Low Power Wide Area Networks (LPWAN) at Sea: Performance Analysis of Offshore Data Transmission by Means of LoRaWAN Connectivity for Marine Monitoring Applications.

IoT LPWAN LoRaWAN marine monitoring offshore data transmission

Journal

Sensors (Basel, Switzerland)
ISSN: 1424-8220
Titre abrégé: Sensors (Basel)
Pays: Switzerland
ID NLM: 101204366

Informations de publication

Date de publication:
23 Jul 2019
Historique:
received: 26 06 2019
revised: 12 07 2019
accepted: 19 07 2019
entrez: 26 7 2019
pubmed: 26 7 2019
medline: 26 7 2019
Statut: epublish

Résumé

In this paper the authors discuss the realization of a Long Range Wide Area Network (LoRaWAN) network infrastructure to be employed for monitoring activities within the marine environment. In particular, transmission ranges as well as the assessment of parameters like Signal to Noise Ratio (SNR) and Received Signal Strength Indicator (RSSI) are analyzed in the specific context of an aquaculture industrial plant, setting up a transmission channel from an offshore monitoring structure provided with a LoRaWAN transmitter, to an ashore receiving device composed of two LoRaWAN Gateways. A theoretical analysis about the feasibility of the transmission is provided. The performances of the system are then measured with different network parameters (in particular the Spreading Factor-SF) as well as with two different heights for the transmitting antenna. Test results prove that efficient data transmission can be achieved at a distance of 8.33 km even using worst case network settings: this suggests the effectiveness of the system even in harsher environmental conditions, thus entailing a lower quality of the transmission channel, or for larger transmission ranges.

Identifiants

pubmed: 31340549
pii: s19143239
doi: 10.3390/s19143239
pmc: PMC6679513
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Subventions

Organisme : Regione Toscana
ID : 7429.31052017.113000176

Références

Sensors (Basel). 2018 Mar 03;18(3):null
pubmed: 29510524
Sensors (Basel). 2018 Apr 06;18(4):null
pubmed: 29642391
Sensors (Basel). 2018 Apr 21;18(4):null
pubmed: 29690552
Sensors (Basel). 2018 Aug 29;18(9):null
pubmed: 30158501
Sensors (Basel). 2018 Nov 16;18(11):null
pubmed: 30453524
Sensors (Basel). 2019 Jan 19;19(2):null
pubmed: 30669487

Auteurs

Lorenzo Parri (L)

Department of Information Engineering and Mathematics, University of Siena, 53100 Siena, Italy.

Stefano Parrino (S)

Department of Information Engineering and Mathematics, University of Siena, 53100 Siena, Italy.

Giacomo Peruzzi (G)

Department of Information Engineering and Mathematics, University of Siena, 53100 Siena, Italy.

Alessandro Pozzebon (A)

Department of Information Engineering and Mathematics, University of Siena, 53100 Siena, Italy. alessandro.pozzebon@unisi.it.

Classifications MeSH