Smart Irrigation Systems: Optimizing Water Use with AI

Abdullah Mohammad Ghazi Khatib () and Bayan Mohamad Alshaib ()
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Abdullah Mohammad Ghazi Khatib: Damascus University
Bayan Mohamad Alshaib: Damascus University

Chapter Chapter 5 in Transforming Agriculture through Artificial Intelligence for Sustainable Food Systems, 2025, pp 73-93 from Springer

Abstract: Abstract This chapter focuses on the application of artificial intelligence (AI) in developing smart irrigation systems to address water scarcity and promote sustainable agriculture. It begins by outlining the global challenges of water management in agriculture and the need for more efficient irrigation practices. The chapter then explores various AI-powered technologies and techniques used in smart irrigation, including soil moisture sensors, weather forecasting models, and crop water stress detection systems. It discusses how machine learning algorithms can analyze data from multiple sources to create precise irrigation schedules tailored to specific crop needs and environmental conditions. The integration of smart irrigation systems with other precision agriculture technologies is examined, highlighting the potential for holistic farm management. The chapter also addresses the economic and environmental benefits of AI-driven irrigation, such as water conservation, reduced energy consumption, and improved crop yields. Finally, it considers the challenges of implementing smart irrigation systems, including infrastructure requirements, farmer adoption, and the need for ongoing system optimization. Graphical Abstract Fig. 5.1 Graphical Abstract—AI applications in smart irrigation systems Diagram illustrating various aspects of 'AI Applications in Smart Irrigation Systems' at the center. Connected concepts include 'Precision Agriculture Integration,' 'Water Conservation,' 'Improved Crop Yields,' 'Energy Efficiency,' 'System Optimization,' 'Farmer Adoption,' 'Implementation Challenges,' 'Crop Water Stress Detection,' 'Weather Forecasting Models,' and 'Soil Moisture Sensors.' Each concept is linked with lines to demonstrate relationships and their role in advancing smart irrigation systems. The diagram uses distinct colors to highlight different categories and areas of application. This Graphical Abstract illustrates the key components and considerations in applying artificial intelligence to smart irrigation systems. It highlights global challenges, AI-powered technologies, integration and benefits, and implementation challenges. The radial layout emphasizes the central role of AI in addressing irrigation challenges.

Keywords: Smart irrigation; Water management; Soil moisture sensors; Weather forecasting; Crop water stress; Machine learning; Precision agriculture; Water conservation; Crop yields (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-981-96-4795-8_5

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DOI: 10.1007/978-981-96-4795-8_5

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