Drowsiness Detection

Made using dlib, opencv, and python.

Table of Contents

• Introduction
• Features
• Requirements
• Installation
• Applications

Introduction

This Drowsiness Detection System is a Python-based project using dlib and OpenCV to detect drowsiness in real-time from a video stream or camera feed. It can be used in various scenarios, such as monitoring the alertness of drivers or individuals operating heavy machinery - such as automobiles. Various studies have suggested that around 20% of all road accidents are fatigue-related, up to 50% on certain roads. Our project aims to reduce the risk of such fatalities.

Features

• Real-time drowsiness detection.
• Alarm system to alert drivers.
• Face and eye tracking for accurate detection.
• Easy integration with existing systems.
• Can be implemented with an alarm system, in say, automobiles.
• prompts to run the model without any hassle

Requirements

• Python 3.11
• OpenCV
• dlib
• NumPy
• A compatible webcam or video feed source.
• mediaplayer source
• a mini computer for running the source code

Installation

1. Clone the repository:

   git clone https://github.com/CodeRreaper69/DROWSINESS_DETECTION_ALARM.git
   

2. Install the required dependencies:

   pip install -r requirements.txt 
   

3. Run the Drowsiness Detection System:

   python main_edit.py
   

Applications

• Driver Monitoring Systems (DMS): Implementing the drowsiness detection system in vehicles can help prevent accidents caused by driver fatigue. It can alert drivers when they are becoming drowsy or distracted, potentially saving lives on the road.

• The driver will walk up if the camers sense sleepiness or drowsiness through it's feed.

• it will wake up the driver by taking over the whole car music system and thereby turning on a high volume alarm or audio with a notification or message to their relatives or acquaintences, so that they can be alerted properly.

• Industrial Safety: In industrial settings where heavy machinery is operated, the system can be used to monitor the alertness of workers. It can trigger alarms or safety measures when a worker shows signs of drowsiness, reducing the risk of accidents.

• Personal well being: Students can use this system to make theem awake at night before the exams, so that if they get asleep, this sytem can wake them up, they just have to install this repo and then the libraries, and all the work will get done automatcially.

• Public Transportation: Drowsiness detection can be integrated into public transportation systems to ensure that bus and train drivers remain alert during their shifts, improving passenger safety.

• Aviation: Pilots and flight crew often have long and irregular working hours. This system can be employed to monitor their alertness during flights, enhancing aviation safety.

• Healthcare: In healthcare settings, especially in intensive care units (ICUs), nurses and medical professionals can benefit from drowsiness detection to ensure they stay alert during long shifts, improving patient care.

• Security and Surveillance: Drowsiness detection can be integrated into security and surveillance systems to ensure that security personnel and surveillance operators remain attentive while monitoring critical areas.

• For DLIB installation refer - DLIB_WHEELS_FOR_PYTHON