Unlocking Water Conservation: Synergizing IoT and Machine Learning for Agricultural Irrigation Efficiency

The traditional irrigation method often results in excessive water usage and wastage, highlighting the urgent need for smarter irrigation solutions. Using the Internet of Things (IoT) and Machine Learning (ML) to their full capacity offers a viable way to automate irrigation procedures with little to no human involvement. This paper suggests an IoT-enabled Machine Learning recommendation system that is taught to maximize water efficiency and minimize farmer intervention. IoT sensors are placed in fields to gather accurate environmental and ground data, which is then processed on a cloud-based server using Machine Learning methods to provide farmers with customized irrigation recommendations. Incorporating a feedback mechanism ensures the system’s adaptability and robustness. By embracing IoT and ML technologies, farmers stand to benefit from significant improvements in water conservation, reduced operational costs, and enhanced agricultural productivity. This interdisciplinary approach not only promotes sustainable water management practices but also fosters innovation in precision agriculture, contributing to a more resilient and resource-efficient farming landscape.