Explainable AI for Early Disease Detection in Precision Agriculture

This project aims to develop Explainable Artificial Intelligence (XAI) models for early disease detection in crops using image analysis. By leveraging machine learning and data science, advanced AI models that not only identify potential diseases in crops based on digital images captured by drones or smartphones but also explain their reasoning in a clear and interpretable manner for farmers can be developed. The project will involve collecting a large dataset of labeled images of healthy and diseased crops under various conditions. Deep learning techniques like convolutional neural networks (CNNs) will be used to train the AI model for accurate disease detection. However, the crucial element will be integrating Explainable AI methods to provide human-understandable explanations for the model's decisions.