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🌟 ARADHYA SONAR - AI Tracking & Reunion System 🌟

A State-of-the-Art Computer Vision & AI Platform for Tracking and Reconnecting Missing Individuals

Author Python Django OpenCV

OverviewKey FeaturesTech StackArchitectureInstallation


🚀 Overview

Welcome to the AI Tracking & Reunion System by Aradhya Sonar. This powerful platform acts as an intelligent shield, leveraging cutting-edge AI and advanced computer vision algorithms to drastically accelerate the process of locating missing persons and returning them safely to their families.

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

✨ Key Features

  • 🧠 Advanced Facial Recognition: Employs deep-learning ArcFace models to match faces with unparalleled accuracy, even in low-light or angled scenarios.
  • 📍 Live RTSP Camera Tracking: Connects to global or local surveillance streams to analyze live feeds autonomously.
  • 🚨 Instant AI Alerts: Triggers real-time notifications to administrators and officers upon detecting a positive match.
  • 🛡️ Secure Command Center: A Django-powered centralized dashboard for law enforcement to manage cases, view sightings, and coordinate operations.
  • ⚡ Asynchronous Processing: Utilizes Celery and Redis to handle intensive image processing operations natively in the background without dropping frames.
  • 🌍 Geospatial Mapping: Calculates nearby police stations instantly upon a positive sighting to dispatch aid seamlessly.

🛠 Technology Stack

The project fuses battle-tested frameworks with next-generation 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, JS, Bootstrap

📂 Project Architecture

Reunite-AI-Tracking-System/
├── Reunite/                 # Core Django Configuration & Settings
│   ├── settings.py          # Environment, Security, and App 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 prepare 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 you have 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 full suite:

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

Project Competition Award: Project Competition Award


👤 Author & Creator

Built and maintained by Aradhya Sonar.

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

"Empowering communities with artificial intelligence to bring loved ones home."


No unauthorized usage allowed.

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An AI-powered command center and real-time facial recognition tracker built to accelerate missing person rescue operations for law enforcement.

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