Identification of paddy plant diseases using Artificial Intelligence (AI)

The identification of diseases in paddy plants is a challenging task, and early detection is critical for effective control and management. Artificial intelligence (AI) and the internet of things may fundamentally alter how diseases are detected in rice plants (IoT). In this study, we propose an AI and IoT-based system for identifying diseases in paddy plants. A network of sensors, cameras, and microcontrollers make up the system, which gathers information on a variety of factors like temperature, humidity, and leaf colour. The machine learning model analyses this data to diagnose the disease in the paddy plant using image recognition techniques. The system allows farmers to remotely access it from any location and monitor their crops. The suggested system is anticipated to increase the precision and effectiveness of disease diagnosis in paddy plants, assisting farmers in taking prompt action to stop the spread of disease and boost crop yield.