食品科学 ›› 2025, Vol. 46 ›› Issue (18): 360-339.doi: 10.7506/spkx1002-6630-20250124-177

• 专题论述 • 上一篇    下一篇

人工智能与活鱼运输综述:潜在应用与挑战

蒲志盈,尹涛,吴海云,尤娟,刘茹   

  1. (1.华中农业大学食品科学技术学院,湖北?武汉 430070;2.东京海洋大学资源与环境学院,日本?东京 108-8477)
  • 出版日期:2025-09-25 发布日期:2025-08-19
  • 基金资助:
    “十四五”国家重点研发计划项目(2024YFD2100505);国家现代农业产业技术体系项目(CARS-45)

Review of Artificial Intelligence in Live Fish Transportation: Potential Applications and Challenges

PU Zhiying, YIN Tao, WU Haiyun, YOU Juan, LIU Ru   

  1. (1. College of Food Science and Technology, Huazhong Agricultural University, Wuhan 430070, China; 2. School of Resources and Environment, Ocean University of Tokyo, Tokyo 108-8477, Japan)
  • Online:2025-09-25 Published:2025-08-19

摘要: 活鱼运输作为渔业产业链的重要环节,其效率与质量至关重要。然而,传统的活鱼运输方式存在劳动强度高、效率低下以及对人工经验的依赖等问题。人工智能(artificial intelligence,AI)的发展为解决这些问题提供了创新的技术手段。已有研究表明,AI驱动的技术可显著提高运输效率、降低成本,并减少活鱼的应激反应,从而优化运输质量。尽管如此,AI在活鱼运输中的应用仍面临多种挑战,如复杂环境中的数据处理、传感器的稳定性与成本问题、算法的实时性要求等。本文综述了AI技术在活鱼运输中的潜在应用场景,包括活鱼应激反应的监测与分类、基于机器视觉和智能传感器的实时水质调节、路径优化算法,以及无人驾驶技术的应用场景,旨在为AI技术在活鱼运输领域的应用与推广提供理论支持和实践参考。

关键词: 活鱼运输;人工智能;传感器;无人驾驶;智能算法

Abstract: As an important link in the fishery industry chain, the efficiency and quality of live fish transportation are crucial. However, traditional transportation methods suffer from high labor intensity, low efficiency, and heavy reliance on human expertise. The development of artificial intelligence (AI) provides innovative technological solutions to address these challenges. Studies indicate that AI-driven technologies can significantly enhance transportation efficiency, reduce costs, and mitigate fish stress responses, thereby improving transportation quality. Nevertheless, AI applications in live fish transportation still face various challenges, such as data processing in complex environments, sensor stability and cost issues, and real-time algorithm requirements. This paper reviews the potential applications of AI in live fish transportation, including monitoring and classification of fish stress responses, real-time water quality regulation based on machine vision and intelligent sensors, route optimization algorithms, and application scenarios of autonomous driving technology. This paper aims to provide theoretical support and practical references for the application and promotion of AI technology in live fish transportation.

Key words: live fish transportation; artificial intelligence; sensors; autonomous driving; intelligent algorithm

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