Open AccessIntelligent Analysis for Drowsiness Alert using Conventional Neural Networks
Author(s) -
D. Jeyabharathi,
K Jeevanantham,
M Kavinmukhil,
Quanith hasan J B Mohamed
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1916/1/012131
Subject(s) - duration (music) , alarm , computer science , scrolling , simulation , histogram , truck , real time computing , artificial intelligence , engineering , automotive engineering , art , literature , aerospace engineering , image (mathematics)
When a job is assigned to drivers who travel through the roads and highways riding a CAB or NATIONAL PERMIT TRUCKS face the risk of tiredness especially during night travels and early morning. This project is to develop a driver drowsiness detection system by using Deep learning. It is known that a driver is under drowsiness influences by looking at the eyes for a moment of duration. Based on the previous research, there is none added tome counter that may exclude driver drowsiness from other activities of eyelid movement. The result can be accurate because histogram analysis analyzed the whole image upto a certain duration giving alarm with battery connection to be disabled for mentioned span of time. Therefore, he can start the vehicle only when the driver completes his rest time.