🌟 ARADHYA SONAR - AI Tracking & Reunion System 🌟

An Innovative Computer Vision & AI Platform for Tracking and Reuniting Missing Individuals

Overview • Key Features • Technology Stack • Architecture • Installation

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🚀 Overview

Welcome to the AI Tracking & Reunion System, crafted by Aradhya Sonar. This powerful platform acts as an intelligent safeguard, leveraging cutting-edge AI and advanced computer vision algorithms to significantly accelerate the process of locating missing persons and ensuring their safe return to their families.

By integrating real-time facial recognition, decentralized RTSP camera tracking, and a comprehensive centralized database, this system enhances modern security and law enforcement capabilities.

✨ Key Features

• 🧠 Advanced Facial Recognition: Employs deep-learning ArcFace models to achieve unparalleled accuracy in face matching, even under challenging lighting conditions or angles.
• 📍 Live RTSP Camera Tracking: Connects with global or local surveillance streams to autonomously analyze live video feeds.
• 🚨 Instant AI Alerts: Sends real-time notifications to administrators and law enforcement personnel upon detecting a positive match.
• 🛡️ Secure Command Center: A Django-powered centralized dashboard that enables law enforcement to manage cases, monitor sightings, and coordinate operations effectively.
• ⚡ Asynchronous Processing: Utilizes Celery and Redis to handle intensive image processing tasks in the background without losing frames.
• 🌍 Geospatial Mapping: Instantly calculates the nearest police stations upon a positive sighting to facilitate prompt assistance.

🛠 Technology Stack

This project integrates established frameworks with state-of-the-art machine learning tools.

Category	Technology
Backend Framework	Django 5.2, Python
Asynchronous Engine	Celery, Redis
Database	SQLite3 / Django ORM
AI & Computer Vision	OpenCV, InsightFace (RetinaFace & ArcFace)
Data Analytics	NumPy, Scikit-Learn
Frontend	HTML5, CSS3, JavaScript, Bootstrap

📂 Project Architecture

Reunite-AI-Tracking-System/
├── Reunite/                 # Core Django Configuration & Settings
│   ├── settings.py          # Environment, Security, and Application Configuration
│   ├── urls.py              # Root URL Routing
│   └── wsgi.py / asgi.py    # Server Gateway Interfaces
├── cases/                   # Missing Person AI Match Engine
│   ├── ai_processor.py      # Core InsightFace Model Logic
│   ├── models.py            # Case Data & Face Embeddings
│   ├── tasks.py             # Asynchronous Celery Processing
│   └── views.py             # Match Logic & Reporting
├── police/                  # Law Enforcement Dashboard
│   ├── models.py            # Officer Profiles
│   └── views.py             # Authentication & Case Handling
├── static/                  # Static Assets
│   ├── assets/              # Vendor Libraries (Bootstrap, AOS)
│   ├── img/                 # Application Imagery & Emblems
│   └── missing_persons/     # Pre-processed Headshots
├── templates/               # User Interface
│   ├── base.html            # Master Layout
│   └── index.html           # Command Center View
├── data/                    # Geospatial & Department Datasets
│   ├── locations.csv        
│   └── police_stations.csv  
├── docs/                    # Project Documentation & Diagrams
│   ├── images/              
│   ├── certificates/        # Achievements and Awards
│   └── Final_Year_Project_Report.pdf
├── scripts/                 # Standalone utilities
│   └── rtspCam.py           # 🎥 Live Surveillance Script
├── requirements.txt         # Dependencies
└── manage.py                # Django CLI

💻 Getting Started

1. Environment Setup

Clone the repository and establish your environment:

git clone https://github.com/sonararadhya/Reunite-AI-Tracking-System.git
cd Reunite-AI-Tracking-System
python -m venv venv

# Windows
venv\Scripts\activate
# Linux/Mac
source venv/bin/activate

2. Install Dependencies

pip install -r requirements.txt

(Ensure that you have the necessary system-level dependencies for OpenCV and Redis installed).

3. Initialize Services

Start Redis Server (Linux):

sudo service redis-server start

Run Database Migrations:

python manage.py migrate

4. Boot up the Ecosystem

You will need multiple terminal windows to run the complete setup:

Terminal 1 (Web Dashboard):

python manage.py runserver

Terminal 2 (AI Background Worker):

celery -A Reunite worker -l info -P solo

Terminal 3 (Live Surveillance):

python scripts/rtspCam.py

🏆 Certifications & Reports

• Final Year Project Report: Access the comprehensive project report
• Project Certificate: View Certificate

Project Competition Award:

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👤 Author & Creator

Developed and maintained by Aradhya Sonar.

🔗 GitHub: https://github.com/sonararadhya

"Empowering communities through artificial intelligence to reunite loved ones."

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📝 Last maintained: September 27, 2026 at 09:26 UTC