WatchMan: AI-Powered Missing Person Detection System

Problem Statement

Traditional missing person searches are limited by manual processes, relying on static methods of identification and tracking. Law enforcement and search teams face significant challenges in:

• Efficiently tracking potential missing person sightings
• Processing large volumes of video surveillance data
• Quickly identifying and alerting relevant authorities
• Integrating advanced machine learning techniques in search efforts

WatchMan (Solution)

Watchman is a cutting-edge, AI-powered missing person detection system that revolutionizes the search and identification process. By leveraging state-of-the-art facial recognition, deep learning, and multi-camera monitoring, the system provides:

• Real-time missing person detection across multiple camera sources
• Advanced facial matching using deep learning techniques
• Automated alerting mechanisms for law enforcement
• Comprehensive logging and tracking of potential sightings

Key Features

• Multi-Technique Facial Recognition

  • Combines traditional face encoding with deep learning feature extraction
  • High-precision matching with configurable confidence thresholds
  • Supports multiple camera sources and video streams

• Advanced Machine Learning

  • Utilizes ResNet50 for deep feature extraction
  • Adaptive matching algorithms with confidence scoring
  • Continuous learning and improvement capabilities

• Comprehensive Alerting System

  • Background thread for processing detection alerts
  • Configurable notification channels
  • Logging of all detection events

• Flexible Configuration

  • JSON-based configuration management
  • Customizable tolerance and alert thresholds
  • Easy integration with external law enforcement APIs

System Requirements

• Python 3.7+
• MongoDB
• CUDA-compatible GPU (recommended for deep learning)

Installation

1. Clone the Repository

git clone https://github.com/SSARAWAGI05/Watchman.git
cd Watchman

2. Install Dependencies

pip install -r requirements.txt

3. Configure MongoDB

• Ensure MongoDB is installed and running
• Update MongoDB connection details in the script

4. Prepare Missing Persons Data

• Place missing persons images in the specified directory
• Ensure images are clear, front-facing photos

5. Run the System

python advanced_sentinel.py

Configuration

Customize the system through config.json:

{
    "face_recognition_tolerance": 0.4,
    "alert_thresholds": {
        "confidence": 0.7,
        "frequency": 3600
    },
    "external_api_endpoints": {
        "law_enforcement": "https://api.lawenforcement.gov/alert",
        "missing_persons_network": "https://api.missingpersons.org/report"
    }
}

Technology Stack

Computer Vision

• OpenCV
• face_recognition
• scipy

Machine Learning

• TensorFlow
• Keras
• ResNet50

Database

• MongoDB

Additional Technologies

• Threading
• Logging
• RESTful API Integration

Ethical Considerations

WatchMan is designed with strict privacy and ethical guidelines:

• All facial data is processed securely
• Personal information is handled with utmost confidentiality
• System complies with data protection regulations

Future Roadmap

• Enhanced deep learning models
• Real-time cloud synchronization
• Mobile application integration
• Advanced anomaly detection

Potential Applications

• Law Enforcement
• Search and Rescue Operations
• Airport and Border Security
• Missing Children Initiatives

Contributing

Contributions are welcome! Please read our contributing guidelines and code of conduct.

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

Contact

Shubam Sarawagi - [email protected]

Project Link: https://github.com/SSARAWAGI05/Watchman

Acknowledgements

• OpenCV Community
• TensorFlow Team
• Face Recognition Library Contributors
• MongoDB Developers

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Disclaimer: This system is intended for ethical use in missing person detection and search operations. Always respect privacy laws and individual rights.