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.
Authors
Jia Ning, Academy of International Law and Global Governance, Wuhan University, Wuhan 430072, China.
Shufen Pang, School of Law, Xiamen University, Xiamen 361005, China.
Zainal Arifin, Research Centre for Oceanography, National Research and Innovation Agency, Jakarta, Indonesia.
Yining Zhang, College of Civil Engineering and Architecture, Zhejiang University, Hangzhou 310058, China.
U. P. K. Epa, Department of Zoology and Environmental Management, University of Kelaniya, Kelaniya 11600, Sri Lanka.
Miaomiao Qu, School of Economics and Management, Zhejiang Ocean University, Zhoushan 316000, China.
Jufen Zhao, School of Social Development and Public Policy, Fudan University, Shanghai 200433, China.
Feiyang Zhen, Economic Diplomacy Research Center, Wuhan University, Wuhan 430072, China.
Abhiroop Chowdhury, Professor, Jindal School of Environment and Sustainability, O.P. Jindal Global University, Sonipat, Haryana, India.
Ran Guo, School of Law, Shanghai Maritime University, Shanghai 201306, China.
Yuncheng Deng, Shi Liang School of Law, Changzhou University, Changzhou 213159, China; Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai 519082, China; Island Research Center, Ministry of Natural Resources, Pingtan 350400, China.
Haiwen Zhang, Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai 519082, China; China Institute for Marine Affairs (CIMA), Beijing 100860, China.
Summary
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.
Published in: Journal of Marine Science and Engineering
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