A Review of Artificial Intelligence Applications in Smart Irrigation Management

Document Type : Review Article

Authors

zahra Ayyab Koushk Gozar

Seyyed Mohammad Reza Naghedifar

Ali Naghi Ziaei

Department of Water Science and Engineering, Faculty of Agriculture, Ferdowsi University of Mashhad, Mashhad, Iran

https://doi.org/10.22067/jwsd.v12i3.2506-1432

Abstract

In light of the increasing challenges posed by water scarcity, population growth, climate change, and the urgent need to enhance agricultural productivity, the adoption of advanced technologies such as Artificial Intelligence (AI) in irrigation management is regarded as a transformative approach. This study aims to investigate the role of AI in optimizing irrigation and managing water resources in agriculture by analyzing various dimensions, including the background of irrigation, modern methodologies, data collection and analysis, water allocation algorithms, performance monitoring, challenges, opportunities, and the provision of strategic solutions. Through a systematic review of credible scientific articles, the present research examines technologies such as environmental sensors, the Internet of Things (IoT), machine learning, deep learning, and decision support systems, and evaluates their effectiveness in improving water use efficiency and increasing crop yield. The results indicate that intelligent irrigation systems can reduce water consumption by 20 to 40 percent while enhancing crop performance. Furthermore, the findings reveal that key challenges to the application of AI in smart irrigation management include lack of infrastructure, high initial costs, and insufficient accurate data. Finally, the study proposes recommendations for the localized development of these systems, emphasizing supportive policies, technology localization, and farmer empowerment.

Keywords

Artificial Intelligence

Precision Irrigation

Smart Agriculture

Machine Learning

Water Resource Management

Subjects

• Irrigation and Agriculture

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