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Multi-Slot BLE Raw Database for Accurate Positioning in Mixed Indoor/Outdoor Environments

Author

Listed:
  • Fernando J. Aranda

    (Sensory Systems Research Group, University of Extremadura, 06006 Badajoz, Spain)

  • Felipe Parralejo

    (Sensory Systems Research Group, University of Extremadura, 06006 Badajoz, Spain)

  • Fernando J. Álvarez

    (Sensory Systems Research Group, University of Extremadura, 06006 Badajoz, Spain)

  • Joaquín Torres-Sospedra

    (UBIK Geospatial Solutions S.L., Espaitec2, Campus de Riu Sec, Avda. Vicente Sos Baynat S/N, 12006 Castellón, Spain
    Institute of New Imaging Technologies, Universitat Jaume I, Avda. Vicente Sos Baynat S/N, 12071 Castellón, Spain)

Abstract

The technologies and sensors embedded in smartphones have contributed to the spread of disruptive applications built on top of Location Based Services (LBSs). Among them, Bluetooth Low Energy (BLE) has been widely adopted for proximity and localization, as it is a simple but efficient positioning technology. This article presents a database of received signal strength measurements (RSSIs) on BLE signals in a real positioning system. The system was deployed on two buildings belonging to the campus of the University of Extremadura in Badajoz. the database is divided into three different deployments, changing in each of them the number of measurement points and the configuration of the BLE beacons. the beacons used in this work can broadcast up to six emission slots simultaneously. Fingerprinting positioning experiments are presented in this work using multiple slots, improving positioning accuracy when compared with the traditional single slot approach.

Suggested Citation

  • Fernando J. Aranda & Felipe Parralejo & Fernando J. Álvarez & Joaquín Torres-Sospedra, 2020. "Multi-Slot BLE Raw Database for Accurate Positioning in Mixed Indoor/Outdoor Environments," Data, MDPI, vol. 5(3), pages 1-20, July.
    • Handle: RePEc:gam:jdataj:v:5:y:2020:i:3:p:67-:d:392383
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    References listed on IDEAS

    as
    1. Germán Martín Mendoza-Silva & Miguel Matey-Sanz & Joaquín Torres-Sospedra & Joaquín Huerta, 2019. "BLE RSS Measurements Dataset for Research on Accurate Indoor Positioning," Data, MDPI, vol. 4(1), pages 1-17, January.
    2. Zohaib Iqbal & Da Luo & Peter Henry & Samaneh Kazemifar & Timothy Rozario & Yulong Yan & Kenneth Westover & Weiguo Lu & Dan Nguyen & Troy Long & Jing Wang & Hak Choy & Steve Jiang, 2018. "Accurate real time localization tracking in a clinical environment using Bluetooth Low Energy and deep learning," PLOS ONE, Public Library of Science, vol. 13(10), pages 1-13, October.
    Full references (including those not matched with items on IDEAS)

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    Cited by:

    1. Emilio Sansano-Sansano & Fernando J. Aranda & Raúl Montoliu & Fernando J. Álvarez, 2020. "BLE-GSpeed: A New BLE-Based Dataset to Estimate User Gait Speed," Data, MDPI, vol. 5(4), pages 1-15, December.
    2. Asim Abdullah & Muhammad Haris & Omar Abdul Aziz & Rozeha A. Rashid & Ahmad Shahidan Abdullah, 2023. "UTMInDualSymFi: A Dual-Band Wi-Fi Dataset for Fingerprinting Positioning in Symmetric Indoor Environments," Data, MDPI, vol. 8(1), pages 1-38, January.

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