Field Survey Photo Verification for Crop Insurance

• Head of Crop Insurance Claims
• Agri Claims Operations Manager
• Survey Agency Project Manager
• Fraud Control Lead, General Insurer

Crop insurance claims for localised calamities and post-harvest losses depend on field surveys, crop cutting experiments and the photos surveyors upload from the field. In a bad season, thousands of photos arrive within a few weeks, and claim teams cannot check every one for location, timing or reuse.

We build a verification layer that checks every survey photo and its metadata before a claim officer opens the file. It compares the photo's geotag with the plot boundary or survey number on record, checks the timestamp against the reported loss event and crop calendar, and confirms the visible crop matches the sowing declaration. A vision model describes visible damage such as lodging, waterlogging or pest attack, without estimating a payable loss. Perceptual hashing finds reused or near-duplicate photos across claims and seasons. Survey forms are read so their details can be compared with the photos. Each claim gets a checklist of passed and failed checks, and failed or uncertain items go to a claim officer.

• Geotag check against plot boundary or survey number coordinates
• Timestamp check against the reported event date and crop calendar
• Crop type recognition compared with the sowing declaration
• Visible damage description such as lodging, waterlogging or pest attack
• Duplicate and near-duplicate photo detection across claims and seasons
• Per-claim evidence checklist for claim officers

1. 01Receive the survey packetPhotos, metadata and survey forms arrive from the surveyor app or survey agency upload, grouped by claim or intimation number.
2. 02Check location and timeGeotags and timestamps are compared with the insured plot and the reported loss event.
3. 03Check crop and damageThe vision model confirms the crop type and describes visible damage in standard categories.
4. 04Check for reuseEach photo is compared with earlier photos across claims and seasons to find copies and near-copies.
5. 05Route by resultClaims where all checks pass go forward; failed or uncertain checks go to a claim officer or for re-survey.
6. 06Officer decision and recordThe claim officer decides with the checklist and photos in front of them, and the decision and evidence are logged.

1. Intake
   • Surveyor app or agency upload connector
   • EXIF and metadata extraction
   • Survey form OCR
2. Spatial and time checks
   • Plot boundary and survey number lookup
   • Geofence and distance check
   • Event and crop calendar rules
3. Vision
   • Crop type classifier
   • Damage category detector
   • Perceptual hash index for reuse detection
4. Review
   • Claim officer checklist screen
   • Re-survey request workflow
5. Records
   • Evidence store with original files
   • Audit log of checks and decisions

Claim officers and surveyors decide every claim. The system checks evidence and describes visible damage, but it never estimates payable loss or rejects a claim on its own; failed checks lead to review or re-survey, not automatic denial.

• Surveyor mobile app or survey agency portal
• Insurer claims system
• Land record and plot boundary data, where available
• National Crop Insurance Portal data exports, where available
• GIS tools for plot mapping

• No automatic claim rejection from any single check
• GPS drift tolerances agreed with the claims team
• Original files kept unchanged, with checks run on copies
• Farmer identity and location data restricted by role
• Regular sampling of passed claims by a senior claims officer

• Designed to support the photo, geotag and survey evidence practices described in PMFBY operational guidelines, without replacing the surveyor's assessment.
• Claim records and audit trails help insurers evidence fair claim handling under IRDAI expectations.

• Agriculture & Agritech

  Crop Disease Detection from Farmer Photos

  Suggest likely diseases, pests and nutrient problems from farmer photos sent on WhatsApp or an app, reply in the farmer's language, and route uncertain or dose questions to an agronomist.

• Agriculture & Agritech

  Land Record and KCC Loan Document Extraction

  Read Khatauni, 7/12, Jamabandi and other land records plus KCC loan papers, extract holdings and crops, convert local area units, and flag mismatches before a credit officer sanctions.

• Insurance

  Motor Claim Damage Assessment from Photos

  Detect damaged panels and damage types from guided claim photos, check them against the workshop estimate and pre-inspection images, and give surveyors a structured evidence pack.

• Insurance

  Tampered and Fraudulent Document Detection

  Score claim documents for signs of editing, fabrication and reuse, explain each signal, and route high-risk files to your investigation team instead of labelling anyone a fraudster.