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Indoor Vehicles Geolocalization Using LoRaWAN

Author

Listed:
  • Pietro Manzoni

    (Department of Computer Engineering (DISCA), Universitat Politècnica de València, 46022 Valencia, Spain
    All authors contributed equally to this work.)

  • Carlos T. Calafate

    (Department of Computer Engineering (DISCA), Universitat Politècnica de València, 46022 Valencia, Spain
    All authors contributed equally to this work.)

  • Juan-Carlos Cano

    (Department of Computer Engineering (DISCA), Universitat Politècnica de València, 46022 Valencia, Spain
    All authors contributed equally to this work.)

  • Enrique Hernández-Orallo

    (Department of Computer Engineering (DISCA), Universitat Politècnica de València, 46022 Valencia, Spain
    All authors contributed equally to this work.)

Abstract

One of the main drawbacks of Global Navigation Satellite Sytems (GNSS) is that they do not work indoors. When inside, there is often no direct line from the satellite signals to the device and the ultra high frequency (UHF) used is blocked by thick, solid materials such as brick, metal, stone or wood. In this paper, we describe a solution based on the Long Range Wide Area Network (LoRaWAN) technology to geolocalise vehicles indoors. Through estimation of the behaviour of a LoRaWAN channel and using trilateration, the localisation of a vehicle can be obtained within a 20–30 m range. Indoor geolocation for Intelligent Transporation Systems (ITS) can be used to locate vehicles of any type in underground parkings, keep a platoon of trucks in formation or create geo-fences, that is, sending an alert if an object moves outside a defined area, like a bicycle being stolen. Routing of heavy vehicles within an industrial setting is another possibility.

Suggested Citation

  • Pietro Manzoni & Carlos T. Calafate & Juan-Carlos Cano & Enrique Hernández-Orallo, 2019. "Indoor Vehicles Geolocalization Using LoRaWAN," Future Internet, MDPI, vol. 11(6), pages 1-15, May.
    • Handle: RePEc:gam:jftint:v:11:y:2019:i:6:p:124-:d:236224
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    Citations

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    Cited by:

    1. Antonella Molinaro & Claudia Campolo & Jérôme Härri & Christian Esteve Rothenberg & Alexey Vinel, 2020. "5G-V2X Communications and Networking for Connected and Autonomous Vehicles," Future Internet, MDPI, vol. 12(7), pages 1-3, July.

    More about this item

    Keywords

    LoRaWAN; geolocalization; ITS;
    All these keywords.

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