Real-time Plant Disease Detection and Pesticide Application System Using IoT and CNN

Globally, farmers use pesticides for improved crop yield and quality. The manual method of applying pesticides cause fatigue, harm to farmers health and application of pesticides in an indefinite proportion on the crops may be less or more in quantity then requirement. This project is aimed to build a 2-D CNN model using deep learning algorithm for plant disease detection and also this research paper outlines the idea of integrating ESP-32 microcontroller with the plant disease detection model to automate the process of pesticide dispensing. This will use image recognition model to identify the damaged crop. By using this technique, the time and work of the farmer will be reduced.