Sleep Detection System

Project Overview

The Sleep Detection System is a Python-based computer vision project that detects whether a person is feeling sleepy by analyzing eye movement using a webcam. If the system detects that the eyes remain closed for a certain period, it triggers an alarm sound to alert the user.

This project is useful for driver drowsiness detection, study monitoring, and fatigue detection systems.

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Technologies Used

• Python
• OpenCV
• Pygame
• Haar Cascade Classifier
• Computer Vision

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Features

• Real-time face detection
• Real-time eye detection
• Detects if eyes remain closed for a long duration
• Plays an alarm sound when sleep is detected
• Works using a webcam

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📂 Project Structure

sleep_detector
│
├── SleepDetection.py
├── buzz.mp3
└── README.md

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Installation

1. Clone the repository

git clone https://github.com/komalkhatod1105/Sleep_Detector.git

2. Install required libraries

pip install opencv-python
pip install pygame

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How to Run

Run the Python file:

python SleepDetection.py

Press ESC to exit the program.

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How It Works

1. The webcam captures video frames.
2. OpenCV detects the face and eyes using Haar Cascade classifiers.
3. If eyes remain closed for a specific duration, the system assumes the user is sleepy.
4. The program plays an alarm sound to alert the user.

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Applications

• Driver drowsiness detection
• Student focus monitoring
• Safety systems in vehicles
• Workplace fatigue monitoring

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Future Improvements

• Use Deep Learning models for higher accuracy
• Add GUI using Tkinter
• Implement Eye Aspect Ratio (EAR) algorithm
• Send mobile notifications

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Author

Komal Khatod