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Early warning system for drivers’ phone usage with deep learning network

Authors :
J. H. Jixu Hou
Xiaofeng Xie
Qian Cai
Zhengjie Deng
Houqun Yang
Hongnian Huang
Xun Wang
Lei Feng
Yizhen Wang
Source :
EURASIP Journal on Wireless Communications and Networking, Vol 2022, Iss 1, Pp 1-11 (2022)
Publication Year :
2022
Publisher :
SpringerOpen, 2022.

Abstract

Abstract Dangerous driving, e.g., using mobile phone while driving, can result in serious traffic problem and threaten to safety. To efficiently alleviate such problem, in this paper, we design an intelligent monitoring system to detect the dangerous behavior while driving. The monitoring system is combined by a designed target detection algorithm, camera, terminal server and voice reminder. An efficiently deep learning model, namely Mobilenet combined with single shot multi-box detector (Mobilenet-SSD), was applied to identify the behavior of driver. To evaluate the performance of proposed system, a dangerous driving dataset,consisting of 6796 images, was constructed. The experimental results show that the proposed system can achieve the accuracy of 99%, and could be used for real-time monitoring of the drivers’ status.

Details

Language :
English
ISSN :
16871499
Volume :
2022
Issue :
1
Database :
Directory of Open Access Journals
Journal :
EURASIP Journal on Wireless Communications and Networking
Publication Type :
Academic Journal
Accession number :
edsdoj.891e515339fb4697ad40dd3d517fa8ce
Document Type :
article
Full Text :
https://doi.org/10.1186/s13638-022-02121-7