Artificial Intelligence-Enabled Leaves Disease Detection and Classification Model for Smart Agriculture

The rapid growth of Artificial Intelligence (AI) in agriculture is transforming traditional farming into a more efficient and technology-driven process. One of the most critical challenges in crop management is the timely detection of leaf diseases, which, if left untreated, can cause severe yield losses and affect overall food security. This study presents an Artificial Intelligence-Enabled Leaves Disease Detection and Classification Model for Smart Agriculture, designed to automatically identify and classify various plant leaf diseases with high accuracy. The model incorporates image processing and deep learning techniques, particularly convolutional neural networks (CNNs), to extract disease-specific features from leaf images. By providing real-time analysis and decision support, the system enables farmers to take proactive measures in disease management, reducing dependency on manual inspections and minimizing the risk of human error. The proposed approach not only improves crop health monitoring but also enhances productivity, sustainability, and profitability in smart agriculture practices.