Paper Contents
Abstract
CropIntel is an intelligent, real-time system developed to assist farmers in identifying grape leaf diseases and analyzing soil health. The proposed model employs a custom Convolutional Neural Network (CNN) for image-based disease detection and uses a rule-based approach for interpreting soil nutrient levels (N, P, K, and pH) derived from lab reports. The backend, built with FastAPI, enables fast communication between the prediction model and the user interface. All input and output data are stored securely in a MySQL database for scalability and traceability. The systems design emphasizes usability, accuracy, and cost-effectiveness, offering an accessible solution for grape farmers. By integrating deep learning with practical agricultural insights, CropIntel promotes early disease detection, informed fertilizer management, and sustainable farming practices, ultimately improving yield quality and reducing economic losses in the viticulture sector.
Copyright
Copyright © 2025 Neha Vilas Sangamnere , Tejash Manoj Sananse , Pranav Jagannath Shevkar , Prachi Sanjay Sukenkar, Abhishek Ganesh Walke, Nivedita.R.Kakade. This is an open access article distributed under the Creative Commons Attribution License.
