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Temperature Impact in LoRaWAN—A Case Study in Northern Sweden

LoRaWAN has become popular as an IoT enabler. The low cost, ease of installation and the capacity of fine-tuning the parameters make this network a suitable candidate for the deployment of smart cities. In northern Sweden, in the smart region of Skellefteå, we have deployed a LoRaWAN to enable IoT a...

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Autores principales: Souza Bezerra, Níbia, Åhlund, Christer, Saguna, Saguna, de Sousa, Vicente A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6833474/
https://www.ncbi.nlm.nih.gov/pubmed/31614808
http://dx.doi.org/10.3390/s19204414
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author Souza Bezerra, Níbia
Åhlund, Christer
Saguna, Saguna
de Sousa, Vicente A.
author_facet Souza Bezerra, Níbia
Åhlund, Christer
Saguna, Saguna
de Sousa, Vicente A.
author_sort Souza Bezerra, Níbia
collection PubMed
description LoRaWAN has become popular as an IoT enabler. The low cost, ease of installation and the capacity of fine-tuning the parameters make this network a suitable candidate for the deployment of smart cities. In northern Sweden, in the smart region of Skellefteå, we have deployed a LoRaWAN to enable IoT applications to assist the lives of citizens. As Skellefteå has a subarctic climate, we investigate how the extreme changes in the weather happening during a year affect a real LoRaWAN deployment in terms of SNR, RSSI and the use of SF when ADR is enabled. Additionally, we evaluate two propagation models (Okumura-Hata and ITM) and verify if any of those models fit the measurements obtained from our real-life network. Our results regarding the weather impact show that cold weather improves the SNR while warm weather makes the sensors select lower SFs, to minimize the time-on-air. Regarding the tested propagation models, Okumura-Hata has the best fit to our data, while ITM tends to overestimate the RSSI values.
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spelling pubmed-68334742019-11-25 Temperature Impact in LoRaWAN—A Case Study in Northern Sweden Souza Bezerra, Níbia Åhlund, Christer Saguna, Saguna de Sousa, Vicente A. Sensors (Basel) Article LoRaWAN has become popular as an IoT enabler. The low cost, ease of installation and the capacity of fine-tuning the parameters make this network a suitable candidate for the deployment of smart cities. In northern Sweden, in the smart region of Skellefteå, we have deployed a LoRaWAN to enable IoT applications to assist the lives of citizens. As Skellefteå has a subarctic climate, we investigate how the extreme changes in the weather happening during a year affect a real LoRaWAN deployment in terms of SNR, RSSI and the use of SF when ADR is enabled. Additionally, we evaluate two propagation models (Okumura-Hata and ITM) and verify if any of those models fit the measurements obtained from our real-life network. Our results regarding the weather impact show that cold weather improves the SNR while warm weather makes the sensors select lower SFs, to minimize the time-on-air. Regarding the tested propagation models, Okumura-Hata has the best fit to our data, while ITM tends to overestimate the RSSI values. MDPI 2019-10-12 /pmc/articles/PMC6833474/ /pubmed/31614808 http://dx.doi.org/10.3390/s19204414 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Souza Bezerra, Níbia
Åhlund, Christer
Saguna, Saguna
de Sousa, Vicente A.
Temperature Impact in LoRaWAN—A Case Study in Northern Sweden
title Temperature Impact in LoRaWAN—A Case Study in Northern Sweden
title_full Temperature Impact in LoRaWAN—A Case Study in Northern Sweden
title_fullStr Temperature Impact in LoRaWAN—A Case Study in Northern Sweden
title_full_unstemmed Temperature Impact in LoRaWAN—A Case Study in Northern Sweden
title_short Temperature Impact in LoRaWAN—A Case Study in Northern Sweden
title_sort temperature impact in lorawan—a case study in northern sweden
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6833474/
https://www.ncbi.nlm.nih.gov/pubmed/31614808
http://dx.doi.org/10.3390/s19204414
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