This project introduces an innovative approach to plant disease detection using machine learning, specifically convolutional neural networks (CNNs). By analyzing digital images of plant leaves and incorporating environmental factors, the project can accurately detect diseases early on, promoting sustainable agriculture. The machine learning models are trained on a diverse dataset, ensuring adaptability across different crops and diseases. The project’s user-friendly interface allows farmers to receive real-time feedback, empowering them with actionable insights for effective crop management. Overall, this automated plant disease detection project aims to enhance crop productivity, reduce losses, and strengthen agricultural resilience.
