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DRIVER DROWSINESS MONITORING SYSTEM USING VISUAL BEHAVIOUR AND MACHINE LEARNING

Project Code CB1014
Application Type DESKTOP APP
Tech/Programming PYTHON

API:
NONE
Web Framework:
NOT APPLICABLE
IDE:
VS CODE
Database:
NOT REQUIRED
DFD Diagram:
Not Available
Videos:
Not Available
E-R Diagram:
Not Available
UML Diagrams:
Available
Final PPT:
Available
SRS:
Available

Description

Drowsy driving is one of the major causes of road accidents and death. Hence, detection of driver’s fatigue and its indication is an active research area. Most of the conventional methods are either vehicle based, or behavioural based or physiological based. Few methods are intrusive and distract the driver, some require expensive sensors and data handling. Therefore, in this study, a low cost, real time driver’s drowsiness detection system is developed with acceptable accuracy. In the developed system, a webcam records the video and driver’s face is detected in each frame employing image processing techniques. Facial landmarks on the detected face are pointed and subsequently the eye aspect ratio, mouth opening ratio and nose length ratio are computed and depending on their values, drowsiness is detected based on developed adaptive thresholding. Machine learning algorithms have been implemented as well in an offline manner. A sensitivity of 95.58% and specificity of 100% has been achieved in Support Vector Machine based classification.

Note

Project with Source Code, Documentation and PPT

1st Review PPT:
Available
2nd Review PPT:
Available
3rd Review PPT:
Available
Architecture Diagram:
Available

Literature Survey:
Available
Test Cases:
Not Available
Data Dictionary:
Available
Future Enhancement:
Available

SRS:
Available
All Modules:
Available
Documentation:
Available
Screen Shots:
Available

How to Install Softwares :Not Available
How to Execute Project :Not Available
Project Explanation Video :Not Available

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