Pipeline
Aerial layer (RGB → orthomosaic → vegetation indices → zoning)
The UAV captures RGB imagery over a target plot. The pipeline:
- RGB capture + photogrammetry — stitch overlapping captures into an orthomosaic.
- Vegetation indices — compute Excess Green (
ExG) and Visible Atmospherically Resistant Index (VARI) from the RGB orthomosaic. RGB-only because dedicated multispectral sensors weren’t available. - Zoning — K-means cluster the index map into management zones (low / mid / high vigour).
Ground layer (ESP32 + Modbus + GPS waypoints)
An ESP32 ground module carries a Modbus soil sensor and a GPS receiver. The rover follows a waypoint plan over the zones identified from the air. At each waypoint it samples the soil and runs an on-device ML model that estimates NPK (nitrogen / phosphorus / potassium) from the multivariate sensor reading.
Dashboard
Firebase + Vercel dashboard surfaces the orthomosaic + zoning overlay alongside the ground-truth NPK readings. A multilingual AI assistant answers farmer queries in their preferred language and grounds answers in the current plot data.
Review paper
Alongside the build, I authored a review paper on affordable, industry-standard precision-agriculture adoption for smallholder farms in Maharashtra — surveying what’s realistically deployable at that scale and cost.
Team
Heramb · Pranav · Paresh · me — MIT-WPU Department of Electronics & Communication Engineering, AY 2025–26.