Farmers Disease Diagnostic and Reporting Portal:An AI-Based Mobile Platform for Crop Disease Screening

Abstract: A farmer who notices a damaged leaf needs both an initial assessment and a way to obtain further advice. This paper describes a mobile portal that connects these tasks through AI-assisted crop screening and structured case reporting. Farmers would record photographs, crop details, and the date of observation. A compact model would suggest possible disease categories for supported crops, while unclear images and uncertain cases would be referred for review. Each case would retain the original evidence, the model version, and any later assessment by a crop specialist. Offline storage would allow observations to be captured without a connection and submitted once connectivity returns. The study presents a system design rather than an implemented service. It defines requirements, processing steps, diagrams, and a plan for evaluating classification quality, synchronization, expert review, and farmer usability. Its contribution is a traceable route from the first observation to a reviewed response. Field trials are still needed to determine whether the design improves reporting or access to useful advice. A photograph-based suggestion would remain preliminary and would not replace field examination or laboratory confirmation when these are required.