The Diversity of Artificial Intelligence Applications in Marine Pollution: A Systematic Literature Review

Ning, Jia and Pang, Shufen and Arifin, Zainal and Zhang, Yining and Epa, U. P. K. and Qu, Miaomiao and Zhao, Jufen and Zhen, Feiyang and Chowdhury, Abhiroop and Guo, Ran and Deng, Yuncheng and Zhang, Haiwen (2024) The Diversity of Artificial Intelligence Applications in Marine Pollution: A Systematic Literature Review. Journal of Marine Science and Engineering, 12 (7). p. 1181. ISSN 2077-1312

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Abstract

Marine pollution, a major disturbance to the sustainable use of oceans, is becoming more prevalent around the world. Multidimensional and sustainable ocean governance have become increasingly focused on managing, reducing, and eliminating marine pollution. Artificial intelligence has been used more and more in recent years to monitor and control marine pollution. This systematic literature review, encompassing studies from the Web of Science and Scopus databases, delineates the extensive role of artificial intelligence in marine pollution management, revealing a significant surge in research and application. This review aims to provide information and a better understanding of the application of artificial intelligence in marine pollution. In marine pollution, 57% of AI applications are used for monitoring, 24% for management, and 19% for prediction. Three areas are emphasized: (1) detecting and responding to oil pollution, (2) monitoring water quality and its practical application, and (3) monitoring and identifying plastic pollution. Each area benefits from the unique capabilities of artificial intelligence. If the scientific community continues to explore and refine these technologies, the convergence of artificial intelligence and marine pollution may yield more sophisticated solutions for environmental conservation. Although artificial intelligence offers powerful tools for the treatment of marine pollution, it does have some limitations. Future research recommendations include (1) transferring experimental outcomes to industrial applications in a broader sense; (2) highlighting the cost-effective advantages of AI in marine pollution control; and (3) promoting the use of AI in the legislation and policy-making about controlling marine pollution.

Item Type: Article
Uncontrolled Keywords: marine pollution; artificial intelligence; bibliometric analyses; sustainable development; oceans
Subjects: Environmental Pollution & Control > Water Pollution & Control
Depositing User: Saepul Mulyana
Date Deposited: 10 Jul 2026 03:35
Last Modified: 10 Jul 2026 03:35
URI: https://karya.brin.go.id/id/eprint/59320

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