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🌾 AgriSense AI

The Future of Smart Farming

AI-powered crop yield prediction, real-time IoT monitoring, disease detection, and intelligent farm analytics — all in one platform.

Python FastAPI React TypeScript PostgreSQL License

Features • Tech Stack • Getting Started • Project Structure • API Reference • Screenshots • Contributing

✨ Features

🤖 Machine Learning Yield Prediction

  • Extra Trees Regression model trained on global crop data
  • Predicts yield (hg/ha) based on region, crop type, rainfall, temperature, and pesticide usage
  • AI-generated natural language explanations of predictions
  • Text-to-speech output for accessibility

🦠 Disease Detection

  • Upload crop leaf images for instant AI-powered classification
  • Identifies diseases with confidence scores
  • Provides treatment recommendations
  • Maintains detection history per farm

📡 IoT Sensor Dashboard

  • Real-time telemetry: temperature, humidity, soil moisture, pH, rainfall, light
  • Live auto-refreshing data (10s intervals)
  • Interactive time-series charts (Recharts)
  • Supports multiple farms with sensor history

📊 Analytics & Reports

  • Historical vs predicted yield comparison
  • Temperature vs soil moisture correlation analysis
  • Per-farm statistical averages
  • Beautiful gradient charts and data visualizations

🌍 Multi-Language Support (i18n)

  • 9 languages: English, हिंदी, বাংলা, ଓଡ଼ିଆ, اردو, Français, Español, தமிழ், తెలుగు
  • Instant language switching from Settings page
  • All pages fully translated (Dashboard, Farms, Prediction, Disease, Sensors, Analytics)

🏡 Farm Management

  • Create, view, and manage multiple farms
  • Track location (lat/long), area, and primary crop
  • GPS coordinates for weather and map integrations

👤 User Profile & Authentication

  • JWT-based authentication (register/login)
  • Editable profile with persistent save to database
  • Role-based user system (Farmer, Agricultural Officer, Admin)

🎨 Premium UI/UX

  • Dark/Light theme toggle
  • Glassmorphism design with animated gradients
  • Responsive layout with mobile support
  • Framer Motion animations throughout
  • Modern landing page with feature showcase

🛠 Tech Stack

Frontend

Technology Purpose
React 19 UI framework
TypeScript 6 Type safety
Vite 8 Build tool & dev server
TailwindCSS 3 Utility-first styling
Framer Motion Animations
React Router 7 Client-side routing
TanStack React Query Server state management
Recharts Data visualization
React Hook Form + Zod Form validation
react-i18next Internationalization
Leaflet Maps (installed)
Axios HTTP client
Radix UI Accessible headless components

Backend

Technology Purpose
FastAPI Async Python web framework
SQLAlchemy 2 Async ORM
Alembic Database migrations
PostgreSQL Database (via Supabase)
AsyncPG Async PostgreSQL driver
scikit-learn ML model (Extra Trees)
Pandas / NumPy Data processing
Joblib Model serialization
python-jose JWT token handling
Passlib + Bcrypt Password hashing
Pydantic v2 Data validation
Loguru Structured logging

🚀 Getting Started

Prerequisites

  • Python 3.10+
  • Node.js 18+ & npm
  • PostgreSQL database (or a free Supabase project)

1. Clone the Repository

git clone https://github.com/sheikhwasimuddin/AgriSense.git
cd AgriSense

2. Backend Setup

cd backend

# Create virtual environment
python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

# Install dependencies
pip install -r requirements.txt

# Configure environment
cp .env.example .env
# Edit .env with your database credentials (see Environment Variables below)

# Run database migrations
alembic upgrade head

# Seed sample data (optional)
python seed_db.py

# Start the server
uvicorn main:app --reload --port 8000

3. Frontend Setup

cd frontend

# Install dependencies
npm install

# Start development server
npm run dev

The app will be available at http://localhost:5173

⚙️ Environment Variables

Create a .env file in the backend/ directory:

# Database (Supabase PostgreSQL)
SUPABASE_URL=https://your-project-ref.supabase.co
SUPABASE_ANON_KEY=your-anon-key
DATABASE_URL=postgresql+asyncpg://postgres:password@db.your-project-ref.supabase.co:5432/postgres

# Authentication
JWT_SECRET_KEY=your_jwt_secret_key
ALGORITHM=HS256
ACCESS_TOKEN_EXPIRE_MINUTES=30

📁 Project Structure

AgriSense/
├── backend/
│   ├── api/                    # FastAPI route handlers
│   │   ├── auth.py             # Authentication (register, login, profile)
│   │   ├── farms.py            # Farm CRUD operations
│   │   ├── prediction.py       # ML yield prediction endpoint
│   │   ├── disease.py          # Disease detection endpoint
│   │   ├── sensors.py          # IoT sensor data endpoints
│   │   └── analytics.py        # Analytics aggregation
│   ├── core/
│   │   ├── config.py           # Pydantic settings
│   │   ├── database.py         # Async SQLAlchemy engine
│   │   ├── logger.py           # Loguru configuration
│   │   └── security.py         # JWT & password utilities
│   ├── db/
│   │   ├── models.py           # SQLAlchemy ORM models
│   │   ├── schemas.py          # Pydantic request/response schemas
│   │   ├── crud.py             # Database operations
│   │   └── migrations/         # Alembic migration scripts
│   ├── ml/
│   │   ├── predictor.py        # ML model loading & inference
│   │   ├── pipeline.pkl        # Trained Extra Trees pipeline
│   │   └── best_model.pkl      # Best model checkpoint
│   ├── main.py                 # FastAPI app entry point
│   ├── seed_db.py              # Database seeder
│   ├── requirements.txt
│   └── .env.example
│
├── frontend/
│   ├── src/
│   │   ├── components/
│   │   │   ├── layout/
│   │   │   │   ├── Sidebar.tsx     # Navigation sidebar
│   │   │   │   ├── Navbar.tsx      # Top navigation bar
│   │   │   │   └── MainLayout.tsx  # App shell layout
│   │   │   ├── ui/                 # Radix UI components (shadcn/ui)
│   │   │   └── theme-provider.tsx  # Dark/Light theme context
│   │   ├── pages/
│   │   │   ├── Home.tsx            # Public landing page
│   │   │   ├── Login.tsx           # Authentication - login
│   │   │   ├── Register.tsx        # Authentication - register
│   │   │   ├── Dashboard.tsx       # Main dashboard
│   │   │   ├── Farms.tsx           # Farm management
│   │   │   ├── Prediction.tsx      # ML yield prediction
│   │   │   ├── Disease.tsx         # Disease detection
│   │   │   ├── Sensors.tsx         # IoT sensor dashboard
│   │   │   ├── Analytics.tsx       # Charts & analytics
│   │   │   ├── Profile.tsx         # User profile editor
│   │   │   └── Settings.tsx        # App settings & language
│   │   ├── services/               # API client functions
│   │   ├── context/                # React context providers
│   │   ├── locales/                # Translation files (9 languages)
│   │   ├── types/                  # TypeScript interfaces
│   │   ├── i18n.ts                 # i18n configuration
│   │   ├── App.tsx                 # Router & providers
│   │   └── main.tsx                # Entry point
│   ├── package.json
│   └── vite.config.ts
│
└── README.md

📡 API Reference

Authentication

Method Endpoint Description
POST /api/v1/auth/register Register a new user
POST /api/v1/auth/login Login (returns JWT token)
GET /api/v1/auth/profile Get current user profile
PUT /api/v1/auth/profile Update user profile

Farms

Method Endpoint Description
GET /api/v1/farms/ List all user farms
POST /api/v1/farms/ Create a new farm
DELETE /api/v1/farms/{id} Delete a farm

Prediction

Method Endpoint Description
POST /api/v1/predict/yield Predict crop yield
GET /api/v1/predict/history/{farm_id} Get prediction history

Disease Detection

Method Endpoint Description
POST /api/v1/disease/predict Detect disease from image
GET /api/v1/disease/history/{farm_id} Get detection history

Sensors

Method Endpoint Description
GET /api/v1/sensors/latest/{farm_id} Latest sensor readings
GET /api/v1/sensors/history/{farm_id} Sensor data history

Analytics

Method Endpoint Description
GET /api/v1/analytics/summary/{farm_id} Farm analytics summary

Health

Method Endpoint Description
GET /health API health check

📖 Interactive API docs available at http://localhost:8000/docs (Swagger UI)

🗄️ Database Schema

erDiagram
    USERS {
        uuid id PK
        string full_name
        string email UK
        string phone
        string city
        int age
        float food_stock
        string role
        string hashed_password
        datetime created_at
    }
    FARMS {
        int id PK
        uuid user_id FK
        string farm_name
        string location
        float latitude
        float longitude
        float area
        string crop
    }
    SENSOR_DATA {
        int id PK
        int farm_id FK
        float temperature
        float humidity
        float soil_moisture
        float soil_ph
        float rainfall
        float light_intensity
        datetime timestamp
    }
    YIELD_PREDICTIONS {
        int id PK
        int farm_id FK
        string crop
        int year
        float rainfall
        float temperature
        float pesticides
        float predicted_yield
        datetime created_at
    }
    DISEASE_PREDICTIONS {
        int id PK
        int farm_id FK
        string image_url
        string disease
        float confidence
        string recommendation
        datetime created_at
    }

    USERS ||--o{ FARMS : owns
    FARMS ||--o{ SENSOR_DATA : has
    FARMS ||--o{ YIELD_PREDICTIONS : has
    FARMS ||--o{ DISEASE_PREDICTIONS : has
Loading

🌐 Supported Languages

Language Code Status
🇬🇧 English en ✅ Complete
🇮🇳 हिंदी (Hindi) hi ✅ Complete
🇮🇳 বাংলা (Bengali) bn ✅ Complete
🇮🇳 ଓଡ଼ିଆ (Odia) or ✅ Complete
🇵🇰 اردو (Urdu) ur ✅ Complete
🇫🇷 Français (French) fr ✅ Complete
🇪🇸 Español (Spanish) es ✅ Complete
🇮🇳 தமிழ் (Tamil) ta ✅ Complete
🇮🇳 తెలుగు (Telugu) te ✅ Complete

🤖 ML Model Details

Property Value
Algorithm Extra Trees Regressor
Training Data Global crop yield dataset (FAO)
Input Features Region, Crop, Year, Rainfall, Temperature, Pesticides
Output Predicted Yield (hg/ha)
Pipeline Label Encoding + Extra Trees (scikit-learn)
Serialization Joblib (.pkl)

🧑‍💻 Development

Running Tests

# Backend
cd backend
python -m pytest tests/

# Frontend
cd frontend
npm run lint
npm run build   # TypeScript type-check + production build

Database Migrations

cd backend

# Create a new migration after model changes
alembic revision --autogenerate -m "Description of change"

# Apply migrations
alembic upgrade head

# Rollback one step
alembic downgrade -1

🤝 Contributing

Contributions are welcome! Here's how:

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

📄 License

This project is licensed under the MIT License — see the LICENSE file for details.

👨‍💻 Author

Sheikh Wasimuddin

⭐ Star this repo if you find it useful!

Built with ❤️ for farmers, by engineers.

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