Adiyono, Soni and Arifin, Muhammad and Latifah, Noor and Darmanto, Eko (2025) Artificial Intelligence in Integrated Marine Observing Systems: A Comprehensive Review. Artificial Intelligence in Integrated Marine Observing Systems: A Comprehensive Review, 10 (1). pp. 155-164. ISSN 2548-1479

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Abstrak

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.

Item Type:	Article
Kata Kunci:	Artificial Intelligence, Marine, Integrated Marine Observing Systems (IMOS), Systematic Literature Review
Subjects:	Teknologi > Teknologi (umum) > Penelitian industri. Penelitian dan pengembangan Teknologi > T1 Teknologi (Umum) > Penelitian operasi. Analisa sistem Teknologi > T1 Teknologi (Umum) > Sistem Informasi Manajemen Teknologi > T1 Teknologi (Umum) > Teknologi Informasi
Program Studi:	Fakultas Teknik > S1 Sistem Informasi
Depositing User:	Mr Soni Adiyino
Date Deposited:	09 Jul 2025 02:35
Last Modified:	09 Jul 2025 02:35
URI:	http://eprints.umk.ac.id/id/eprint/24210

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