AI-Powered COVID-19 Safety Monitoring System

An advanced computer vision application integrating deep learning models for real-time face mask detection and social distancing monitoring, wrapped in a responsive PyQt5 GUI.

System Overview

1. User Authentication

Secure login system with SQLite database integration.

2. Intuitive Dashboard

User-friendly interface for easy navigation between different monitoring features.

3. Face Mask Detection

Real-time face mask detection using deep learning models and OpenCV.

4. Social Distancing Monitoring

Advanced social distancing violation detection with YOLO object detection.

Key Features

• Real-time video processing with OpenCV
• Deep learning-based face mask detection using TensorFlow/Keras
• YOLO-based object detection for social distancing analysis
• Multi-threaded video capture and processing
• SQLite database integration for user management
• SMTP integration for automated alert systems
• Responsive GUI design with PyQt5

Core Technologies

• Python 3.x
• PyQt5
• OpenCV
• TensorFlow / Keras
• YOLO (You Only Look Once)
• SQLite
• CUDA (for GPU acceleration)

Libraries & Frameworks

• NumPy for numerical operations
• imutils for video stream handling
• SciPy for spatial distance calculations

Software Engineering Practices

• Multi-threading for performance optimization
• OOP principles in GUI and backend logic
• Event-driven programming with PyQt5
• Database design and management
• API integration (SMTP for email notifications)

Computer Vision & AI

• Real-time video stream processing
• Object detection and tracking
• Transfer learning (MobileNetV2 for mask detection)
• Custom model training and deployment

User Interface Design

• Responsive layout management
• Custom styling and theming
• Dynamic UI updates based on detection results

System Requirements

• Python 3.7+
• NVIDIA GPU with CUDA support (for optimal performance)
• Webcam or IP camera for video input