Crop health analytics — Sugarcane
Satellite and drone imagery models for yield, stress and disease. Delivered for a sugarcane client in Sanand.
- Location
- Sanand
- Year
- 2020
- Duration
- 9 weeks
- Team
- 3 engineers
- 12%
- yield uplift
- 111k
- hectares
- 31k
- farmers
The challenge
The sugarcane team was relying on manual effort that could not keep up with volume, and every miss had a direct cost.
What we built
We ran a two-week discovery sprint, then built and fielded the system end to end on PyTorch, GDAL and rasterio, with operator training and an SLA.
Delivery timeline
Phase 1
Discovery sprint and site survey
Phase 2
Prototype built and tested in the Motera lab
Phase 3
Pilot on site with before/after measurement
Phase 4
Scale-out, training and handover
Highlights
- Operator training delivered in Gujarati, Hindi and English
- Designed, built and supported from Motera, Ahmedabad
- Before-and-after measurements agreed with the client up front
- Integrated with existing PLC, ERP or GIS systems — no rip-and-replace
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