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Driver Drowsiness Detection and Alerting system using Deep Learning
Authors
Thejas A V,Dr.kusumadhara S,Dr. Bhagya H. K.,Dr. Savitha M
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Keywords
Index Terms - IoT,GPS,technology,ESP32,Spo2,BPM.
Abstract
One of the main difficulties standing up to this present reality is the ascent in street mishaps. Inappropriate and scatterbrained driving is the main source of street mishaps. This study's principal objective is to foster a non-meddlesome framework that can recognize human exhaustion and give an early admonition. Drivers who don't stop much of the time while driving significant distances are in danger of becoming tired, which they some of the time don't understand until it is past the point of no return. The driver's sluggishness or absence of focus is respected to be an essential consider such episodes. Driver lethargy checking exploration could help with the decrease of mishaps. As per master research, about a fourth of serious thruway mishaps can be credited to sluggish drivers who need to rest, and that implies that lethargic drivers cause more car crashes than drink-driving. The innovation will utilize a camera to follow and screen drivers' eyes, and by building a Milestones calculation, we will actually want to identify drowsiness side effects in drivers sufficiently early to keep away from mishaps. Thus, this examination will help with recognizing a driver's sluggishness ahead of time and giving admonition yield as cautions ,along this really genuine we have executed an IoT-empowered liquor recognition ,pulse (BPM) and Spo2 observing framework which closes down the vehicle's motor, sets off a caution during driver id sleepy and liquor consumed circumstances. This framework shares the live area utilizing GPS innovation . Anyhow in thinking of concept and academic studies implementing the system with available resources and building a POC with PC and ESP32 controller with addition sensor and actuators ,This combination of modules will identify tiredness or fatigue and can be used to automatically stop the vehicle .
IJCRT's Publication Details
Unique Identification Number - IJCRT2307777
Paper ID - 241827
Author type - Indian Author
Page Number(s) - g594-g604
Pubished in - Volume 11 | Issue 7 | July 2023
DOI (Digital Object Identifier) -
No Of Downloads - 91
Author Country - India, 570017, Mysore, Mysore, 570017, Science and Technology
Publisher Name - IJPUBLICATION | www.ijcrt.org | ISSN : 2320-2882
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Thejas A V,Dr.kusumadhara S,Dr. Bhagya H. K.,Dr. Savitha M, "Driver Drowsiness Detection and Alerting system using Deep Learning", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.11, Issue 7, pp.g594-g604, July 2023, Available at :http://www.ijcrt.org/papers/IJCRT2307777.pdf
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ISSN: 2320-2882 Impact Factor: 7.97 and ISSN APPROVED Journal Starting Year (ESTD) : 2013
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ISSN: 2320-2882 Impact Factor: 7.97 and ISSN APPROVED Journal Starting Year (ESTD) : 2013
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