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🔥 Arduino Fire Sensor Network - FlamDirect

A real-time wildfire monitoring system using 4,096 virtual Arduino temperature sensors deployed across Eldorado National Forest.

🌟 Features

🔥 Fire Simulation Engine

  • 64x64 grid = 4,096 Arduino sensors covering 3.7 km²
  • Real-time fire physics with wind, slope, and fuel modeling
  • Temperature tracking from 20°C to 800°C+
  • Fire spread analysis with rate and direction calculation
  • 300 simulation steps for comprehensive fire progression

📡 Arduino Sensor Network

  • Virtual Arduino sensors with temperature, PM2.5, wind, and battery data
  • Fire state detection: Empty, Vegetation, Burning, Ash
  • Risk level assessment: LOW → MODERATE → HIGH → CRITICAL → EXTREME
  • Real-time data streaming via WebSocket

🗺️ Advanced Visualization

  • Temperature heatmaps showing fire intensity
  • Fire state visualization with color-coded sensors
  • Critical hotspot detection and alerting
  • Fire center tracking and spread vectors
  • Interactive tooltips with detailed sensor data

⚡ Real-time Controls

  • Play/Pause/Reset fire simulation
  • Speed control (0.5x to 5x playback)
  • Step-by-step progression
  • Jump to specific simulation steps

🚀 Quick Start

1. Install Dependencies

# Python dependencies
pip install websockets numpy asyncio

# Node.js dependencies (frontend)
cd frontend
npm install

2. Start the Arduino Fire Sensor Network

# Start the fire simulation server
python start-fire-server.py

# Or run directly
python fire-websocket-server.py

3. Start the Frontend

cd frontend
npm run dev

4. Open the Application

Visit http://localhost:3000 to see the Arduino Fire Sensor Network in action!

🔧 Technical Architecture

Backend Components

backend/firesimheadless.py

  • Fire simulation engine with cellular automata
  • Arduino sensor network generation (4,096 sensors)
  • Temperature calculation with heat diffusion
  • Fire spread metrics and hotspot detection

fire-websocket-server.py

  • WebSocket server for real-time data streaming
  • Simulation playback controls (play/pause/speed)
  • Client connection management
  • Data broadcasting to frontend

Frontend Components

app/(components)/FireLayers.tsx

  • Advanced deck.gl layers for fire visualization
  • Temperature heatmaps and scatter plots
  • Fire state coloring and risk level indicators
  • Interactive tooltips with sensor details

app/(components)/Sidebar.tsx

  • Fire simulation controls (play/pause/reset)
  • Real-time fire analytics (spread rate, affected area)
  • Critical fire zones with hotspot listing
  • Arduino sensor statistics

app/(lib)/store.ts

  • Fire simulation state management
  • WebSocket message handling
  • Real-time data processing
  • UI state synchronization

📊 Data Flow

Arduino Sensors (Virtual) → Fire Simulation Engine → WebSocket Server → Frontend
     ↓                           ↓                        ↓              ↓
Temperature Data         Fire Physics Model      Real-time Streaming   Visualization
Wind/Battery Info        Spread Calculation      Message Broadcasting  User Controls
Fire State Detection     Hotspot Analysis        Client Management     Analytics Display

🔥 Fire Simulation Details

Fire States

  • 🌿 VEGETATION (1): Normal forest vegetation
  • 🔥 BURNING (2): Active fire spreading
  • 🌫️ ASH (3): Burned out areas
  • ⬜ EMPTY (0): Non-flammable areas

Risk Levels

  • 🟢 LOW (20-30°C): Normal conditions
  • 🟡 MODERATE (30-60°C): Elevated temperature
  • 🟠 HIGH (60-100°C): Fire risk
  • 🔴 CRITICAL (100-300°C): Immediate danger
  • ⚫ EXTREME (300°C+): Active burning

Simulation Parameters

  • Grid Size: 64x64 cells (4,096 sensors)
  • Cell Size: 30x30 meters each
  • Total Area: 3.7 km² (Eldorado National Forest)
  • Simulation Steps: 300 (representing ~10 hours)
  • Update Frequency: 2-5 seconds per step

🌐 WebSocket API

Connection

ws://localhost:8765

Message Types

Simulation Initialization

{
  "type": "simulation_init",
  "data": {
    "total_steps": 300,
    "sensor_count": 4096,
    "grid_size": 64,
    "simulation_area_km2": 3.7,
    "base_coordinates": { "lat": 38.7891, "lon": -120.4234 }
  }
}

Sensor Data Batch

{
  "type": "sensor_batch",
  "step": 150,
  "sensors": [
    {
      "id": "ARDUINO_32_32",
      "lat": 38.7891,
      "lon": -120.4234,
      "temperature": 45.2,
      "pm25": 12.5,
      "state": 1,
      "risk_level": "MODERATE",
      "battery_level": 87
    }
  ],
  "spread_analysis": {
    "burning_cells": 25,
    "total_affected_area": 22500,
    "spread_rate": 1800,
    "max_temperature": 650.5
  }
}

Control Commands

{"type": "play"}
{"type": "pause"}
{"type": "reset"}
{"type": "set_step", "step": 150}
{"type": "set_speed", "speed": 2.0}

🎯 Use Cases

🚨 Emergency Response

  • Real-time fire detection from Arduino sensors
  • Hotspot identification for rapid response
  • Evacuation zone planning based on spread prediction
  • Resource allocation for firefighting efforts

📈 Research & Analysis

  • Fire behavior modeling with environmental factors
  • Spread pattern analysis for forest management
  • Sensor network optimization studies
  • Climate change impact assessment

🎓 Education & Training

  • Wildfire simulation for training programs
  • Arduino sensor network demonstrations
  • Real-time data visualization examples
  • Emergency response scenario planning

🔧 Configuration

Environment Variables

# Frontend
NEXT_PUBLIC_WS_URL=ws://localhost:8765

# Backend
FIRE_SIMULATION_STEPS=300
ARDUINO_SENSOR_COUNT=4096
UPDATE_INTERVAL_MS=2000

Simulation Parameters

# In backend/firesimheadless.py
size = 64              # Grid size (64x64 = 4,096 sensors)
steps = 300            # Simulation duration
CELL_SIZE_METERS = 30  # Each cell represents 30x30m
BASE_LAT = 38.7891     # Eldorado National Forest
BASE_LON = -120.4234

🚀 Deployment

Production Setup

  1. Server: Deploy WebSocket server on cloud instance
  2. Frontend: Build and deploy Next.js application
  3. Scaling: Use load balancer for multiple WebSocket connections
  4. Monitoring: Add logging and metrics collection

Docker Support (Future)

# Dockerfile for fire simulation server
FROM python:3.9-slim
COPY . /app
WORKDIR /app
RUN pip install -r requirements.txt
EXPOSE 8765
CMD ["python", "fire-websocket-server.py"]

📝 License

MIT License - Feel free to use this Arduino Fire Sensor Network for research, education, and emergency response applications.

🤝 Contributing

  1. Fork the repository
  2. Create feature branch (git checkout -b feature/arduino-enhancement)
  3. Commit changes (git commit -am 'Add new sensor feature')
  4. Push to branch (git push origin feature/arduino-enhancement)
  5. Create Pull Request

📞 Support

For questions about the Arduino Fire Sensor Network:

  • 🔥 Fire Simulation: Check backend/firesimheadless.py
  • 🌐 WebSocket Issues: Review fire-websocket-server.py
  • 🗺️ Visualization Problems: Examine app/(components)/FireLayers.tsx
  • 📱 Frontend Issues: Look at app/(lib)/store.ts

🔥 FlamDirect Arduino Fire Sensor Network - Protecting forests with real-time wildfire monitoring! 🌲