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LoRaWAN: Lost for Localization?

Svertoka, Ekaterina; Rusu-Casandra, Alexandru; Burget, Radim; Marghescu, Ion; Hosek, Jiri; Ometov, Aleksandr (2022-12-01)

 
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LoRaWAN_Lost_for_Localization.pdf (3.519Mt)
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Svertoka, Ekaterina
Rusu-Casandra, Alexandru
Burget, Radim
Marghescu, Ion
Hosek, Jiri
Ometov, Aleksandr
01.12.2022

IEEE Sensors Journal
doi:10.1109/JSEN.2022.3212319
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Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:tuni-202212058893

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Peer reviewed
Tiivistelmä
Nowadays, the flexible localization solution for various devices for work safety is one of the most demanding research questions. Notably, it is expected to provide an acceptable level of precision in different types of environments empowered by wearable technology and the Interent of Things (IoT) devices. Existing leading localization technologies are adapted for certain conditions, e.g., Wi-Fi, BLE, UWB are used for indoor areas and various GNSS-based ones for outdoor. This work focuses on investigating the LoRaWAN (868 MHz band) as a potential candidate to bridge this gap, being one of the most reliable and recognized communication technologies for the Industrial Internet of Things (IIoT). In the past, the research community had a lot of critics with respect to the applicability of LoRaWAN for localization, while the vision is facing a tremendous change over the past two years. The purpose of this work is to assess the feasibility of LoRaWAN as a localization solution for work safety applications in the industrial scenario from different angles. The work is based on two measurement campaigns conducted at the Brno University of Technology (BUT), Brno, Czech Republic, and University Politechnica in Bucharest (UPB), Bucharest, Romania. The campaigns cover both indoor and outdoor scenarios, provide the practical limitations of the positioning in standalone and k-NN powered localization systems. According to the results, LoRaWAN-based localization with relatively dense gateways deployment allows for achieving a meter-level accuracy, which may be suitable for the localization of workers.
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Kalevantie 5
PL 617
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Kalevantie 5
PL 617
33014 Tampereen yliopisto
oa[@]tuni.fi | Tietosuoja | Saavutettavuusseloste