Automated Leaf Damage Assessment and Crop Classification Using Convolutional Neural Networks

The Automated Leaf Damage Assessment and Crop Classification system using Convolutional Neural Networks (CNN) is designed to enhance agricultural productivity through intelligent monitoring and analysis of crop health. The system captures images of plant leaves using a camera and processes them using a CNN model to detect diseases and classify crops accurately. It also integrates soil moisture sensing for real-time irrigation control and uses a water pump to maintain optimal soil conditions. Additionally, pest control mechanisms are activated when diseases are detected, and GSM communication provides alerts to farmers. This system reduces manual effort, improves accuracy in disease detection, and supports smart farming practices. Future enhancements include mobile applications, drone-based monitoring, and large-scale agricultural deployment.