Crop Suggestion and Disease Detection System using Random Forest and Convolutional Neural Network

Abstract: This study provides an extensive web and mobile-based application aimed at improving agriculture practice using crop suggestion, disease prediction, and farmer query answering. The system applies machine learning, image processing, and natural language processing concepts to present recommendatory information to farmers. Random Forest is applied for crop prediction with an accuracy rate of 99.14%, while CNN is applied for disease prediction. Moreover, an expert-consulting system through real-time chat-based query resolution links farmers with experts. This technology-based solution is designed to enhance crop yield, optimize farm decisions, and increase accessibility for farmers