This systematic review critically evaluates the current state and future potential of real-time, end-to-end smart, and automated irrigation management systems, focusing on integrating the Internet of Things (IoTs) and machine learning technologies for enhanced agricultural water use efficiency and crop productivity. In this review, the automation of each component is examined in the irrigation management pipeline from data collection to application while analyzing its effectiveness, efficiency, and integration with various precision agriculture technologies. It also investigates the role of the interoperability, standardization, and cybersecurity of IoT-based automated solutions for irrigation applications. Furthermore, in this review, the existing gaps are identified and solutions are proposed for seamless integration across multiple sensor suites for automated systems, aiming to achieve fully autonomous and scalable irrigation management. The findings highlight the transformative potential of automated irrigation systems to address global food challenges by optimizing water use and maximizing crop yields.

Irrigation is the artificial application of water to crops to supply moisture. With rising drought indices and rapid population expansion, the need for irrigation water for food production is growing. Nonetheless, irrigated agriculture is battling several issues that have resulted in poor performance, inefficient water usage, and low crop water production. Improving water use efficiency in irrigated agriculture necessitates using technology that decreases water losses, matches available supplies to demand, and tracks performance. Geographical Information Systems (GIS) and Remote Sensing (RS) allow for effectively managing water and land resources for irrigation. Current GIS and RS uses in irrigation systems are covered in this study, covering land suitability for irrigation, crop water needs, irrigation scheduling, performance evaluation, and other related applications. The future potential of GIS and RS applications for sustainable irrigation water management are highlighted. This paper offers relevant information for researchers, irrigators, and policymakers on using GIS and RS in irrigation water management and how technological improvements will change irrigation water management to enhance water usage efficiency.