dc.contributor.author |
Sayyid, Abrar |
|
dc.contributor.author |
Khan, Muhammad (14DET84) |
|
dc.contributor.author |
Khan, Asad (14DET80) |
|
dc.contributor.author |
Dakhani, Musaddique (14DET76) |
|
dc.date.accessioned |
2017-05-19T04:28:17Z |
|
dc.date.available |
2017-05-19T04:28:17Z |
|
dc.date.issued |
2017-05 |
|
dc.identifier.uri |
http://www.aiktcdspace.org:8080/jspui/handle/123456789/1954 |
|
dc.description.abstract |
Various investigations show that driver’s drowsiness is one of the main causes of road accidents. The current technology in digital computer system allows researchers around the world to study the fatigue behaviour. The purpose of this study is to detect the drowsiness in drivers to prevent the accidents and to improve the safety on the highways. Real time face detection is implemented to locate driver’s face region. In this project the eye blink of the driver is detected. If the drivers eyes remain closed for more than a certain period of time, the driver is said to be drowsy and an alarm is sounded. The programming is done in python language and Open CV using the Haarcascade library for the detection of facial features. In this project we aim to develop drowsiness system |
en_US |
dc.language.iso |
en_US |
en_US |
dc.publisher |
AIKTC |
en_US |
dc.relation.ispartofseries |
Accession # PE0174; |
|
dc.subject |
Project Report - EXTC |
en_US |
dc.title |
Drowsiness detection system |
en_US |
dc.type |
Project Report |
en_US |