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Edge Computing Approach for Vessel Monitoring System

Author

Listed:
  • Joao C. Ferreira

    (ISTAR-IUL, Instituto Universitário de Lisboa (ISCTE-IUL), 1649-026 Lisboa, Portugal
    ALGORITMI Research Centre, University of Minho, 4800-058 Guimarães, Portugal
    INOV INESC Inovação—Instituto de Novas Tecnologias, 1000-029 Lisboa, Portugal)

  • Ana Lucia Martins

    (Business Research Unit (BRU-IUL), Instituto Universitário de Lisboa (ISCTE-IUL), 1649-026 Lisboa, Portugal)

Abstract

A vessel monitoring system (VMS) is responsible for real-time vessel movement tracking. At sea, most of the tracking systems use satellite communications, which have high associated costs. This leads to a less frequent transmission of data, which reduces the reliability of the vessel location. Our research work involves the creation of an edge computing approach on a local VMS, creating an intelligent process that decides whether the collected data needs to be transmitted or not. Only relevant data that can indicate abnormal behavior is transmitted. The remaining data is stored and transmitted only at ports when communication systems are available at lower prices. In this research, we apply this approach to a fishing control process increasing the data collection process from once every 10 min to once every 30 s, simultaneously decreasing the satellite communication costs, as only relevant data is transmitted in real-time to the competent central authorities. Findings show substantial communication savings from 70% to 90% as only abnormal vessel behavior is transmitted. Even with a data collection process of once every 30 s, findings also show that the use of more stable fishing techniques and fishing areas result in higher savings. The proposed approach is assessed as well in terms of the environmental impact of fishing and potential fraud detection and reduction.

Suggested Citation

  • Joao C. Ferreira & Ana Lucia Martins, 2019. "Edge Computing Approach for Vessel Monitoring System," Energies, MDPI, vol. 12(16), pages 1-15, August.
  • Handle: RePEc:gam:jeners:v:12:y:2019:i:16:p:3087-:d:256539
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    References listed on IDEAS

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    1. Campbell, Maria S. & Stehfest, Kilian M. & Votier, Stephen C. & Hall-Spencer, Jason M., 2014. "Mapping fisheries for marine spatial planning: Gear-specific vessel monitoring system (VMS), marine conservation and offshore renewable energy," Marine Policy, Elsevier, vol. 45(C), pages 293-300.
    2. Martín, P. & Muntadas, A. & de Juan, S. & Sánchez, P. & Demestre, M., 2014. "Performance of a northwestern Mediterranean bottom trawl fleet: How the integration of landings and VMS data can contribute to the implementation of ecosystem-based fisheries management," Marine Policy, Elsevier, vol. 43(C), pages 112-121.
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    Cited by:

    1. Mussawir Ul Mehmood & Abasin Ulasyar & Abraiz Khattak & Kashif Imran & Haris Sheh Zad & Shibli Nisar, 2020. "Cloud Based IoT Solution for Fault Detection and Localization in Power Distribution Systems," Energies, MDPI, vol. 13(11), pages 1-19, May.

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