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  Published Paper Details:

  Paper Title

IMPLEMENTATION OF A ROAD SAFETY SYSTEM FOR DROWSY DRIVING USING DEEP LEARNING

  Authors

  Tanmay Pramanick,  Ganesh Nikumbh,  Giriraj Pachorkar,  Sagar Shinde

  Keywords

Driver Drowsiness Detection System, Eyes Detection, Face Detection, Fatigue Detection, Visual Behaviour, Road Safety System

  Abstract


Drowsiness is a huge reason for road accidents and Data Science is the best possible cure for it. This detection system is a road safety technology that can prevent accidents from happening that are caused by the drivers who fell asleep while driving. According to the survey, 21 percent of all fatal accidents are due to drowsy driving. 60 percent of drivers or about 167 million people in the world have driven a vehicle feeling drowsy or in a fatigue in the past years. This turns out to be a huge problem not only for the driver but also for the pedestrians and other drivers. This system is a safety system that alerts the driver whenever he feels drowsy. The eyes movement of the driver is monitored live and whenever the driver feels asleep or closes eye for more than 2 seconds, then it will detect and alert the driver using a buzzer, vibrator or a water sprinkler. Basically, our aim is to prevent accidents from happening using image processing and deep learning.

  IJCRT's Publication Details

  Unique Identification Number - IJCRT2112433

  Paper ID - 214151

  Page Number(s) - e185-e190

  Pubished in - Volume 9 | Issue 12 | December 2021

  DOI (Digital Object Identifier) -   

  Publisher Name - IJCRT | www.ijcrt.org | ISSN : 2320-2882

  E-ISSN Number - 2320-2882

  Cite this article

  Tanmay Pramanick,  Ganesh Nikumbh,  Giriraj Pachorkar,  Sagar Shinde,   "IMPLEMENTATION OF A ROAD SAFETY SYSTEM FOR DROWSY DRIVING USING DEEP LEARNING", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.9, Issue 12, pp.e185-e190, December 2021, Available at :http://www.ijcrt.org/papers/IJCRT2112433.pdf

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ISSN: 2320-2882
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ISSN and 7.97 Impact Factor Details


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ISSN: 2320-2882
Impact Factor: 7.97 and ISSN APPROVED
Journal Starting Year (ESTD) : 2013
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