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

被引:0
|
作者
Ning, Jia [1 ]
Pang, Shufen [2 ]
Arifin, Zainal [3 ]
Zhang, Yining [4 ]
Epa, U. P. K. [5 ]
Qu, Miaomiao [6 ]
Zhao, Jufen [7 ]
Zhen, Feiyang [8 ]
Chowdhury, Abhiroop [9 ]
Guo, Ran [10 ]
Deng, Yuncheng [11 ,12 ,13 ]
Zhang, Haiwen [12 ,14 ]
机构
[1] Wuhan Univ, Acad Int Law & Global Governance, Wuhan 430072, Peoples R China
[2] Xiamen Univ, Sch Law, Xiamen 361005, Peoples R China
[3] Natl Res & Innovat Agcy, Res Ctr Oceanog, Jakarta 14430, Indonesia
[4] Zhejiang Univ, Coll Civil Engn & Architecture, Hangzhou 310058, Peoples R China
[5] Univ Kelaniya, Dept Zool & Environm Management, Kelaniya 11600, Sri Lanka
[6] Zhejiang Ocean Univ, Sch Econ & Management, Zhoushan 316000, Peoples R China
[7] Fudan Univ, Sch Social Dev & Publ Policy, Shanghai 200433, Peoples R China
[8] Wuhan Univ, Econ Diplomacy Res Ctr, Wuhan 430072, Peoples R China
[9] OP Jindal Global Univ, Jindal Sch Environm & Sustainabil, Sonipat 131001, India
[10] Shanghai Maritime Univ, Sch Law, Shanghai 201306, Peoples R China
[11] Changzhou Univ, Shi Liang Sch Law, Changzhou 213159, Peoples R China
[12] Southern Marine Sci & Engn Guangdong Lab Zhuhai, Zhuhai 519082, Peoples R China
[13] Minist Nat Resources, Isl Res Ctr, Pingtan 350400, Peoples R China
[14] China Inst Marine Affairs CIMA, Beijing 100860, Peoples R China
关键词
marine pollution; artificial intelligence; bibliometric analyses; sustainable development; oceans; OIL-SPILL DETECTION; LAND-BASED SOURCES; PLASTIC DEBRIS; IMAGE SEGMENTATION; SAR IMAGES; SUSTAINABLE DEVELOPMENT; BIBLIOMETRIC ANALYSIS; DATABASES-SCOPUS; SEA-FLOOR; COASTAL;
D O I
10.3390/jmse12071181
中图分类号
U6 [水路运输]; P75 [海洋工程];
学科分类号
0814 ; 081505 ; 0824 ; 082401 ;
摘要
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.
引用
收藏
页数:25
相关论文
共 50 条
  • [31] Artificial intelligence and dynamic pricing: a systematic literature review
    Chenavaz, Regis Y.
    Dimitrov, Stanko
    JOURNAL OF APPLIED ECONOMICS, 2025, 28 (01)
  • [32] Contribution of Artificial Intelligence in Entrepreneurship: A Systematic Literature Review
    Mnajli, Fatima Ezzahra
    Chroqui, Razane
    DIGITAL TECHNOLOGIES AND APPLICATIONS, ICDTA 2024, VOL 3, 2024, 1100 : 13 - 23
  • [33] Artificial intelligence in mathematics education: A systematic literature review
    bin Mohamed, Mohamed Zulhilmi
    Hidayat, Riyan
    Suhaizi, Nurain Nabilah Binti
    Sabri, Norhafiza Binti Mat
    bin Mahmud, Muhamad Khairul Hakim
    Baharuddin, Siti Nurshafikah Binti
    INTERNATIONAL ELECTRONIC JOURNAL OF MATHEMATICS EDUCATION, 2022, 17 (03)
  • [34] Artificial intelligence and family businesses: a systematic literature review
    Kumar, Deepak
    Ratten, Vanessa
    JOURNAL OF FAMILY BUSINESS MANAGEMENT, 2024,
  • [35] Artificial Intelligence for Detecting Periodontitis: Systematic Literature Review
    Fidyawati, Desy
    Masulili, Sri Lelyati C.
    Iskandar, Hanna Bachtiar
    Suhartanto, Heru
    Soeroso, Yuniarti
    OPEN DENTISTRY JOURNAL, 2024, 18
  • [36] Artificial intelligence in animal farming: A systematic literature review
    Bao, Jun
    Xie, Qiuju
    JOURNAL OF CLEANER PRODUCTION, 2022, 331
  • [37] Artificial intelligence in project management: systematic literature review
    ISCTE – Instituto Universitário de Lisboa, Lisbon, Portugal
    不详
    不详
    不详
    不详
    Int. J. Technol. Intell. Planning, 2022, 2 (143-163): : 143 - 163
  • [38] The implementation of artificial intelligence in organizations: A systematic literature review
    Lee, Maggie C. M.
    Scheepers, Helana
    Lui, Ariel K. H.
    Ngai, Eric W. T.
    INFORMATION & MANAGEMENT, 2023, 60 (05)
  • [39] Artificial intelligence in learning and development: a systematic literature review
    Bhatt, Parag
    Muduli, Ashutosh
    EUROPEAN JOURNAL OF TRAINING AND DEVELOPMENT, 2023, 47 (7/8) : 677 - 694
  • [40] Artificial intelligence to automate the systematic review of scientific literature
    José de la Torre-López
    Aurora Ramírez
    José Raúl Romero
    Computing, 2023, 105 : 2171 - 2194