Driver drowsiness detection and smart alerting using deep learning and IoT-Reference-Cited by-同舟云学术

Driver drowsiness detection and smart alerting using deep learning and IoT

Published:2023-07 Issue: Volume:22 Page:100705
ISSN:2542-6605
Container-title:Internet of Things
language:en
Short-container-title:Internet of Things

Author:

Phan Anh-Cang^ORCID,Trieu Thanh-Ngoan^ORCID,Phan Thuong-Cang^ORCID

Publisher

Elsevier BV

Subject

Management of Technology and Innovation,Artificial Intelligence,Computer Science Applications,Hardware and Architecture,Engineering (miscellaneous),Information Systems,Computer Science (miscellaneous),Software

Reference38 articles.

1. . NHTSA, https://www.nhtsa.gov/risky-driving/drowsy-driving.

2. . NSC, https://www.nsc.org/road/safety-topics/fatigued-driver.

3. Prevalence of Motor Vehicle Crashes Involving Drowsy Drivers;Tefft,2014

Cited by 14 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Exploring Subjective Sleepiness with UnnCyberpsy, a Web-Based Psychophysiological Research Tool;Journal on Interactive Systems;2024-09-01

2. Automatic Detection of Driver Drowsiness and Distraction for Public Safety: Deep Learning Based Approach;2024 International Conference on Knowledge Engineering and Communication Systems (ICKECS);2024-04-18

3. Reliable data transmission for a VANET-IoIT architecture: A DNN approach;Internet of Things;2024-04

4. A New Method for Detecting the Fatigue Using Automated Deep Learning Techniques for Medical Imaging Applications;Wireless Personal Communications;2024-03

5. In the Blink of an Eye: Insomnia Microexpression Classification Using CNN-LSTM;2024 4th International Conference on Innovative Practices in Technology and Management (ICIPTM);2024-02-21