Fatigue Driving Detection Based on Convolutional Neural Network Model Connected to New Energy Vehicles

Fatigue driving detection based on Convolutional Neural Network (CNN) is a method that utilizes deep learning technology to monitor and identify whether a driver is in a fatigued state in real-time. This method analyzes the driver's facial features, eye status, and other information, combining multiple algorithms and techniques to achieve accurate detection and early warning of fatigue driving. This paper takes the application comparison of Yolov8 model as an example to conduct research on the idea of integrating fatigue detection systems with the Internet of Vehicles. During driving, if fatigue driving occurs, the system will make a judgment. Then, the autonomous driving system will take over the driving of the car and remind the driver to enter a rest area or stop to rest.

Authors

Publication Details

Journal
Theory and Practice of Science and Technology
Published
2025-01-01
DOI
https://doi.org/10.47297/taposatwsp2633-456927.20250602
Primary Topic
Advanced Sensor and Control Systems
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Fatigue Driving Detection Based on Convolutional Neural Network Model Connected to New Energy Vehicles

Xiang Li
Theory and Practice of Science and Technology
Advanced Sensor and Control Systems
article

Fatigue Driving Detection Based on Convolutional Neural Network Model Connected to New Energy Vehicles

Xiang Li
article en

Abstract

Fatigue driving detection based on Convolutional Neural Network (CNN) is a method that utilizes deep learning technology to monitor and identify whether a driver is in a fatigued state in real-time. This method analyzes the driver's facial features, eye status, and other information, combining multiple algorithms and techniques to achieve accurate detection and early warning of fatigue driving. This paper takes the application comparison of Yolov8 model as an example to conduct research on the idea of integrating fatigue detection systems with the Internet of Vehicles. During driving, if fatigue driving occurs, the system will make a judgment. Then, the autonomous driving system will take over the driving of the car and remind the driver to enter a rest area or stop to rest.

Theory and Practice of Science and TechnologyVol. 6(2)
Affordable and clean energy
Openalex Percentile: Top 94%
Advanced Sensor and Control Systems
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.