HIDS - Home Intrusion Detection System

Overview:

HIDS is a locally deployed Home Intrusion Detection System designed to enhance home security through real-time monitoring and alerting. Leveraging cutting-edge technologies like YOLO (You Only Look Once) object detection and Flask web framework, this system detects intruders and provides immediate notifications to homeowners via email.

Key Features:

• Real-time Object Detection:

  • Utilizes YOLO object detection model to identify intruders in real-time from webcam footage.
  • Utilizes YOLO (You Only Look Once) object detection model, a state-of-the-art deep learning framework.
    • YOLO employs a single neural network to simultaneously predict bounding boxes and class probabilities.
    • It divides the image into a grid and predicts bounding boxes and probabilities for each grid cell, enabling efficient detection.
    • YOLOv3, the version implemented in HIDS, enhances accuracy and speed by integrating multiple detection scales and advanced feature extraction techniques.

• Email Alerting:

  • Sends instant email notifications to homeowners upon detecting suspicious activity, enabling rapid response.
    • Utilizes Simple Mail Transfer Protocol (SMTP) for sending emails securely over the internet.
    • Implements two-factor authentication (2FA) architecture of Google Workspace for enhanced email security.
      • Google Workspace 2FA adds an extra layer of protection by requiring users to verify their identity through a secondary method, such as a mobile device or authenticator app.
      • This ensures that only authorized users can access the email alerting system, preventing unauthorized access and enhancing overall system security.

• Flask Web Interface:

  • Offers a user-friendly web interface powered by Flask for easy monitoring of detected intrusions and system status.
    • Utilizes the lightweight and flexible architecture of Flask, a micro web framework for Python, to create dynamic web applications.
    • Flask follows a modular design, allowing developers to build scalable and maintainable web interfaces by organizing code into smaller, reusable components.
      • This modular approach enhances performance by reducing overhead and improving code maintainability, resulting in faster response times and better overall user experience.

Installation:

1. Clone the HIDS repository to your local machine:

   git clone <repository-url>

2. Install required dependencies:

   pip install -r requirements.txt

3. Configure email settings in config.py to enable email alerting.

4. Run the application:

   python app.py

5. Access the web interface at http://localhost:5000 to monitor intrusions and system status.

Usage:

• Launch the HIDS system by running app.py.
• Navigate to the web interface to view live camera feed and intrusion alerts.
• Receive email notifications upon detecting intruders for immediate action.

Contributing:

Contributors to HIDS are valued and appreciated! Special thanks to all those who have contributed to this project:

1. David Grace - Tech Lead & Project Manager
2. Adersh S Thomas - Developer (Python)
3. Akshay S P - Developer (UI/UX)
4. Jayasurya - Intern

Version History:

v1.0 (Genesis - YOLO Person Detection):

• Initial release featuring basic YOLO person-class detection with Alarm Trigger functionality.
• Capable of distinguishing humans from other animate and inanimate objects.
• Implemented real-time detection and alerting system.

v2.0 (Enhanced Control Interface - Flask Dashboard):

• Introduced Flask Dashboard Interface.
• Provided clients with initial intruder detection alerts and administrative control.
• Enhanced user experience with interactive controls and customizable settings.

v3.0 (Advanced Alerting and Classification - SMTP Email Integration):

• Integrated SMTP email alerting system.
• Delivered notifications to client email addresses with precise timestamps.
• Implemented classification of humanoids as daytime humanoids or intruders based on predefined curfew times.
• Enhanced alerting system with customizable email templates and recipient lists.

v3.5 (Performance Optimization and UI Refinement - Cyberpunk Theme):

• Enhanced overall system performance and responsiveness.
• Revamped user interface with a cyberpunk-themed design.
• Provided a visually appealing and immersive environment for monitoring and control.
• Improved system stability and reliability through optimized code architecture.
• Streamlined user workflows with intuitive navigation and enhanced usability features.

BleedingEdge Development Model:

• The term "BleedingEdge" denotes the primary development branch.
• It houses the latest updates and experimental features.
• New updates and features are developed as deviations from the BleedingEdge branch, ensuring a continuous cycle of innovation and improvement.

Disclaimer:

This software is provided as-is and without warranty. Use at your own risk.

Contact:

For any inquiries or support, please contact maintainer-email.

License:

This project is licensed under the MIT License - see the LICENSE file for details.