EventsHolography Meets Advanced Manufacturing
Published
This submission belongs to the session IA. Industry Applications of the event Holography Meets Advanced Manufacturing
Published date
13 Mar, 2023
Academic Editor
author-avatarVIJAYAKUMAR ANAND
Citation
MUZAMMIL PARVEZ M, Srinivas Allanki, Mohammed Ali Baig, G. Sudhagar, Mohammed Abdul Muqeet, Chella Santosh, Penky Satyanaraana, Advanced driver fatigue detection by integration of OpenCV, DNN module and deep learning, in Proceedings of Holography Meets Advanced Manufacturing, 20 February–22 February 2023, MDPI: Basel, Switzerland, doi: 10.3390/HMAM2-14158
Share
Email
Facebook
Twitter
LinkedIn

Advanced driver fatigue detection by integration of OpenCV, DNN module and deep learning

Mohammed Ali Baig 2
Chella Santosh 5
Penky Satyanaraana 5
1. KL UNIVERSITY
2. School of Electronics and Communication Engineering, Reva University, Bangaluru, Karnataka, India
3. Department of ECE, Bharath Institute of Higher Education and Research, Chennai, India.
4. Deaprtment of Electrical Engineering Department, Muffakham jah college of Engineering and Technology Hyderabad, India
5. Department of ECE, koneru Lakshmaiah Education Foundation, Vaddeswaram, India-522502.
Abstract

Road safety is significantly impacted by drowsiness or weariness, which is a primary contributor to auto accidents. If drowsy drivers are informed in advance, many fatal incidents can be avoided. Over the past 20 to 30 years, the number of road accidents and injuries in India has been rising alarmingly. According to the experts, the main cause of this issue is that drivers who do not take frequent rests when travelling long distances run a great danger of becoming drowsy, which they frequently fail to identify early enough. There are several drowsiness detection techniques that track a driver's level of tiredness while they are operating a vehicle and alert them if they are not paying attention to the road. This study describes a noncontact way for determining a driver's tiredness utilising detecting techniques

Keywords
OpenCV
DNN
Deep learning
Drowsy driver fatigue
Manuscript
Oral Presentation
Poster
sciforum-070216_PDF.pdf
DESIGN OF LOW POWER PHASE LOCKED LOOP
Design and simulation of a low power and high speed Fast Fourier Transform for medical image compression