Arif Faysal

ESP32·Sep 20, 2024

ESP32 Vehicle Tracker - Real-Time Fleet Management

A comprehensive IoT solution for vehicle tracking and fleet management using ESP32, MicroPython, and FastAPI with real-time monitoring capabilities.

Live Demo View Source

MicroPythonFastAPIIoTWebSocketReal-TimeFleet ManagementEmbedded Systems

🚗 Project Overview

ESP32 Vehicle Tracker is a comprehensive IoT solution designed for real-time vehicle monitoring and fleet management. Built with modern web technologies and embedded systems, it provides seamless tracking, collision detection, and remote control capabilities through a cloud-based dashboard.

🎯 Problem Statement

Traditional vehicle tracking systems are expensive, proprietary, and lack real-time capabilities. Small fleet operators need an affordable, scalable solution that provides:

Real-time location tracking
Instant collision detection and alerts
Remote vehicle control capabilities
Comprehensive fleet analytics
Easy deployment and maintenance

🚀 Solution Architecture

Hardware Layer (ESP32 + Sensors)

ESP32 DevKit: Main microcontroller with WiFi capability
GPS Module: NEO-6M for precise location tracking
Accelerometer/Gyroscope: MPU6050 for collision detection
GSM Module: SIM800L for backup communication
Power Management: Optimized battery usage with deep sleep

Firmware (MicroPython)

Lightweight Implementation: Efficient code optimized for ESP32 constraints
Sensor Integration: Real-time data collection from multiple sensors
Communication Protocol: HTTP/WebSocket for cloud connectivity
Error Handling: Robust error recovery and reconnection logic

Backend (FastAPI + Python)

REST API: Comprehensive endpoints for device management
WebSocket Server: Real-time bidirectional communication
Database: PostgreSQL for reliable data persistence
Authentication: JWT-based security with role-based access

Frontend (Web Dashboard)

Real-Time Map: Interactive vehicle tracking with live updates
Alert System: Instant notifications for critical events
Analytics Dashboard: Comprehensive fleet performance metrics
Mobile Responsive: Works seamlessly on all devices

🔧 Key Features

1. Real-Time Vehicle Tracking

Live GPS Monitoring: Sub-second location updates
Route Visualization: Historical and real-time route tracking
Geofencing: Custom boundary alerts and notifications
Speed Monitoring: Real-time speed tracking with violation alerts

2. Advanced Collision Detection

Multi-Sensor Fusion: Combines accelerometer and gyroscope data
Machine Learning: AI-powered collision pattern recognition
Instant Alerts: Immediate notifications via WebSocket and Telegram
False Positive Reduction: Smart filtering to minimize false alarms

3. Remote Vehicle Control

Engine Lock/Unlock: Remote engine immobilization capability
Emergency Stop: Instant vehicle shutdown in critical situations
Light Control: Remote headlight and indicator management
Horn Activation: Anti-theft alarm system integration

4. Cloud Integration & Analytics

Real-Time Dashboard: Live fleet monitoring and management
Historical Data: Comprehensive trip logs and analytics
Performance Metrics: Fuel efficiency and driver behavior analysis
Report Generation: Automated daily, weekly, and monthly reports

📊 Technical Implementation

ESP32 Firmware Architecture

# Main application loop
async def main_loop():
    while True:
        # Collect sensor data
        location = get_gps_data()
        motion = get_accelerometer_data()
        
        # Process collision detection
        if detect_collision(motion):
            send_collision_alert(location)
        
        # Send telemetry
        await send_data_to_cloud({
            'location': location,
            'timestamp': time.time(),
            'vehicle_id': DEVICE_ID
        })
        
        await asyncio.sleep(1)

FastAPI Backend Structure

# WebSocket endpoint for real-time communication
@app.websocket("/ws/{vehicle_id}")
async def websocket_endpoint(websocket: WebSocket, vehicle_id: str):
    await manager.connect(websocket, vehicle_id)
    try:
        while True:
            data = await websocket.receive_json()
            await process_vehicle_data(vehicle_id, data)
            await manager.broadcast_to_dashboard(vehicle_id, data)
    except WebSocketDisconnect:
        manager.disconnect(websocket, vehicle_id)

Real-Time Data Flow

graph LR
    A[ESP32 Device] --> B[WiFi/GSM]
    B --> C[FastAPI Backend]
    C --> D[PostgreSQL]
    C --> E[WebSocket]
    E --> F[Dashboard]
    C --> G[Telegram Bot]
    G --> H[Mobile Alerts]