AI Based Real-Time Crop Image Analytics for Crop Insurance-PMFBY

Abstract

This project presents an AIbased real-time crop image analytics system designed to support crop insurance under the Pradhan Mantri Fasal Bima Yojana (PMFBY). The system enhances crop assessment by automatically analyzing images to detect crop health, diseases, and damage using artificial intelligence, computer vision, and deep learning techniques. Users can upload crop images through a web-based interface, and the system provides instant and accurate results, enabling quick evaluation of crop conditions. Traditional crop assessment methodsrely on manual inspection, which is time-consuming, labor-intensive, and prone to human errors, often leading to delays in insurance claim settlements and lack of transparency. These limitations highlight the need for an automated, efficient, and reliable solution that can perform real-time analysis with minimal human intervention.The proposed system addresses this need by integrating technologies such as Python, Flask, OpenCV, and deep learning models to deliver fast and consistent outcomes. It helps farmers, insurance agents, and authorities make better decisions by providing data-driven insights. By reducing human effort, minimizing errors, and accelerating the verification process, the system improves the overall efficiency and reliability of crop insurance assessment under PMFBY, making it a scalable