Integrated Fishing Vessel Monitoring System to Support Electronic Administrative Sanctions
Systematic Review
Keywords:
fisheries surveillance, electronic administrative sanctions, integrated monitoringAbstract
Rapid advances in digital innovation have transformed fisheries monitoring into a more transparent, accountable, and technology-oriented mechanism for marine resource management. This study presents a Literature Review that explores how the Integrated Fisheries Vessel Monitoring System (SVMS) contributes to the implementation of Electronic Administrative Sanctions (EAS). Using the PRISMA approach, 72 peer-reviewed publications from 2015 to 2025 were analyzed across the Scopus, Web of Science, and ScienceDirect databases. This synthesis focuses on three main domains: (1) integrated VMS technology configuration, including the application of IoT devices, geographic information systems (GIS), and data interoperability; (2) policy frameworks and governance structures that enable digital sanctioning processes; and (3) operational barriers in practice, such as cybersecurity risks, interagency coordination, and lack of technical standards. Findings indicate that integrated VMS systems substantially improve real-time vessel tracking, reduce illegal, unreported, and unregulated (IUU) fishing activities, and strengthen law enforcement efficiency through automation and analytics. However, challenges remain in establishing data-sharing mechanisms and harmonizing legal instruments among maritime authorities. Furthermore, this review highlights the importance of developing standardized digital infrastructure, enhancing cross-agency collaboration, and fostering an adaptive policy environment. Collectively, these studies provide a critical perspective on the evolution and potential of integrated digital surveillance systems to advance sustainable fisheries management and effective electronic law enforcement.
References
Acharya, D., Farazi, M., Rolland, V., Petersson, L., Rosebrock, U., Smith, D., … Wilcox, C. (2024). Towards automatic anomaly detection in fisheries using electronic monitoring and automatic identification system. Fisheries Research, 272(January), 106939. https://doi.org/10.1016/j.fishres.2024.106939
Cacaud, P., KuruC, M., & Spreij, M. (2003). Legislative Administrative sanctions in fisheries law Administrative sanctions in fisheries law (FAO, ed.). Rome.
Coro, G., Sana, L., Ferrà, C., Bove, P., & Scarcella, G. (2023). Estimating hidden fishing activity hotspots from vessel transmitted data. Frontiers in Sustainable Food Systems, 7.
Elizabeth, S., Arthur, P., & Charles, A. (2021). Vessel monitoring systems as a tool for mapping fishing effort for a small inshore fishery operating within a marine protected area. Marine Policy, 124(September 2020), 104325. https://doi.org/10.1016/j.marpol.2020.104325
Faillettaz, R., & Abangan, A. S. (2023). Arti icial intelligence for fish behavior recognition may unlock fishing gear selectivity. Frontiers in Marine Science, 10(February). https://doi.org/10.3389/fmars.2023.1010761
Galdelli, A. (2021). Monitor Fisheries and Detect Suspicious Activities †. MDPI Journal, 21, 1–18.
Gardner, C., Goethel, D. R., Karnauskas, M., Smith, M. W., Perruso, L., Iii, J. F. W., & Tassetti, A. N. (2022). Artificial Attraction : Linking Vessel Monitoring System and Habitat Data to Assess Commercial Exploitation on Artificial Structures in the Gulf of Mexico. Frontiers in Marine Science, 9(February), 1–20. https://doi.org/10.3389/fmars.2022.772292
Gerritsen, H., & Lordan, C. (2011). Integrating vessel monitoring systems ( VMS ) data with daily catch data from logbooks to explore the spatial distribution of catch and effort at high resolution. ICES Journal of Marine Science, 68(1), 245–252. https://doi.org/doi:10.1093/icesjms/fsq137
KKP. (2024). Bijak Mengelola Laut untuk Ekonomi Biru. Jakarta: Kementerian Kelautan dan Perikanan.
Kuemlangan, B., Amidjogbe, E., Nakamura, J., Tomassi, A., Hupperts, R., Bojang, B., & Amador, T. (2023). Enforcement approaches against illegal fishing in national fisheries legislation. Marine Policy, 149(34), 105. https://doi.org/10.1016/j.marpol.2023.105514
Kushardono, D., & Gaol, J. (2023). Deteksi Kapal Penangkapan Ikan Menggunakan data Visible Infrared Imaging Deteksi Kapal Penangkapan Ikan Menggunakan data Visible Infrared Imaging Radiometer Suite ( VIIRS ) dan data Vessel Monitoring System ( VMS ) di Wilayah Pengelolaan Perikanan Negara. Journal of Marine and Aquatic Sciences, 8(1), 102–107. https://doi.org/10.24843/jmas.2022.v08.i01.p12
National Development Planning Agency. (2021). Blue Economy Development Framework for Indonesia’s Economic Transformation. Jakarta: BAPPENAS.
Orofino, S., Mcdonald, G., Mayorga, J., Costello, C., & Bradley, D. (2023). Opportunities and challenges for improving fisheries management through greater transparency in vessel tracking. ICES Journal of Marine Science, 80(February), 675–689. https://doi.org/10.1093/icesjms/fsad008
Pratomo, A., & Sabihaini. (2020). Integration Of Weather Information Systems And The Potential Of Fish Spread With Vessel Monitoring. 11(11), 1372–1386.
Skerritt, D. (2024). Seeking clarity on transparency in fisheries governance and management. Marine Policy, 165. https://doi.org/https://doi.org/10.1016/j.marpol.2024.106221
Soemarmi, A., & Indarti, E. (2020). Teknologi Vessel Monitoring System ( VMS ) Sebagai Strategi Perlindungan Dan Pembangunan. Masalah- Masalah Hukum, 49(3), 303–313. https://doi.org/https://doi.org/10.14710/mmh.49.3.2020.303-313
Stone, J. C., Hugh, T., Edoardo, B., Merel, A., Sears, K., Klugar, M., & Zachary, J. L. (2023). From critical appraisal to risk of bias assessment: clarifying the terminology for study evaluation in JBI systematic reviews. JBI Evidence Synthesis, 21(3), 472–477. https://doi.org/10.11124/JBIES-22-00434
Vaarandi, R., & Tsiopoulos, L. (2017). A Systematic Literature Review of Cyber Security Monitoring in Maritime. Arxiv.
Valentina, M., Mesa, C., & Patino-rodriguez, C. E. (2024). Cybersecurity at Sea : A Literature Review of Cyber-Attack Impacts and Defenses in Maritime Supply Chains. MDPI Journal, 15(11), 710. https://doi.org/https://doi.org/10.3390/info15110710
Welch, H., Ames, R. T., Kolla, N., Kroodsma, D. A., Marsaglia, L., Russo, T., … Hazen, E. L. (2024). Harnessing AI to map global fishing vessel activity. One Earth, 7(10), 1685–1691. https://doi.org/10.1016/j.oneear.2024.09.009
Willette, D. A., Barber, P. H., Bunje, P. M. E., Cauzac, J., Conchon, A., & Trenkel, V. M. (2023). Emerging monitoring technologies to reduce illegal fishing activities at sea and prevent entry of fraudulent fish into markets. Frontiers, (May), 1–7. https://doi.org/10.3389/fsufs.2023.1166131
