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Smart Agriculture ›› 2020, Vol. 2 ›› Issue (3): 1-20.doi: 10.12133/j.smartag.2020.2.3.202004-SA007

• 专题--农业人工智能与大数据 • 上一篇    下一篇

人工智能在水产养殖中研究应用分析与未来展望

李道亮1,2(), 刘畅1,2   

  1. 1.中国农业大学 信息与电气工程学院,北京 100083
    2.国家数字渔业创新中心,北京 100083
  • 收稿日期:2020-04-26 修回日期:2020-08-31 出版日期:2020-09-30
  • 基金资助:
    中国工程院咨询研究项目(2019-ZD-5-04-03)
  • 通信作者: 李道亮(1971-),男,教授,博士,研究方向为农业信息先进感知与智能处理。电话:010-62737679。E-mail:dliangl@cau.edu.cn。

Recent Advances and Future Outlook for Artificial Intelligence in Aquaculture

LI Daoliang1,2(), LIU Chang1,2   

  1. 1.College of Information and Electronics Engineering, China Agricultural University, Beijing 100083, China
    2.National Innovation Center for Digital Fishery, Beijing 100083, China
  • Received:2020-04-26 Revised:2020-08-31 Online:2020-09-30

摘要:

中国水产养殖的生产模式已由粗放型向集约型转变,生产结构不断调整升级,生产水平不断提高。但较低的劳动生产率、生产效率和资源利用率,低质量的水产品以及缺乏安全保障等问题都严重制约中国水产养殖业的快速发展。利用现代信息技术,研究智能设备来实现精确、自动化和智能化的水产养殖,提高渔业生产力和资源利用率是解决上述矛盾的主要途径。水产养殖中的人工智能是研究利用计算机实现水产养殖的过程,也就是利用机器和计算机监视水下生物的生长,进行问题判断、讨论和分析,提出养殖相关决策,完成自动化养殖。为深入了解人工智能技术在水产养殖中的研究发展现状,本文从水产养殖的生命信息获取、水产生物生长调控与决策、鱼类疾病预测与诊断、水产养殖环境感知与调控,以及水产养殖水下机器人5个具体方面入手,结合生产中面临的实际问题,分析了人工智能在水产养殖中的研究应用现状和技术特点;阐述了人工智能应用的主要技术手段和原理,总结了近年来人工智能技术在水产养殖中的最新应用研究进展,分析了当前人工智能技术在水产养殖发展中面临的主要问题和挑战,并提出了推动水产养殖转型的主要建议,以期为加速推进中国渔业数字化、精准化和智慧化提供参考。

关键词: 水产养殖, 人工智能, 行为识别, 疾病诊断, 决策与控制, 水下机器人

Abstract:

The production of China's aquaculture has changed from extensive model to intensive model, the production structure is continuously adjusting and upgrading, and the production level has been continuously improved. However, as an important part of China's agricultural production, aquaculture plays an important role in promoting the development of China's agricultural economy. Low labor productivity, production efficiency and resource utilization, low-quality aquatic products, and the lack of safety guarantees have severely limited the rapid development of China's aquaculture industry. Using modern information technology and intelligent devices to realize precise, automated, and intelligent aquaculture, improving fishery productivity and resource utilization is the main way to solve the above contradictions. Artificial intelligence technology in aquaculture is to use the computer technology to realize the production process of aquaculture, monitor the growth of underwater organisms, judge, discuss and analyze problems, and then perform feeding, disease treatment, and breeding. In order to understand the development status and technical characteristics of artificial intelligence technology in aquaculture, in this article, five main aspects of aquaculture, i.e., life information acquisition, aquatic product growth regulation and decision-making, fish disease prediction and diagnosis, aquaculture environment perception and regulation, and aquaculture underwater robots, combined with the practical problems in aquaculture, were mainly focused on. The application principles and necessity of artificial intelligence technology in each aspect were explained. Commonly used technical methods were point out and the classic application cases were deeply analyzed. The main problems, bottlenecks and challenges in the current development of artificial intelligence technology in aquaculture were analyzed, including turbid water, multiple interference factors, corrosion of equipment, and movement of underwater animals, etc., and reasonable research directions for these potential challenges were pointed out. In addition, the main strategic strategies to promote the transformation of aquaculture were also proposed. The development of aquaculture is inseparable from artificial intelligence technology, this review can provide references to accelerate the advancement of digitalization, precision and intelligent aquaculture.

Key words: aquaculture, artificial intelligence, behavior recognition, prediction and diagnosis, decision and control, underwater robot

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