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Real-World Indoor Location Assessment with Unmodified RFID Antennas

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Pattern Recognition Applications and Methods (ICPRAM 2023)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 14547))

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Abstract

The management of health systems has been one of the main challenges in several countries, especially where the aging population is increasing. This led to the adoption of smarter technologies as means to automate, and optimize processes within hospitals. One of the technologies adopted is active location tracking, which allows the staff within the hospital to quickly locate any sort of entity, from key persons to patients or equipment. In this work, we focus on exploring ML models to develop a reliable method for active indoor location tracking based on off the shelf RFID antennas with UHF passive tags. The presented work describes the full development of the solution, from the initial development made within a controlled environment, to the final evaluation made on a real health clinic. The proposed solution was able to achieved 0.47 m on average on a complex medical environment, with unmodified hardware.

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Notes

  1. 1.

    https://www.etsi.org/deliver/etsi_en/302200_302299/302208/03.02.00_20/en_302208v030200a.pdf.

  2. 2.

    https://www.gs1.org/standards/rfid/uhf-air-interface-protocol.

  3. 3.

    https://www.iso.org/standard/59644.html.

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Acknowledgements

This work is supported by the European Regional Development Fund (FEDER), through the Competitiveness and Internationalization Operational Programme (COMPETE 2020) of the Portugal 2020 framework [Project SDRT with Nr. 070192 (POCI-01-0247-FEDER-070192)]

Author information

Authors and Affiliations

  1. Departamento de Eletrónica, Telecomunicações e Informática, Universidade de Aveiro, Aveiro, Portugal

    Pedro Sobral, Rui Santos, Pedro Marques, Mário Antunes & João Paulo Barraca

  2. Instituto de Telecomunicações, Universidade de Aveiro, Aveiro, Portugal

    Pedro Sobral, Ricardo Alexandre, Mário Antunes & João Paulo Barraca

  3. Think Digital, Aveiro, Portugal

    João Silva & Nuno Ferreira

Authors
  1. Pedro Sobral
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  2. Rui Santos
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  3. Ricardo Alexandre
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  4. Pedro Marques
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  5. Mário Antunes
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  6. João Paulo Barraca
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  7. João Silva
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  8. Nuno Ferreira
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Corresponding author

Correspondence to Mário Antunes .

Editor information

Editors and Affiliations

  1. Sapienza University of Rome, Rome, Italy

    Maria De Marsico

  2. ICAR-CNR, Napoli, Italy

    Gabriella Sanniti Di Baja

  3. University of Lisbon, Lisbon, Portugal

    Ana Fred

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Sobral, P. et al. (2024). Real-World Indoor Location Assessment with Unmodified RFID Antennas. In: De Marsico, M., Di Baja, G.S., Fred, A. (eds) Pattern Recognition Applications and Methods. ICPRAM 2023. Lecture Notes in Computer Science, vol 14547. Springer, Cham. https://doi.org/10.1007/978-3-031-54726-3_3

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  • DOI: https://doi.org/10.1007/978-3-031-54726-3_3

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-54725-6

  • Online ISBN: 978-3-031-54726-3

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