Design of Smart Irrigation System Based on MLA
Gunjan Bobade, Chetan Dhule, Ritika Khadilkar, Rahul Agrawal, Nekita Chavhan Morris
Abstract
Agriculture has always been a fundamental aspectof Indian culture, making it the country's most efficient andimportant occupation. Over the years, smart and advanced techniques have been developed to optimize farming practices, and one such development is the smart irrigation system. This system has become increasingly popular among farmers as it helps them reduce water usage while maximizing profits. This has not only helped farmers increase their profits but has also made farming a more sustainable and eco-friendly occupation. The proposed Model is a AI Based Smart irrigation System, which utilizes machine learning algorithms (ML) to predict soil moisture levels based on parameters such as temperature, humidity, and soil moisture. This system is developed through cloud computing, allowing for real-time data to be extracted from (IoT) sensors. The decision tree, a supervised learning algorithm, is applied to the data to classify or predict values. The result obtained from the decision tree helps predict the appropriate amount of water needed for the crops, gives the accuracy of 90% It allowing for efficient water usage and promoting yield growth.