Real Time Driver Drowsiness Detection

Drowsiness detection is a safety technology that can prevent accidents which are caused by drivers who fall asleep while driving. Driver inattention might be the result of a lack of alertness when driving due to driver drowsiness and distraction. Driver distraction occurs when an object or event dra

Project Title

Real Time Driver Drowsiness Detection

Project Area of Specialization

Artificial Intelligence

Project Summary

Drowsiness detection is a safety technology that can prevent accidents which are caused by drivers who fall asleep while driving. Driver inattention might be the result of a lack of alertness when driving due to driver drowsiness and distraction. Driver distraction occurs when an object or event draws a person’s attention away from the driving task unlike driver distraction; driver drowsiness involves no triggering event but, instead, is characterized by a progressive withdrawal of attention from the road and traffic demands. Both driver drowsiness and distraction, however, might have the same effects i.e., decreased driving performance, longer reaction time, and an increased risk of crash involvement. The purpose of this is to build a drowsiness detection system that will detect that if a person’s eyes are closed for a few seconds or a person driving the vehicle is distracted. This system will alert the driver when drowsiness is detected.

Project Objectives

The main aim of the project is to save lives and our objective is to create better environment. Our proposed system will detect drowsiness of drivers to prevent accidents and improve safety on the roads and highways. It will also help transportation companies to assure the safety of their passengers and goods.  

? Save lives.

? Prevent accidents.

? Safer environment.

Project Implementation Method

Our project phases are defined broadly in three phases: 
 
PHASE 1: Data Set Learning  The proposed system will be based on an already existing data set which is available on Kaggle. In this phase we will shortlist the best features relevant to the proposed system and study these features in detail.  
 
PHASE 2: Designing Base Structure After completing the first phase, different algorithms will be tested on the data set and the base structure will be designed accordingly. The real time detection will be implemented by: ? Training AI model to detect drowsiness ? Implementing drowsiness detection using OpenCV, dlib and Python ? Testing AI model accuracy  
 
PHASE 3: Final Deliverable The proposed system in its final phase will have a fully functional face and eye detection system and a working alarm system synchronized with the facial behavior. The system will work in such a way that it will derive input in real time from live stream and analyze the facial behavior to detect drowsiness of driver.  
 
Development Tool: ? OpenCV, Jupyter Notebook 
 
Programming Language: ? Python 
 

Benefits of the Project

? The proposed system will provide a safer environment and help save countless lives

? Will help in a secure delivery of goods transported by different companies

? Warns the driver of drowsiness and the risk of sleep ? Compliance with driver warnings helps to avoid crashes caused by fatigue

? This technology has not been introduced in Pakistan yet

Technical Details of Final Deliverable

The final deliverable of “Driver drowsiness detection” will be a real time computer vision based system along with documentation manual having all the technical details of system. It will be developed in Python language. The system will automatically detect the drowsiness and alert the driver immediately.

Final Deliverable of the Project

Hardware System

Core Industry

Transportation

Other Industries

Core Technology

Artificial Intelligence(AI)

Other Technologies

Sustainable Development Goals

Good Health and Well-Being for People

Required Resources

If you need this project, please contact me on contact@adikhanofficial.com