Enabling mMTC in Remote Areas: LoRaWAN and LEO Satellite Integration for Offshore Wind Farm Monitoring

Asad Ullah, Konstantin Mikhaylov, Hirley Alves

Research output: Contribution to journalArticleScientificpeer-review

56 Citations (Scopus)

Abstract

The offshore wind farms are gaining momentum due to their promise to offer sustainable energy with low pollution and greenhouse gas emission. However, despite all the immense technological progress of recent years, the operation in a harsh and hard-to-reach environment remains challenging. According to the reports, each offshore wind turbine requires five maintenance visits a year on average, and the cumulative repair costs constitute around 30% of the turbine’s life-cycle expenditure. Motivated by the advancement of massive machine-type connectivity (mMTC) and satellite technologies, in this study, we investigate the potential of these to enable remote monitoring of the offshore wind farms. Specifically, the two alternative architectures are considered. The indirect architecture relies on using a local mMTC gateway (GW) with a backbone over a reliable communication channel (e.g., satellite or wire-based). The direct approach implies the transmission of the data by sensors on the wind turbines directly to the mMTC GW on the low-Earth-orbit satellite. The details of the system design, the alternative implementation strategies, and relevant pros, cons, and tradeoffs are pin-pointed. Finally, we employ simulations using realistic deployment and traffic and advanced propagation and collision models to characterize these two approaches’ feasibility and packet delivery probability numerically when implemented over LoRaWAN mMTC technology.
Original languageEnglish
Pages (from-to)3744-3753
Number of pages10
JournalIEEE Transactions on Industrial Informatics
Volume18
Issue number6
DOIs
Publication statusPublished - Jun 2022
MoE publication typeA1 Journal article-refereed

Funding

This work was supported by the Academy of Finland through the 6Genesis Flagship project under Grant 318927 and the MRAT-SafeDrone project under Grant 341111.

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