期刊
AGRIENGINEERING
卷 4, 期 1, 页码 70-103出版社
MDPI
DOI: 10.3390/agriengineering4010006
关键词
precision irrigation; water; machine learning; mobile app; web app; smart agriculture; digitalization
Freshwater is crucial for agriculture and the integration of different machine learning models can optimize irrigation decision management. This paper reviews the research trend of machine learning techniques in sustainable irrigation management and discusses the use of digital farming solutions for remote monitoring and control.
Freshwater is essential for irrigation and the supply of nutrients for plant growth, in order to compensate for the inadequacies of rainfall. Agricultural activities utilize around 70% of the available freshwater. This underscores the importance of responsible management, using smart agricultural water technologies. The focus of this paper is to investigate research regarding the integration of different machine learning models that can provide optimal irrigation decision management. This article reviews the research trend and applicability of machine learning techniques, as well as the deployment of developed machine learning models for use by farmers toward sustainable irrigation management. It further discusses how digital farming solutions, such as mobile and web frameworks, can enable the management of smart irrigation processes, with the aim of reducing the stress faced by farmers and researchers due to the opportunity for remote monitoring and control. The challenges, as well as the future direction of research, are also discussed.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据