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Improving bluetooth beacon-based indoor location and fingerprinting

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Abstract

The complex way radio waves propagate indoors, leads to the derivation of location using fingerprinting techniques. In this cases, location is computed relying on WiFi signals strength mapping. Recent Bluetooth low energy (BLE) provides new opportunities to explore positioning. In this work is studied how BLE beacons radio signals can be used for indoor location scenarios, as well as their precision. Additionally, this paper also introduces a method for beacon-based positioning, based on signal strength measurements at key distances for each beacon. This method allows to use different beacon types, brands, and location conditions/constraints. Depending on each situation (i.e., hardware and location) it is possible to adapt the distance measuring curve to minimize errors and support higher distances, while at the same time keeping good precision. Moreover, this paper also presents a comparison with traditional positioning method, using formulas for distance estimation, and the position triangulation. The proposed study is performed inside the campus of Viseu Polytechnic Institute, and tested using a group of students, each with his smart-phone, as proof of concept. Experimental results show that BLE allows having < 1.5 m error approximately 90% of the times, and the experimental results using the proposed location detection method show that the proposed position technique has 13.2% better precision than triangulation, for distances up to 10 m.

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Acknowledgements

“This work is financed by national funds through FCT - Fundação para a Ciência e Tecnologia, IP, under the project UID/Multi/04016/2019. Also financed by CityAction and BlueEyes project, respectively, CENTRO-01-0247-FEDER-017711, and 02/SAICT/2016, supported by Centro Portugal Regional Operational Program (CENTRO 2020), under the Portugal 2020 Partnership Agreement, through the European Regional Development Fund (ERDF). Furthermore, we would like to thank the Instituto Politécnico de Viseu and CI&DETS for their support”.

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Authors and Affiliations

  1. Department of Computer, Polytechnic Institute of Viseu, Viseu, Portugal

    Pedro Martins, Filipe Sá, Francisco Morgado & Filipe Caldeira

  2. Department of Computer Sciences, University of Coimbra, Coimbra, Portugal

    Maryam Abbasi

  3. Department of Computer Sciences, University of Lisbon, Lisbon, Portugal

    José Cecílio

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  1. Pedro Martins
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  2. Maryam Abbasi
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  3. Filipe Sá
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  4. José Cecílio
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  5. Francisco Morgado
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  6. Filipe Caldeira
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Correspondence to Pedro Martins.

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Martins, P., Abbasi, M., Sá, F. et al. Improving bluetooth beacon-based indoor location and fingerprinting. J Ambient Intell Human Comput 11, 3907–3919 (2020). https://doi.org/10.1007/s12652-019-01626-2

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  • DOI: https://doi.org/10.1007/s12652-019-01626-2

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