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International Advanced Research Journal in Science, Engineering and Technology
International Advanced Research Journal in Science, Engineering and Technology A Monthly Peer-Reviewed Multidisciplinary Journal
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← Back to VOLUME 13, ISSUE 10, OCTOBER 2026

Farmers Disease Diagnostic / Reporting Portal: An AI – Based Mobile Portal

Miss. Gayatri R. Patil, Asst. Prof. Chetana M. Kawale

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Abstract: Farmers Disease Diagnostic/Reporting Portal is an AI-based mobile portal designed to help farmers identify and report crop diseases in an easy, fast, and accessible manner. Crop disetthjaases can significantly affect agricultural production and may cause financial losses when they are not identified and managed at an early stage. Farmers, especially in rural areas, may face difficulties in obtaining timely information about crop diseases and appropriate management practices.
The proposed system allows farmers to upload or capture an image of an affected crop or plant through a mobile portal. The uploaded image is processed using image processing and Artificial Intelligence techniques to identify possible crop diseases. Based on the analysis, the system provides the predicted disease along with relevant information and recommended management measures. The portal also provides a disease reporting facility through which farmers can submit details about affected crops, disease symptoms, location, and other relevant information.
The collected reports can be stored in a centralized database and accessed by authorized administrators or agricultural experts for monitoring and analysis. The system aims to create a digital connection between farmers, disease information, and agricultural support services. By integrating AI- based disease detection with mobile-based reporting, the proposed portal can support early identification of crop diseases, improve access to agricultural information, and assist in better crop disease management.

Keywords: Artificial Intelligence, Crop Disease Detection, Farmers, Mobile Portal, Disease Diagnosis, Image Processing, Machine Learning, Crop Health, Disease Reporting, Agricultural Technology, Digital Agriculture, Plant Disease Management.

How to Cite:

[1] Miss. Gayatri R. Patil, Asst. Prof. Chetana M. Kawale, “Farmers Disease Diagnostic / Reporting Portal: An AI – Based Mobile Portal,” International Advanced Research Journal in Science, Engineering and Technology (IARJSET), DOI: 10.17148/IARJSET.2026.131005

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