Artificial Intelligence in Integrated Marine Observing Systems: A Comprehensive Review

Soni Adiyono (Prodi Sistem Informasi, Fakultas Teknik, Universitas Muria Kudus)
Muhammad Arifin (Prodi Sistem Informasi, Fakultas Teknik, Universitas Muria Kudus)
Noor Latifah (Prodi Sistem Informasi, Fakultas Teknik, Universitas Muria Kudus)
Eko Darmanto (Prodi Sistem Informasi, Fakultas Teknik, Universitas Muria Kudus)

International Journal of Marine Engineering Innovation and Research
Vol 10, No 1 (2025)

The marine ecosystem is vital for sustaining life on Earth, yet its vastness and complexity present significant challenges for effective monitoring and management. Integrated Marine Observing Systems (IMOS) have emerged as essential tools for understanding and protecting marine environments. This study aims to systematically review the integration of artificial intelligence (AI) into IMOS, focusing on its contributions to data processing, biodiversity monitoring, and environmental change analysis. A systematic literature review (SLR) method is employed to analyze existing research and identify key AI techniques and their applications in marine and oceanographic studies. Results indicate that deep learning is the most widely used AI method, with marine research being the primary application domain. Other areas, such as environmental monitoring and industrial systems, also demonstrate considerable potential. However, data inconsistency, operational limitations, and the lack of standardized frameworks remain significant barriers. This review highlights the transformative role of AI in enhancing IMOS capabilities and provides recommendations for addressing existing challenges to support sustainable marine management.