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Temperature Impact in LoRaWAN: A Case Study in Northern Sweden
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.ORCID iD: 0000-0003-1396-1006
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.ORCID iD: 0000-0002-8681-9572
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.ORCID iD: 0000-0001-8561-7963
Federal University of Rio Grande do Norte (UFRN).ORCID iD: 0000-0003-2859-6136
2019 (English)In: Sensors, ISSN 1424-8220, E-ISSN 1424-8220, Vol. 19, no 20, article id 4414Article in journal (Refereed) Published
Abstract [en]

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.

Place, publisher, year, edition, pages
MDPI, 2019. Vol. 19, no 20, article id 4414
Keywords [en]
ADR, IoT, LoRa, LoRaWAN, propagation model, smart city
National Category
Communication Systems Media and Communication Technology
Research subject
Pervasive Mobile Computing
Identifiers
URN: urn:nbn:se:ltu:diva-76400DOI: 10.3390/s19204414ISI: 000497864700062PubMedID: 31614808Scopus ID: 2-s2.0-85073456473OAI: oai:DiVA.org:ltu-76400DiVA, id: diva2:1361298
Note

Validerad;2019;Nivå 2;2019-10-21 (johcin)

Available from: 2019-10-15 Created: 2019-10-15 Last updated: 2019-12-09Bibliographically approved

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