Development of a Real Time Drowsy Driver Detection System

Precious O.C., Kinsley C.I., Chukwuemeka E.E. and Ebere U.c
Additional contact information
Precious O.C.: Enugu State University of Science and Technology, Nigeria
Kinsley C.I.: Enugu State University of Science and Technology, Nigeria
Chukwuemeka E.E.: Department of Computer Science, Ebonyi State University, Abakaliki, Nigeria
Ebere U.c: Destinet Smart Technologies, New layout, Enugu, Nigeria

International Journal of Research and Innovation in Applied Science, 2022, vol. 7, issue 1, 82-86

Abstract: This paper presents the development of real time drowsy driver detection system. The study reviewed literature and identified that drowsy has remained a major cause of most road accidents. To address this problem a real time drowsy driver was developed using convolutional neural network and implemented as an accident prevention and control system using Mathlab. The result when tested showed that the system was able to detect drowsiness in real time which is very good.

Date: 2022
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.rsisinternational.org/journals/ijrias/ ... -7-issue-1/82-86.pdf (application/pdf)
https://www.rsisinternational.org/virtual-library/ ... 051938702.1694191524 (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:bjf:journl:v:7:y:2022:i:1:p:82-86

Access Statistics for this article

International Journal of Research and Innovation in Applied Science is currently edited by Dr. Renu Malsaria

More articles in International Journal of Research and Innovation in Applied Science from International Journal of Research and Innovation in Applied Science (IJRIAS)
Bibliographic data for series maintained by Dr. Renu Malsaria ().