Application for predicting plant diseases integrated with a recommendation system

Abstract

The project titled focuses on using machine learning techniques to identify diseases on plant leaves, coupled with developing a mobile application for practical application. The system for disease detection on plant leaves utilizes artificial intelligence (AI) and machine learning. The data includes images of diseased and healthy plant leaves, which are preprocessed and fed into a Convolutional Neural Network (CNN) model to detect common diseases. Results show that the model achieves high accuracy, providing disease names, symptoms, and effective treatment recommendations for farmers. The recommendation system includes treatment measures, prevention strategies, and farming practices improvement. Additionally, the system provides a plant care handbook for reference and real-world application. Future directions for system development include expanding the database to include more disease types and enhancing analytical capabilities. This technology not only protects crop productivity and quality but also promises to reduce losses caused by plant diseases, thereby enhancing efficiency and sustainability in agriculture production.