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张东,等                                                                  水产学报, 2025, 49(7): 079103

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                                A study of aquatic animal behavior in the AI era


                                                           1*
                                              ZHANG Dong  ,     DUAN Ming  2
                   1. East China Sea Fisheries Research Institute, Chinese Academy of Fisheries Science, Shanghai 200090, China;
                2. Hubei Key Laboratory of Smart Fisheries, State Key Laboratory of Breeding Biotechnology and Sustainable Aquaculture,
                               Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan 430072, China


              Abstract: As the importance of ethology in the management of aquatic animals (including natural resources and aquaculture)
              becomes increasingly prominent, traditional manual observation and data analysis methods can no longer meet the industry's
              demand for ethological data of aquatic animals. In recent years, with the rapid development of artificial intelligence (AI) tech-
              nologies, related technologies have played an increasingly important role in the study on aquatic animal behavior, providing
              strong technical support for accelerating research on aquatic animal behavior and its application in the fisheries industry, such
              as aquaculture. This paper briefly reviews the latest applications of AI technology in the study of aquatic animal behavior, and
              the significant advancement in behavioral research from "manual observation" to "intelligent perception", including automatic
              image and video analysis, behavior pattern recognition, behavior prediction, and applications in aquaculture. Finally, the review
              discusses the key research directions of aquatic animal behavior in the AI era, providing a reference for researchers in the
              related fields. In the future, we should particularly focus on the following fields: ① animal personality which is the core of
              behavioral ecology; ② behavior-ecology-physiology-gene data chain; ③ AI model generalization; ④ data standardization.
              Key words: aquatic animal; artificial intelligence; behavior; machine learning; internet of things; big data
              Corresponding author: ZHANG Dong. E-mail: zdfit63@163.com
              Funding projects: Science and Technology Innovation Team Project of Chinese Academy of Fishery Sciences (2023TD56)











              https://www.china-fishery.cn                           中国水产学会主办    sponsored by China Society of Fisheries
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