Driver Drowsiness Detection Using Python

Prof. Abhay Rewatkar; Ms. Priyanka Khapekar; Ms. Damini Rahangdale; Ms. Komal Nagpure; Ms. Simran Nitnaware

Driver Drowsiness Detection Using Python

May 2022

Vol-8, Issue-3

Paper ID: 16836

ISSN: 2395-4396

Downloads: 0

Abstract & Details

Research Area

Information Technology

Keywords

Fatigue detection drivers assistance system eye-state recognition head pose estimation

Abstract

Driver fatigue is one in every of the foremost necessary causes of accidents within the world. detection the state of the effort is one in every of the surest ways that during which of live driver fatigue. throughout this project we've an inclination to tend to aim to develop a model state detection system. this technique works by observance the eyes of the effort Associate in Nursing sounding associate alarm once he/she is drowsy. The system thus designed can be a non-intrusive quantity observance system. The priority is on up the protection of the effort whereas not being obtrusive. throughout this project the attention blink of the effort is detected. If the drivers eyes keep closed for quite specific amount of some time, the effort is imagined to be drowsy Associate in Nursing associate alarm is plumbed. The programming for this is {often this can be} this could be} often exhausted OpenCV exploitation the Haarcascade library for the detection of countenance.

License

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Author Information

#	Name	Institute / Affiliation
1	Prof. Abhay Rewatkar	Asst. Professor, Department of Information Technology, Tulsiramji Gaikwad-Patil College of Engineering and Technology, Nagpur, India
2	Ms. Priyanka Khapekar	Student Information Technology Department, Tulsiramji Gaikwad Patil College of Engineering and Technology, Nagpur, Maharashtra, India.
3	Ms. Damini Rahangdale	Student Information Technology Department, Tulsiramji Gaikwad Patil College of Engineering and Technology, Nagpur, Maharashtra, India.
4	Ms. Komal Nagpure	Student Information Technology Department, Tulsiramji Gaikwad Patil College of Engineering and Technology, Nagpur, Maharashtra, India.
5	Ms. Simran Nitnaware	Student Information Technology Department, Tulsiramji Gaikwad Patil College of Engineering and Technology, Nagpur, Maharashtra, India.

How to Cite

Use the following formats to cite this article in your research.

APA Style

Rewatkar, Prof. Abhay, Khapekar, Ms. Priyanka, Rahangdale, Ms. Damini, Nagpure, Ms. Komal, & Nitnaware, Ms. Simran (2022). Driver Drowsiness Detection Using Python. International Journal of Advance Research and Innovative Ideas In Education, 8(3), 1644-1648.

MLA Style

Rewatkar, Prof. Abhay, et al. "Driver Drowsiness Detection Using Python." International Journal of Advance Research and Innovative Ideas In Education, vol. 8, no. 3, 2022, pp. 1644-1648.

IEEE Style

Prof. Abhay Rewatkar, Ms. Priyanka Khapekar, Ms. Damini Rahangdale, Ms. Komal Nagpure, and Ms. Simran Nitnaware, "Driver Drowsiness Detection Using Python," International Journal of Advance Research and Innovative Ideas In Education, vol. 8, no. 3, pp. 1644-1648, 2022.

Vancouver Style

Rewatkar Prof. Abhay, Khapekar Ms. Priyanka, Rahangdale Ms. Damini, Nagpure Ms. Komal, Nitnaware Ms. Simran. Driver Drowsiness Detection Using Python. International Journal of Advance Research and Innovative Ideas In Education. 2022;8(3):1644-1648.

Harvard Style

Rewatkar, Prof. Abhay, Khapekar, Ms. Priyanka, Rahangdale, Ms. Damini, Nagpure, Ms. Komal, & Nitnaware, Ms. Simran (2022) 'Driver Drowsiness Detection Using Python', International Journal of Advance Research and Innovative Ideas In Education, 8(3), pp. 1644-1648.

Chicago Style

Rewatkar, Prof. Abhay, et al. "Driver Drowsiness Detection Using Python." International Journal of Advance Research and Innovative Ideas In Education 8, no. 3 (2022): 1644-1648.

Turabian Style

Rewatkar, Prof. Abhay, et al. "Driver Drowsiness Detection Using Python." International Journal of Advance Research and Innovative Ideas In Education 8, no. 3 (2022): 1644-1648.