Paper Title

DriveGuard: Driver-Drowsiness Detection using Kotlin, Convolution Neural Networks

Article Identifiers

Registration ID: IJNRD_200233

Published ID: IJNRD2306495

DOI: Click Here to Get

Authors

Jyoti , Krishan Gopal , Harsh Vardhan SIngh , Pawan Sethi

Keywords

Drowsiness, Drowsiness Dataset, GPS, CNN, Deep Learning

Abstract

India has reported a massive number of over 151,000 fatalities in 2019, with youth being involved in almost 70 percent of the road accidents. This research paper is based on the study of “DriveGuard” . The main objective of this paper is to create a drowsiness detection application, automatic for handling the drowsy driver detection problem. It is recommended for travelers who avoid regular breaks in between their travel and hence might suffer from drowsiness. DriveGuard assistance can make the driver aware of his/her state and avoid carelessness in long extended drives. The paper focuses on the signs of drowsiness while driving that can be observed and hence how Kotlin based DriveGuard can be used to detect and prevent road accidents. Physical signs such as the inability to keep eyes wide open, frequent yawning, extending the head forward, can indicate driver fatigue and serve as early warning signs for potential accidents. By detecting these signs, measures can be taken to prevent accidents, saving lives and reducing the number of fatalities on the road.

How To Cite (APA)

Jyoti, Krishan Gopal, Harsh Vardhan SIngh, & Pawan Sethi (June-2023). DriveGuard: Driver-Drowsiness Detection using Kotlin, Convolution Neural Networks. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 8(6), e788-e794. https://ijnrd.org/papers/IJNRD2306495.pdf

Issue

Volume 8 Issue 6, June-2023

Pages : e788-e794

Other Publication Details

Paper Reg. ID: IJNRD_200233

Published Paper Id: IJNRD2306495

Downloads: 000121980

Research Area: Computer Science & Technology 

Country: Janakpuri,Delhi, Delhi, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2306495.pdf

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2306495

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