浙江农业科学

浙江农业科学 ›› 2025, Vol. 66 ›› Issue (9): 2280-2286.DOI: 10.16178/j.issn.0528-9017.20240734

• 资源与环境 • 上一篇    下一篇

智能灌溉算法在农业现代化中的机遇与挑战

章毅1(), 袁潇潇2, 曹栋栋3, 黄玉韬3, 梁立军4,*()   

  1. 1.国科大杭州高等研究院,浙江 杭州 310024
    2.杭州第一技师学院,浙江 杭州 310023
    3.浙江农科种业有限公司,浙江 杭州 310021
    4.杭州电子科技大学 自动化学院,浙江 杭州 310012
  • 收稿日期:2024-09-14 出版日期:2025-09-11 发布日期:2025-10-14
  • 通讯作者: 梁立军(1987—),男,副研究员,博士,研究方向为人工智能和智慧灌溉、水处理膜材料设计的交叉研究, E-mail: llj@hdu.edu.cn。
  • 作者简介:章毅(1981—),男,高级工程师,硕士,研究方向为数字农业研究与成果推广, E-mail: 549984164@qq.com。
  • 基金资助:
    杭州市农业与社会发展领域科研计划项目(20241203A05)

Opportunities and challenges of intelligent irrigation algorithms in agricultural modernization

ZHANG Yi1(), YUAN Xiaoxiao2, CAO Dongdong3, HUANG Yutao3, LIANG Lijun4,*()   

  1. 1. Hangzhou Institute for Advanced Study, Hangzhou 310024, Zhejiang
    2. Hangzhou First Technician College, Hangzhou 310023, Zhejiang
    3. Hangzhou Nongke Seed Industry Co., Ltd., Hangzhou 310021, Zhejiang
    4. School of Automation, Hangzhou Dianzi University, Hangzhou 310012, Zhejiang
  • Received:2024-09-14 Online:2025-09-11 Published:2025-10-14

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摘要：

随着农业现代化的发展,传统的灌溉方式已经不能满足农业发展的需求,尤其是农业用水还面临着水资源短缺等情况,而智能灌溉技术可以很好地实现水资源的合理运用进而提升生产力和实现农业可持续发展。智能灌溉算法是确保智能灌溉系统高效运作和智能化的核心,算法依赖传感器技术收集数据,通过无线通信传输,利用机器学习和神经网络分析大数据,实现精确灌溉。然而,智能灌溉算法在数据质量、隐私保护及算法复杂性上仍存在多重难题。本文讨论并提出了一些关于提升数据质量、优化算法及推行政策扶持等的建议,以推动智能灌溉的广泛运用,为智能灌溉算法的发展方向提供一定的指导,实现农业现代化与可持续发展。

关键词: 智能灌溉算法, 模型, 机器学习, 数据分析处理

Abstract:

With the development of agricultural modernization, traditional irrigation methods can no longer meet the demands of agricultural development. Especially, agricultural water use is still facing water resource shortages and other situations. However, intelligent irrigation technology can well achieve the rational utilization of water resources, thereby enhancing productivity and realizing sustainable agricultural development. The intelligent irrigation algorithm is the core to ensure the efficient operation and intelligence of the intelligent irrigation system. The algorithm relies on sensor technology to collect data, transmits it through wireless communication, and uses machine learning and neural networks to analyze big data to achieve precise irrigation. However, intelligent irrigation algorithms still face multiple challenges in terms of data quality, privacy protection and algorithm complexity. This paper discussed and put forward some insights on improving data quality, optimizing algorithms and implementing policy support, in order to promote the wide application of intelligent irrigation, provide certain guidance for the development direction of intelligent irrigation algorithms, and achieve agricultural modernization and sustainable development.

Key words: intelligent irrigation algorithm, model, machine learning, data analysis and processing

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