SoilIntelligence

Precision agriculture decision support system. Analyses soil nutrient levels, predicts crop yield with uncertainty quantification, and prescribes exact fertiliser quantities — all backed by 244,000+ global soil samples and real-time market data.

What it does

1. Soil analysis — Assesses N, P, K, Ca, Mg, pH, organic carbon and gives an overall quality score
2. Yield prediction — Monte Carlo forecasting using Liebig's Law (limiting factor) with 90% confidence intervals
3. Fertiliser recommendations — Exact product quantities (DAP, Urea, MOP) with cost and ROI
4. Regional benchmarking — Compares your soil against 49k real African + 195k global reference samples
5. Risk assessment — Probability statements ("82% chance of positive ROI") with LOW/MODERATE/HIGH tiers

How it works

Soil test results or GPS coordinates
         ↓
Nutrient analysis + quality scoring
         ↓
Monte Carlo yield prediction (1000 simulations, 90% CI)
         ↓
Fertiliser prescription + ROI calculation
         ↓
PDF report for farmer

Data sources

Source	Coverage	Size
iSDA Africa	49,225 field samples with measured nutrients	10 MB
WoSIS Global	195,000+ modelled samples worldwide	14 MB
SoilGrids API	250m resolution soil properties (ISRIC)	Live
Open-Meteo	Weather forecasts and soil moisture	Live
FAO GIEWS	Crop price data	Live
World Bank	Fertiliser commodity prices	Live

Running locally

pip install -r requirements.txt
python web.py

Open http://127.0.0.1:8080.

Tech stack

• Backend: Flask, pandas, numpy, scipy
• Frontend: HTML/CSS/JS, Leaflet.js maps
• ML: Random forest benchmarking, Liebig's Law yield model, Monte Carlo uncertainty
• Reports: fpdf for PDF generation

License

MIT