ABSENS - AI-Based System for Efficiently Notifying and Searching

📑 Overview

ABSENS is a comprehensive platform developed to help locate and reunite missing individuals using advanced AI technology. The system leverages facial recognition, age progression technology, and a nationwide network of volunteers and law enforcement agencies to create a robust solution for finding missing persons.

By combining cutting-edge technology with a user-friendly interface, ABSENS aims to streamline the process of reporting, searching for, and identifying missing individuals across India.

✨ Key Features

• 🔍 AI-Powered Recognition: State-of-the-art facial recognition and age progression technology for accurate identification
• 🔔 Real-time Alerts: Instant notifications for potential matches and sightings across the country
• 💾 Centralized Database: Comprehensive repository of missing person reports with advanced search capabilities
• 👥 Volunteer Network: Nationwide network of verified volunteers and organizations working together
• 👮 Law Enforcement Integration: Secure connection with police and agencies across India
• 📱 Responsive Design: Fully responsive interface that works seamlessly on all devices
• 🌙 Dark Mode Support: Complete dark mode implementation for better accessibility and reduced eye strain
• 🔒 Secure Authentication: Robust user authentication and authorization system

🛠️ Tech Stack

Frontend

• Framework: Next.js 14 (React)
• Language: TypeScript
• Styling: Tailwind CSS with custom UI components
• State Management: Redux Toolkit
• Authentication: JWT with secure token refresh

Backend

• API Server: Node.js with Express
• Database: MongoDB
• Authentication: JWT, bcrypt for password hashing
• Validation: Joi/Zod

AI/ML Services

• Image Processing: FastAPI
• Facial Recognition: DeepFace
• Embedding Models: Google's Embedding Model
• Vector Database: For efficient similarity search

🚀 Getting Started

Prerequisites

Before you begin, ensure you have the following installed:

• Node.js (v18.0.0 or higher)
• npm (v9.0.0 or higher) or yarn (v1.22.0 or higher)
• MongoDB (v6.0 or higher)
• Python 3.9+ (for AI services)

Installation

1. Clone the repository

git clone https://github.com/your-organization/absens.git
cd absens

2. Set up the Frontend

# Navigate to the Frontend directory
cd Frontend

# Install dependencies
npm install
# or
yarn install

# Create a .env.local file with the following content
echo "NEXT_PUBLIC_BACKEND_URL=http://localhost:5000
NEXT_PUBLIC_IMAGE_RECOGNITION_URL=http://localhost:8000" > .env.local

3. Set up the Backend

# Navigate to the Backend directory
cd ../Backend

# Install dependencies
npm install
# or
yarn install

# Create a .env file with the following content
echo "PORT=5000
MONGODB_URI=mongodb://localhost:27017/absens
JWT_SECRET=your_jwt_secret_key
JWT_EXPIRES_IN=7d" > .env

4. Set up the AI Service (if applicable)

# Navigate to the AI-Service directory
cd ../AI-Service

# Create and activate a virtual environment
python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

# Install dependencies
pip install -r requirements.txt

Running the Application

1. Start the Frontend

cd Frontend
npm run dev
# or
yarn dev

2. Start the Backend

cd Backend
npm run dev
# or
yarn dev

3. Start the AI Service (if applicable)

cd AI-Service
python app.py

The application will be available at:

• Frontend: http://localhost:3000
• Backend API: http://localhost:5000
• AI Service: http://localhost:8000

📂 Project Structure

absens/
├── Frontend/               # Next.js frontend application
│   ├── app/                # Next.js app directory (pages and layouts)
│   ├── components/         # Reusable UI components
│   │   ├── ui/             # Base UI components
│   │   └── layout/         # Layout components
│   ├── lib/                # Utility functions and state management
│   │   ├── slices/         # Redux slices
│   │   └── store.ts        # Redux store configuration
│   └── public/             # Static assets
│
├── Backend/                # Node.js backend application
│   ├── controllers/        # Request handlers
│   ├── models/             # Database models
│   ├── routes/             # API routes
│   ├── middleware/         # Custom middleware
│   └── utils/              # Utility functions
│
└── AI-Service/             # Facial recognition service
    ├── models/             # ML models
    ├── api/                # FastAPI endpoints
    └── utils/              # Utility functions

🔐 Authentication Flow

ABSENS implements a secure authentication system using JWT (JSON Web Tokens):

1. User registers or logs in through the frontend
2. Backend validates credentials and issues a JWT and refresh token
3. Frontend stores the tokens securely
4. JWT is included in the Authorization header for protected API requests
5. When the JWT expires, the refresh token is used to obtain a new JWT
6. Backend middleware validates the JWT for protected routes

🌐 API Endpoints

Authentication

• POST /api/auth/register - Register a new user
• POST /api/auth/login - Login and receive JWT
• POST /api/auth/refresh - Refresh JWT token
• POST /api/auth/logout - Invalidate tokens

Missing Persons

• POST /api/missing-persons - Report a missing person
• GET /api/missing-persons - Get all missing persons
• GET /api/missing-persons/:id - Get a specific missing person
• PUT /api/missing-persons/:id - Update a missing person report
• DELETE /api/missing-persons/:id - Delete a missing person report

Search

• POST /api/search - Search for missing persons with optional image upload
• GET /api/search/results/:id - Get search results

🧪 Testing

# Run frontend tests
cd Frontend
npm test
# or
yarn test

# Run backend tests
cd ../Backend
npm test
# or
yarn test

🚢 Deployment

Docker Deployment

A docker-compose.yml file is provided for easy deployment:

# Build and run with Docker Compose
docker-compose up -d

Manual Deployment

Frontend

cd Frontend
npm run build
npm start

Backend

cd Backend
npm run build
npm start

🤝 Contributing

We welcome contributions to ABSENS! Please follow these steps:

1. Fork the repository
2. Create a feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add some amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

Please ensure your code follows our coding standards and includes appropriate tests.

� System Workflow Diagrams

Overall System Architecture

graph TD
    A[User] -->|Reports/Searches| B[Frontend]
    B -->|API Requests| C[Backend]
    C -->|Stores Data| D[(Database)]
    C -->|Image Processing| E[AI Service]
    E -->|Face Recognition| F[ML Models]
    E -->|Similarity Search| G[(Vector DB)]
    C -->|Notifications| H[Alert System]
    H -->|Sends Alerts| I[Users/Agencies]

Loading

Missing Person Report Flow

sequenceDiagram
    participant User
    participant Frontend
    participant Backend
    participant Database
    participant AIService

    User->>Frontend: Submit missing person report with photos
    Frontend->>Backend: POST /api/missing-persons
    Backend->>Database: Store report details
    Backend->>AIService: Process uploaded images
    AIService->>AIService: Extract facial features
    AIService->>Database: Store feature vectors
    AIService->>Backend: Return processing results
    Backend->>Frontend: Confirm report submission
    Frontend->>User: Display confirmation

Loading

Search Process Flow

sequenceDiagram
    participant User
    participant Frontend
    participant Backend
    participant Database
    participant AIService

    User->>Frontend: Upload photo for search
    Frontend->>Backend: POST /api/search
    Backend->>AIService: Process search image
    AIService->>AIService: Extract facial features
    AIService->>Database: Search for similar faces
    Database->>AIService: Return potential matches
    AIService->>Backend: Return search results
    Backend->>Frontend: Display potential matches
    Frontend->>User: Show search results

Loading

Alert Notification Flow

graph TD
    A[Potential Match Found] -->|Triggers| B[Alert System]
    B -->|Notifies| C[Law Enforcement]
    B -->|Notifies| D[Reporting User]
    B -->|Notifies| E[Nearby Volunteers]
    C -->|Takes Action| F[Investigation]
    D -->|Provides| G[Additional Information]
    E -->|Assists with| H[Local Search]
    F -->|Updates| I[Case Status]
    I -->|Notifies| J[All Stakeholders]

Loading