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Analysis of Bluetooth Low Energy RSSI Values for Use as a Real Time Link Quality Indicator for Indoor Location

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Computational Science and Its Applications – ICCSA 2020 (ICCSA 2020)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 12254))

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Abstract

Technologies that can be used for location outdoors are readily available using Global Positioning Systems (GPS) whilst technologies used for indoor location still prove to be a challenge. Technologies such as Radio Frequency Identification (RFID), Bluetooth, and Wi-Fi, together with location algorithms that include optimization, still require further research for large-scale deployments. This study adopts Bluetooth Low Energy technology and uses the Received Signal strength Indicator (RSSI) from messages as a data source. We then analyse the RSSI from Low Power Nodes, their calculated mean, median and mode values as a basis for further use in an indoor real time location system. Fingerprint databases have been used extensively as a reference to determine location. However, due to the changing indoor environment these may become outdated very quickly. Therefore, this study proposes the use of a Link Quality Indicator as a reference point for further calculation of the location of an asset or a person. The Nordic System on Chip (SOC) is used as the low power node together with a series of Raspberry Pi gateways. Results show that the mean and mode can be used in combination to filter and smooth RSSI values. These calculated RSSI values can then be used and as inputs for an indoor location engine for location determination.

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Author information

Authors and Affiliations

  1. Department of IT, Durban University of Technology, Durban, South Africa

    Jay Pancham & Richard Millham

  2. Durban University of Technology, Durban, South Africa

    Simon James Fong

  3. Department of Computer and Information Science, University of Macau, Taipa, Macau SAR

    Simon James Fong

Authors
  1. Jay Pancham
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  2. Richard Millham
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  3. Simon James Fong
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Corresponding authors

Correspondence to Jay Pancham , Richard Millham or Simon James Fong .

Editor information

Editors and Affiliations

  1. University of Perugia, Perugia, Italy

    Osvaldo Gervasi

  2. University of Basilicata, Potenza, Potenza, Italy

    Beniamino Murgante

  3. Chair- Center of ICT/ICE, Covenant University, Ota, Nigeria

    Sanjay Misra

  4. University of Cagliari, Cagliari, Italy

    Chiara Garau

  5. University of Cagliari, Cagliari, Italy

    Ivan Blečić

  6. Clayton School of Information Technology, Monash University, Clayton, VIC, Australia

    David Taniar

  7. Department of Information Science, Kyushu Sangyo University, Fukuoka, Japan

    Bernady O. Apduhan

  8. University of Minho, Braga, Portugal

    Ana Maria A. C. Rocha

  9. Polytechnic University of Bari, Bari, Italy

    Eufemia Tarantino

  10. Polytechnic University of Bari, Bari, Italy

    Carmelo Maria Torre

  11. Department of Neurology, University of Massachusetts Medical School, Worcester, MA, USA

    Yeliz Karaca

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Pancham, J., Millham, R., Fong, S.J. (2020). Analysis of Bluetooth Low Energy RSSI Values for Use as a Real Time Link Quality Indicator for Indoor Location. In: Gervasi, O., et al. Computational Science and Its Applications – ICCSA 2020. ICCSA 2020. Lecture Notes in Computer Science(), vol 12254. Springer, Cham. https://doi.org/10.1007/978-3-030-58817-5_69

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  • DOI: https://doi.org/10.1007/978-3-030-58817-5_69

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-58816-8

  • Online ISBN: 978-3-030-58817-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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