🚗 Detection of Driving Pattern & Real-Time Vehicle Tracking System

A backend-centric vehicle telematics platform that ingests live GPS telemetry, persists trip data, exposes RESTful APIs, visualizes vehicle locations, and performs offline driving-behavior analysis using C++.

Designed to simulate real-world IoT → backend → analytics pipelines with emphasis on API design, data persistence, and system integration.

📌 Overview

End-to-end vehicle tracking and driving analytics workflow: GPS Simulator / Client → Laravel REST API → MySQL → Web Dashboard ↓ C++ Analytics The system continuously receives vehicle telemetry (latitude, longitude, speed), stores trip data in a relational database, exposes APIs for live tracking and historical playback, and performs offline analysis to classify driving behavior.

Driving analytics detects harsh acceleration, sudden braking, and aggressive vs normal driving patterns.

Primary focus areas: backend system design, data ingestion pipelines, database modeling, and cross-language integration (PHP + C++).

🛠 Tech Stack

Backend: Laravel (PHP) – REST APIs, MVC architecture Database: MySQL – GPS telemetry & trip metrics Frontend: HTML / CSS / JavaScript, Google Maps API Analytics: C++ – STL-based driving-pattern classification Realtime (Prototype): Firebase – evaluated for streaming updates

✨ Core Features Backend (Laravel + MySQL)

REST APIs for GPS telemetry ingestion (Vehicle ID, Latitude/Longitude, Speed, Timestamp)

APIs for latest vehicle position, trip history, and speed samples

Normalized relational schema for vehicles, trips, and driving metrics

Frontend

Live vehicle visualization on map

Periodic polling for location updates

Basic trip playback

C++ Driving Analytics

Processes stored speed samples

Detects sudden acceleration and hard braking

Classifies driving behavior as aggressive or normal using numeric thresholds

📂 Project Structure vehicle-tracking-system/ ├── backend/ # Laravel REST APIs ├── frontend/ # Map visualization ├── database/ # MySQL schema ├── analytics/ # C++ driving-pattern module ├── simulator/ # GPS data generator (optional) ├── screenshots/ └── README.md ▶ How to Run Backend cd backend composer install php artisan migrate php artisan serve Frontend

Open frontend/index.html in browser.

C++ Analytics g++ driving_analysis.cpp -o analysis ./analysis 📊 API Endpoints

POST /api/location — ingest GPS telemetry

GET /api/location/{vehicle_id} — fetch latest location

GET /api/history/{vehicle_id} — retrieve trip history

💡 Engineering Learnings

Designed RESTful APIs for telemetry ingestion

Implemented backend persistence using MySQL

Built near–real-time data flow via polling

Applied C++ STL for analytical processing

Debugged end-to-end pipelines across frontend, backend, and analytics layers

Integrated heterogeneous components into a cohesive system

🎯 Why This Project Matters

This project emphasizes software engineering fundamentals over UI:

Backend architecture & API design

Data ingestion pipelines

Relational database modeling

C++ analytical processing

Debugging distributed system components

It reflects practical experience building production-style backend systems with analytics integration. Project uploaded and documented.