Investigating Internet of Things and Artificial Intelligence-Based Approaches to Smart Irrigation System Optimisation for Agricultural Water Resource Management - Balassem Zaid Ajzan; Alkhafaij Mahdi Abdulkhudur; Raju Nadimpalli Venkata Ganapathi (SHS Web of Conferences)
This paper presents a promising approach to optimizing agricultural water resource management. The study investigates how IoT and AI can enhance irrigation practices, ensuring water is used efficiently and sustainably in agriculture. Existing methods often fall short due to their inability to dynamically adjust to real-time conditions, leading to over-irrigation or under-irrigation, which can harm crop yield and waste resources. To address these issues, we propose an Agricultural Water Resource Management using AI (AWRM-AI) system. This system leverages IoT sensors to monitor environmental variables and uses AI algorithms to analyze this data and make real-time irrigation decisions. By implementing AWRM-AI, we can optimize water usage, reduce waste, and ensure crops receive the precise amount of water needed at the right time. Our findings demonstrate that the AWRM-AI system significantly improves water-use efficiency, leading to better crop yields and a reduction in water wastage. This approach not only conserves valuable water resources but also enhances the sustainability of agricultural practices, making it a vital tool for modern agriculture.