Advanced Agro Management Using Machine Learning and IoT

In this research study, we aim to create a revolutionary agricultural management portal that is capable of identifying diseases in leaves, flowers, and fruits deploying an Arduino Board, an Esp32-camera module to collect real-time visuals and machine learning algorithms. Through the integration of sensors and cameras into the agricultural environment, our system can collect information on crop development and health as well as recognize and diagnose illnesses. As a result, choices like irrigation strategies, fertilization, and pest control can be made knowing exactly what diseases are present and how they might impact crop health thanks to machine learning algorithms like InceptionV3.Through an all-inclusive Full Stack web application, which will identify the ailment, prescribe items for treatment, and provide the option to purchase them.The technology utilized in this research is projected to improve sustainable crop growing practices, raise flower, fruit, and leaf yields, and minimize crop losses, as well as provide a trained consultation alternative for one-on-one personal assistance.