GPS Vehicle Tracking System with Web Dashboard

A real-time vehicle tracking system using Apache Spark Streaming, Kafka, and a web-based dashboard.

Features

• 🚗 Real-time GPS vehicle tracking
• 📍 Interactive map visualization using Leaflet
• ⚠️ Overspeed alerts (>80 km/h)
• 📊 Live statistics dashboard
• 🔄 WebSocket-based real-time updates

System Architecture

1. GPS Producer (gps_producer.py) - Simulates GPS data and sends to Kafka
2. Spark Stream Processor (vehicle_tracking_spark.py) - Processes GPS streams using Apache Spark
3. Web Dashboard (web_app.py) - Flask-based real-time web interface

Installation

1. Install Python dependencies:

pip install -r requirements.txt

2. Install and start Kafka:
   • Download Kafka from https://kafka.apache.org/downloads
   • Start Zookeeper: bin/zookeeper-server-start.sh config/zookeeper.properties
   • Start Kafka: bin/kafka-server-start.sh config/server.properties

Usage

Run the complete system:

1. Start GPS Producer (Terminal 1):

python gps_producer.py

2. Start Web Dashboard (Terminal 2):

python web_app.py

3. Open Dashboard in browser:

http://localhost:5000

4. (Optional) Run Spark Processing (Terminal 3):

python vehicle_tracking_spark.py

Dashboard Features

• Live Map: Shows real-time vehicle positions with color-coded markers

  • Green: Normal speed
  • Red: Overspeed alert

• Vehicle Status: Lists all active vehicles with current speed and location

• Statistics:

  • Total active vehicles
  • Number of overspeed alerts
  • Average fleet speed

• Alert History: Recent overspeed violations

Configuration

• Kafka Server: localhost:9092
• Kafka Topic: vehicle_gps
• Web Server: http://localhost:5000
• Overspeed Threshold: 80 km/h
• Base Location: Bangalore (12.9716°N, 77.5946°E)

Vehicle Data Format

{
  "vehicle_id": "CAR_001",
  "latitude": 12.9716,
  "longitude": 77.5946,
  "speed": 65.5,
  "event_time": "2025-12-11T12:00:00"
}