdoors, having a clear view of the sky. These systems, however, are not usable indoors, because there is no signal from satellites. Therefore, it is necessary to use other localization techniques indoors. This paper focuses on the use of Bluetooth Low Energy and Wi-Fi radio technologies. We have created a special mobile application for the Android operating system in order to evaluate these techniques. This application allows localization testing in a real environment within a building of a university campus. We compare multiple approaches based on K-Nearest Neighbors and Particle Filter algorithms that have been further modified. The combination of Low Energy Bluetooth and Wi-Fi appears to be a promising solution reaching the satisfying accuracy and minimal deployment costs.

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Notes

  1. 1.

    https://github.com/Rajawali/Rajawali.

  2. 2.

    https://github.com/Estimote/Android-SDK.

  3. 3.

    https://github.com/couchbase/couchbase-lite-android.

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Acknowledgements

The authors of this paper would like to thank Tereza Krizova for proofreading. This work and the contribution were also supported by a project of Students Grant Agency – FIM, University of Hradec Kralove, Czech Republic (under ID: UHK-FIM-SP-2017). Radek Bruha is a student member of the research team.

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Authors and Affiliations

  1. Department of Informatics and Quantitative Methods, Faculty of Informatics and Management, University of Hradec Kralove, Hradec Kralove, Czech Republic

    Radek Bruha & Pavel Kriz

Authors
  1. Radek Bruha
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  2. Pavel Kriz
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Corresponding author

Correspondence to Pavel Kriz .

Editor information

Editors and Affiliations

  1. Department of Information Systems, Faculty of Computer Science and Management, Wrocław University of Science and Technology, Wrocław, Poland

    Ngoc Thanh Nguyen

  2. Department of Computer Science, University of Cyprus, Nicosia, Cyprus

    George A. Papadopoulos

  3. Department of Information Systems, Gdynia Maritime University, Gdynia, Poland

    Piotr Jędrzejowicz

  4. Department of Information Systems, Faculty of Computer Science and Management, Wrocław University of Science and Technology, Wrocław, Poland

    Bogdan Trawiński

  5. Department of Information Systems, University of Münster, Münster, Germany

    Gottfried Vossen

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Bruha, R., Kriz, P. (2017). Different Approaches to Indoor Localization Based on Bluetooth Low Energy Beacons and Wi-Fi. In: Nguyen, N., Papadopoulos, G., Jędrzejowicz, P., Trawiński, B., Vossen, G. (eds) Computational Collective Intelligence. ICCCI 2017. Lecture Notes in Computer Science(), vol 10449. Springer, Cham. https://doi.org/10.1007/978-3-319-67077-5_29

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  • DOI: https://doi.org/10.1007/978-3-319-67077-5_29

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-67076-8

  • Online ISBN: 978-3-319-67077-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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