🪖 HelmetEye — AI-Powered Traffic Surveillance System

🎓 Final Year Project (FYP) — Bachelor of Information Technology
University of Kotli, AJK (2021–2025)

An intelligent real-time traffic surveillance system that automatically detects helmet violations and vehicle number plates from live video feeds — built to automate traffic monitoring and support law enforcement agencies.

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🚨 Problem Statement

Manual traffic monitoring is:

• ❌ Slow, error-prone, and resource-heavy
• ❌ Unable to scale across multiple camera feeds
• ❌ Inconsistent in catching violations in real-time

HelmetEye solves this by using computer vision and deep learning to automatically detect violations, extract number plate data, and log everything to a database — with zero human intervention.

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✨ Key Features

• 🪖 Real-time helmet detection using YOLOv12
• 🔢 Automatic number plate recognition via OCR
• 📹 Live video feed processing frame by frame
• 🗄️ Violation logging with timestamp to database
• ⚡ FastAPI backend for fast, scalable API handling
• 💻 Next.js dashboard for live monitoring and violation history
• 📊 Docs folder with project documentation

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🛠️ Tech Stack

Layer	Technology
🧠 Detection Model	YOLOv12
🔤 OCR Engine	EasyOCR / Tesseract
⚙️ Backend	Python, FastAPI
🎨 Frontend	Next.js, TypeScript, Tailwind CSS
🗄️ Database	PostgreSQL / MySQL
👁️ Computer Vision	OpenCV
🚀 Hosting	Firebase App Hosting

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🏗️ Project Structure

HelmetEye/
│
├── backend/                  # Python FastAPI backend
│   ├── models/               # YOLOv12 model files
│   ├── routes/               # API endpoints
│   ├── ocr/                  # Number plate OCR logic
│   └── main.py               # FastAPI entry point
│
├── src/                      # Next.js frontend
│   └── app/
│       └── page.tsx          # Main dashboard page
│
├── docs/                     # Project documentation
├── next.config.ts            # Next.js configuration
├── tailwind.config.ts        # Tailwind CSS config
└── apphosting.yaml           # Firebase hosting config

🔄 How It Works

📹 Live Video Feed ↓ 🧠 YOLOv12 Detection (helmet + number plate) ↓ 🔤 OCR Engine (extracts plate text) ↓ ⚙️ FastAPI Backend (processes & validates) ↓ 🗄️ Database (logs violation + timestamp) ↓ 💻 Next.js Dashboard (displays live results)

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🚀 Getting Started

Prerequisites

• Python 3.9+
• Node.js 18+
• PostgreSQL

Backend Setup

# Clone the repo
git clone https://github.com/tashfeen786/HelmetEye.git
cd HelmetEye/backend

# Install Python dependencies
pip install -r requirements.txt

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

Frontend Setup

# Go to root directory
cd ..

# Install Node dependencies
npm install

# Start Next.js dev server
npm run dev

Environment Variables

Create a .env file in the backend folder:

DATABASE_URL=postgresql://user:password@localhost:5432/helmeteye
MODEL_PATH=./models/yolov12_helmet.pt

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📸 Screenshots

🔜 Coming soon — live demo screenshots

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📊 Model Performance

Metric	Value
Detection Model	YOLOv12
Task	Helmet + Number Plate Detection
Input	Live video / image frames
OCR	Real-time text extraction

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🎯 Use Cases

• 🏙️ Smart City Infrastructure — automated violation detection
• 🚔 Traffic Law Enforcement — instant number plate logging
• 📊 Road Safety Analytics — violation trend reporting
• 🏍️ Highway Monitoring — large-scale deployment ready

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👨‍💻 Author

Tashfeen Aziz — AI/ML Engineer & Python Developer

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📄 License

This project is licensed under the MIT License.

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