Precision Irrigation Management Using Machine Learning and Digital Farming Solutions

AgriEngineering

Omosun Yerima¹  Mohamad Shukri Zainal Abidin²  Oliver Hensel³  Abozar Nasirahmadi³  Ajibade Sylvester Ayobami⁴  Emmanuel Abiodun Abioye⁵  Travis J. Esau⁶  Olakunle Elijah⁷ 

[1] College of Engineering, Micheal Okpara University of Agriculture, Umudike 7267, Abia State, Nigeria;Control and Mechatronics Engineering Division, School of Electrical Engineering, Faculty of Engineering, Universiti Teknologi, Skudai 81310, Malaysia;Department of Agricultural and Biosystems Engineering, University of Kassel, 37213 Witzenhausen, Germany;Department of Geography and Remote Sensing, Nigerian Defense Academy, Kaduna 800281, Nigeria;Electrical/Electronic Engineering Department, Akanu Ibiam Federal Polytechnic, Unwana 480854, Ebonyi State, Nigeria;Engineering Department, Faculty of Agriculture, Dalhousie University, Truro, NS B2N 5E3, Canada;Wireless Communication Center, School of Electrical Engineering, Faculty of Engineering, Universiti Teknologi, Skudai 81310, Malaysia;

关键词: precision irrigation;    water;    machine learning;    mobile app;    web app;    smart agriculture;   

DOI  :  10.3390/agriengineering4010006

来源: DOAJ

【 摘 要 】

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.

【 授权许可】

Unknown