AI Based Plant Disease Monitoring Using Maching Learning

Plants play a crucial role in human life as they are a major source of energy and help reduce the effects of global warming. However, plants are increasingly affected by diseases such as bacterial spot, late blight, and Septoria leaf spot, which significantly reduce crop productivity. Therefore, early detection of plant diseases is essential in agriculture to ensure effective disease management. Identifying diseases at an early stage helps prevent their spread and minimizes crop loss. The main objective of this project is to detect plant leaf diseases using Machine Learning techniques applied to images and videos. For image-based detection, a Random Forest classifier, a machine learning algorithm, is used for classification. For video-based detection, the proposed method employs ResNet50, a deep learning algorithm. These techniques provide prediction results evaluated using performance metrics such as accuracy, precision, and efficiency. This system can be applied in agriculture fields, nurseries, college gardens, and similar environments