Collection of Real Time Observations & Photo of Crops (CROPIC)
Kartavya Desk Staff
Source: IE
Context: The Ministry of Agriculture and Farmers Welfare has launched CROPIC, a tech-driven initiative using AI to monitor crop health and automate crop loss assessment.
• The pilot phase will cover Kharif 2025 and Rabi 2025-26 in 50 selected districts.
About Collection of Real Time Observations & Photo of Crops (CROPIC):
• What is CROPIC? CROPIC stands for Collection of Real Time Observations & Photo of Crops. It is a mobile app-based initiative to photograph standing crops and analyse them using AI-powered image recognition.
• CROPIC stands for Collection of Real Time Observations & Photo of Crops. It is a mobile app-based initiative to photograph standing crops and analyse them using AI-powered image recognition.
• Developed By: Developed by the Union Ministry of Agriculture and Farmers’ Welfare under the Fund for Innovation and Technology (FIAT) of PMFBY.
• Objectives of CROPIC:
• Real-time monitoring of crop growth stages and health. Early identification of crop stress and potential yield loss. Automated assessment for timely insurance claims under PMFBY. Build a crop image signature database for machine learning models. Promote digital transformation and resilience in agriculture.
• Real-time monitoring of crop growth stages and health.
• Early identification of crop stress and potential yield loss.
• Automated assessment for timely insurance claims under PMFBY.
• Build a crop image signature database for machine learning models.
• Promote digital transformation and resilience in agriculture.
• How Will CROPIC Work?
• Farmer-Driven Photo Upload: Farmers will upload crop images 4–5 times during the crop cycle using the CROPIC mobile app, ensuring real-time, ground-level data capture. AI-Based Image Analysis: These photos are processed through an AI cloud engine that uses computer vision to detect crop type, growth stage, stress signs, and possible damages. Diagnostic Output Generation: The model generates precise diagnostics including crop condition, stage, stress indicators, and severity of loss based on visual markers. Web-Based Dashboard for Officials: A centralised digital dashboard displays analysed data for district/state-level officials to track crop health and emerging risks. Support for Insurance Claim Validation: The analysed images serve as verifiable evidence to aid fast, transparent, and automated processing of PMFBY compensation claims.
• Farmer-Driven Photo Upload: Farmers will upload crop images 4–5 times during the crop cycle using the CROPIC mobile app, ensuring real-time, ground-level data capture.
• AI-Based Image Analysis: These photos are processed through an AI cloud engine that uses computer vision to detect crop type, growth stage, stress signs, and possible damages.
• Diagnostic Output Generation: The model generates precise diagnostics including crop condition, stage, stress indicators, and severity of loss based on visual markers.
• Web-Based Dashboard for Officials: A centralised digital dashboard displays analysed data for district/state-level officials to track crop health and emerging risks.
• Support for Insurance Claim Validation: The analysed images serve as verifiable evidence to aid fast, transparent, and automated processing of PMFBY compensation claims.
• Key Features of CROPIC:
• Crowdsourced Data Collection: Data is sourced directly from farmers through mobile apps, ensuring local participation and wider coverage of farm-level realities. Photo-Analytics Engine with AI: The platform integrates machine learning and image recognition to identify disease, pest attacks, or yield-affecting anomalies. Dashboard for Visual Monitoring: Real-time analytics are mapped and visualised on a digital dashboard for authorities to intervene proactively. PMFBY Integration for Efficiency: The model links seamlessly with the Pradhan Mantri Fasal Bima Yojana to reduce human dependency and enable faster claim settlements. Pilot Coverage and Scalability: The initiative will initially cover 50 districts per season across different agro-climatic zones, focusing on 3 insured crops per district.
• Crowdsourced Data Collection: Data is sourced directly from farmers through mobile apps, ensuring local participation and wider coverage of farm-level realities.
• Photo-Analytics Engine with AI: The platform integrates machine learning and image recognition to identify disease, pest attacks, or yield-affecting anomalies.
• Dashboard for Visual Monitoring: Real-time analytics are mapped and visualised on a digital dashboard for authorities to intervene proactively.
• PMFBY Integration for Efficiency: The model links seamlessly with the Pradhan Mantri Fasal Bima Yojana to reduce human dependency and enable faster claim settlements.
• Pilot Coverage and Scalability: The initiative will initially cover 50 districts per season across different agro-climatic zones, focusing on 3 insured crops per district.