Abstract :

AI Based Real-Time Crop Image Analytics For Crop Insurance – PMFBY Is An Intelligent Web Application Developed To Support Farmers In The Early Detection Of Crop Diseases While Providing Guidance Related To Crop Insurance. In Traditional Farming, Disease Identification Mainly Depends On Manual Field Inspection, Which Is Time-consuming, Labor-intensive, And Often Delays Timely Treatment. Such Delays May Reduce Crop Productivity And Result In Financial Losses For Farmers. To Overcome These Challenges, The Proposed System Enables Farmers To Upload Crop Leaf Images And Receive Real-time Disease Analysis Along With Suitable Recommendations. A ResNet50-based Convolutional Neural Network (CNN) Is Used To Accurately Classify Crop Diseases From Leaf Images, While OpenCV Is Employed To Estimate The Visible Affected Leaf Area And Determine The Severity Of Infection. Based On The Severity Level, The Application Provides Preventive Measures, Treatment Recommendations, And Guidance To Consult Agricultural Experts. For Crops Showing Severe Visible Damage, The System Also Provides Information About The Pradhan Mantri Fasal Bima Yojana (PMFBY) And Directs Farmers To Official Crop Insurance Resources. The Application Is Implemented Using Python, Flask, TensorFlow, Keras, OpenCV, HTML, CSS, JavaScript, And SQLite, Providing A Simple And User-friendly Platform For Realtime Crop Disease Analysis. The Proposed System Supports Timely Decision-making, Improves Crop Health Management. KEYWORDS: Crop Disease Detection, Crop Image Analytics, Deep Learning, ResNet50, OpenCV, Computer Vision, Crop Insurance, PMFBY, Flask Web Application

Published:

01-8-2026

Issue:

Vol. 26 No. 8 (2026)

Page Nos:

1163 - 1171

Section:

Articles

License:

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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