Intelligent Irrigation System With Smart Farming Using Ml and Artificial Intelligence Techniques

Abstract Due to increase in population, there is a drastic changes in whether condition which also affects agricultural productivity which leads to raise in food demand and creates a significant problem for humanity. This study suggests an automated control system of smart farming uses artificial intelligence, IoT and machine learning to monitor and regulate several agricultural regions vital to the entire farming process to solve lower productivity. Finally, provide better visualization and monitoring of the environment around us, we offered a web application that combines the different data produced by the sensors with the forecast from our models. The ensemble learning algorithm (SVM-KNN) to make an accuracy rate of 90% rather than individual SVM and KNN was 72% and 76%, respectively.