SoilGuard - Soil Health Monitoring & Agricultural ROI Platform

A comprehensive agricultural platform that combines satellite data analysis, weather monitoring, and market intelligence to help farmers optimize soil health and maximize ROI through data-driven decision making.

🌟 Features

Core Analysis

• 🛰️ Satellite Data Analysis: Google Earth Engine integration for vegetation and soil health monitoring
• 🌦️ Weather Intelligence: Real-time weather data with agricultural indices (GDD, drought risk, frost alerts)
• 📈 Market Analysis: Crop price monitoring and market sentiment analysis
• 🤖 AI-Powered Insights: Intelligent soil health assessment and crop recommendations using Gemini & Claude
• 📊 Comprehensive Dashboard: Interactive farm management with real-time analytics
• 🔄 Real-time Updates: Automated monitoring with alert systems

🆕 Spatial Zone Analysis

• 🗺️ Dynamic Grid System: Auto-generates analysis zones based on farm size
  • < 2 ha: 2×2 grid (4 zones) using Sentinel-2 (10m resolution)
  • 2-10 ha: 3×3 grid (9 zones) using Sentinel-2 (10m resolution)
  • 10-50 ha: 4×4 grid (16 zones) using Landsat (30m resolution)
  • 50+ ha: 5×5 grid (25 zones) using Landsat (30m resolution)
• 🎯 Zone-Level Recommendations: AI agents provide specific actions for each problem zone
• 🔥 Interactive Health Map: Satellite imagery overlay with color-coded zones showing exactly WHERE problems are

🆕 Analysis History & Persistence

• 💾 Database Storage: All soil health and ROI analyses are saved to Supabase
• 📜 Analysis History: View and compare past analyses for trend tracking
• 🔍 Historical Insights: Click any past analysis to view full details
• 📊 Trend Analysis: Track farm health improvements over time

🛠️ Tech Stack

Frontend:

• Next.js 14 (App Router)
• TypeScript
• Tailwind CSS
• React Components

Backend:

• FastAPI (Python)
• Supabase (Database & Auth)
• Google Earth Engine API
• OpenWeatherMap API
• Various commodity price APIs

AI & Analysis:

• Google Gemini API
• Anthropic Claude API
• Custom satellite data processing
• Agricultural algorithms

🚀 Quick Start

Prerequisites

• Node.js 18+ and npm
• Python 3.11+
• Git

1. Clone the Repository

git clone https://github.com/yourusername/larmms.git
cd larmms

2. Environment Setup

Copy the environment template and configure your API keys:

cp env.template .env
# Edit .env with your actual API keys (see API Setup section below)

3. Backend Setup

cd backend
pip install -r requirements.txt
uvicorn main:app --reload --host 0.0.0.0 --port 8000

4. Frontend Setup

cd frontend
npm install
npm run dev

5. Database Setup

# Run Supabase migrations
supabase db push

🔑 API Setup Guide

Required APIs

1. Supabase (Required)

Purpose: Database, Authentication, Real-time subscriptions

Setup Steps:

1. Go to supabase.com
2. Create a new project
3. Go to Settings → API
4. Copy your Project URL and API keys

Environment Variables:

NEXT_PUBLIC_SUPABASE_URL=your_project_url
NEXT_PUBLIC_SUPABASE_ANON_KEY=your_anon_key
SUPABASE_SERVICE_ROLE_KEY=your_service_role_key

Cost: Free tier (up to 50MB database, 100MB file storage)

---

Optional APIs (Graceful Fallbacks Available)

2. Google Earth Engine (Optional)

Purpose: Satellite imagery analysis for soil and vegetation monitoring

Setup Steps:

1. Go to Google Cloud Console
2. Create a new project
3. Enable Earth Engine API
4. Set up authentication:

   pip install earthengine-api
   earthengine authenticate

Environment Variables:

GOOGLE_CLOUD_PROJECT_ID=your_project_id

Cost: Free for research/non-commercial (25,000 API calls/day)

3. OpenWeatherMap (Optional)

Purpose: Weather data and agricultural forecasting

Setup Steps:

1. Go to OpenWeatherMap
2. Sign up for free account
3. Generate API key

Environment Variables:

OPENWEATHERMAP_API_KEY=your_api_key

Cost: Free tier (1,000 calls/day), $40/month for 100k calls

4. Commodity Price APIs (Optional) - Multiple Free Tiers Available

4a. Alpha Vantage (RECOMMENDED)

• Website: alphavantage.co
• Cost: 25 requests/day FREE, then $49.99/month unlimited
• Perfect for development and light production use
• Variable: ALPHA_VANTAGE_API_KEY

4b. Twelve Data (Best Free Tier)

• Website: twelvedata.com/pricing
• Cost: 800 requests/day FREE, excellent coverage
• Variable: TWELVE_DATA_API_KEY

4c. Financial Modeling Prep

• Website: financialmodelingprep.com
• Cost: 250 requests/day FREE
• Variable: FMP_API_KEY

4d. Commodities API (Paid Only)

• Website: commodities-api.com
• Cost: 7-day free trial only, then $49.99/month minimum
• Variable: COMMODITIES_API_KEY

5. AI APIs (Optional)

5a. Google Gemini

• Website: Google AI Studio
• Cost: Free tier (15 requests/minute), pay-per-use beyond
• Variable: GOOGLE_GEMINI_API_KEY

5b. Anthropic Claude

• Website: console.anthropic.com
• Cost: Pay-per-use ($3/million input tokens)
• Variable: ANTHROPIC_API_KEY

5c. OpenAI

• Website: platform.openai.com
• Cost: Pay-per-use ($0.50-$20/million tokens depending on model)
• Variable: OPENAI_API_KEY

💰 Cost Breakdown

Free Tier (Recommended for Development)

• Supabase: Free
• Google Earth Engine: Free (research use)
• OpenWeatherMap: Free (1k calls/day)
• All other APIs: Demo data fallbacks
• Total: $0/month

Production Tier (Recommended for Live Usage)

• Supabase Pro: $25/month
• OpenWeatherMap: $40/month (100k calls)
• Alpha Vantage: $49.99/month OR use free tier (25 calls/day)
• AI APIs: ~$10-50/month (depending on usage)
• Total: ~$75-165/month (or ~$75/month with free commodity API tier)

🏗️ Project Structure

SoilGuard/
├── frontend/                    # Next.js frontend application
│   ├── src/
│   │   ├── app/                # App router pages
│   │   │   └── dashboard/      # Farm management pages
│   │   ├── components/
│   │   │   ├── Analysis/       # SoilHealthDisplay, ROIDisplay, AnalysisHistory, ZoneMapOverlay
│   │   │   ├── Map/            # Interactive maps and location picker
│   │   │   └── FarmerDashboard/# Health gauges, action cards, zone alerts
│   │   └── lib/                # API client, Supabase config, utilities
├── backend/                    # FastAPI backend application
│   ├── routers/
│   │   ├── analysis.py        # Soil health, ROI, zonal analysis endpoints + history
│   │   ├── farms.py           # Farm CRUD operations
│   │   └── auth.py            # Authentication endpoints
│   ├── services/
│   │   ├── satellite_service.py    # Google Earth Engine integration
│   │   ├── spatial_grid.py         # 🆕 Dynamic zone grid generation
│   │   ├── soil_health_agent.py    # AI soil analysis with zone recommendations
│   │   ├── roi_agent.py            # AI crop ROI analysis
│   │   └── ai_config.py            # Gemini + Claude configuration
│   ├── utils/
│   │   ├── database.py             # 🆕 Supabase client for persistence
│   │   └── satellite_calculations.py
│   └── requirements.txt
├── supabase/
│   └── migrations/
│       ├── 001_initial_schema.sql      # Users, farms tables
│       └── 002_analysis_tables.sql     # 🆕 soil_health_analyses, roi_analyses tables
├── backend/env.example         # Backend environment template
├── frontend/env.example        # Frontend environment template
└── README.md

🧪 Testing the Platform

1. Check Service Status

curl http://localhost:8000/health
curl http://localhost:8000/api/v1/analysis/status

2. Test Farm Creation

1. Open http://localhost:3000
2. Register/Login
3. Add a new farm with pin drop location
4. View satellite analysis

3. Test Analysis Pipeline

The platform automatically processes:

• Satellite vegetation indices (NDVI, NDWI, SAVI, EVI, etc.)
• Zone-based health scoring (dynamic grid based on farm size)
• Weather risk assessment
• Market price analysis
• AI-powered recommendations with zone-specific actions

4. Test Analysis History

1. Run a complete analysis on a farm
2. Expand the "Analysis History" section on the farm page
3. View past analyses and click to see full details
4. Compare trends over time

🚀 Deployment

Frontend (Vercel)

# Deploy to Vercel
npm run build
vercel --prod

Backend (Railway/Fly.io)

# Deploy to Railway
railway login
railway init
railway up

🤝 Contributing

1. Fork the repository
2. Create a feature branch: git checkout -b feature/amazing-feature
3. Commit changes: git commit -m 'Add amazing feature'
4. Push to branch: git push origin feature/amazing-feature
5. Open a Pull Request

Built with ❤️ for sustainable agriculture and data-driven farming