AI-Based AgriTech Web Application for Smart and Sustainable Agriculture

Global agriculture faces increasing challenges from climate variability, crop diseases, soil degradation, and inefficient resource utilization, which significantly affect productivity and sustainability, particularly for small and marginal farmers. This paper presents AgriTech, an integrated AI-based web application designed to support smart and sustainable agricultural practices through data-driven decision-making. The system integrates AI and machine learning techniques, including crop recommendation using soil and climatic parameters, convolutional neural network (CNN)-based plant disease detection, and crop yield prediction. Additional features, such as real-time weather advisory, digital marketplace integration, government scheme information, and a collaborative farmer community forum, enhance usability. Experimental evaluation demonstrates robust performance, achieving crop recommendation accuracy of 99.55%, disease detection accuracy of 92.3%, and a yield prediction RMSE of 0.47 t/ha. These results indicate that AgriTech can effectively assist farmers in improving productivity, reducing risk, and adopting sustainable agricultural practices.