Automatic Driver Drowsiness Detection Based on Visual Information and Artificial Intelligence

Authors(1) :-Yeshwanth Rao Bhandayker

Drowsiness as well as Tiredness of motorists is amongst the considerable root causes of road crashes. Yearly, they raise the quantities of deaths as well as fatalities injuries globally. In this paper, a module for Advanced Motorist Aid System (ADAS) is presented to lower the number of crashes as a result of chauffeurs tiredness as well as therefore in-crease the transport safety; this system manages automatic chauffeur drowsiness detection based on aesthetic info and also Artificial Intelligence. We suggest a formula to find, track, and evaluate both the vehicle driver’s deal with and also eyes to determine PERCLOS, a scientifically supported measure of sleepiness related to slow-moving eye closure.

Authors and Affiliations

Yeshwanth Rao Bhandayker
System Programmer Analyst, FINANCE: Trading Application Vanguard, Malvern, PA - 19355

Face Detection and Tracking, Drowsiness detection, Eyes Detection and Tracking

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Publication Details

Published in : Volume 5 | Issue 3 | May-June 2019
Date of Publication : 2019-06-30
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 294-301
Manuscript Number : CSEIT195369
Publisher : Technoscience Academy

ISSN : 2456-3307

Cite This Article :

Yeshwanth Rao Bhandayker, "Automatic Driver Drowsiness Detection Based on Visual Information and Artificial Intelligence", International Journal of Scientific Research in Computer Science, Engineering and Information Technology (IJSRCSEIT), ISSN : 2456-3307, Volume 5, Issue 3, pp.294-301, May-June-2019. Available at doi : https://doi.org/10.32628/CSEIT195369
Journal URL : https://res.ijsrcseit.com/CSEIT195369 Citation Detection and Elimination     |      |          | BibTeX | RIS | CSV

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