Go To Drowsy and Yawing Driver Alert System

Driver drowsiness is a major contributor to road accidents worldwide. Fatigue and lack of sleep are common issues among drivers, often resulting in decreased alertness and increased risk of collisions. One effective way to prevent such accidents is by detecting and alerting drivers about their drowsiness in advance. Various methods exist for identifying signs of drowsiness. In this study, we propose a deep learning-based solution for detecting driver fatigue. Our approach leverages transfer learning using MobileNet, a lightweight convolutional neural network architecture. We utilized a dataset focused on the eye region to accurately identify signs of drowsiness.

Authors

Publication Details

Journal
International Journal for Research in Applied Science and Engineering Technology
Published
2025-04-29
DOI
https://doi.org/10.22214/ijraset.2025.69574
Primary Topic
Sleep and Work-Related Fatigue
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Go To Drowsy and Yawing Driver Alert System

Mrs. V. Ratnasri
International Journal for Research in Applied Science and Engineering Technology
Sleep and Work-Related Fatigue
article

Go To Drowsy and Yawing Driver Alert System

Mrs. V. Ratnasri
article en

Abstract

Driver drowsiness is a major contributor to road accidents worldwide. Fatigue and lack of sleep are common issues among drivers, often resulting in decreased alertness and increased risk of collisions. One effective way to prevent such accidents is by detecting and alerting drivers about their drowsiness in advance. Various methods exist for identifying signs of drowsiness. In this study, we propose a deep learning-based solution for detecting driver fatigue. Our approach leverages transfer learning using MobileNet, a lightweight convolutional neural network architecture. We utilized a dataset focused on the eye region to accurately identify signs of drowsiness.

International Journal for Research in Applied Science and Engineering TechnologyVol. 13(4)
Openalex Percentile: Top 91%
Sleep and Work-Related Fatigue
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Go To Drowsy and Yawing Driver Alert System — Mrs. V. Ratnasri · International Journal for Research in Applied Science and Engineering Technology (2025) | TGRS Research Map | TGRS