Paper Info
Title
An Implementation of Deep Learning based IoV System for Traffic Accident Collisions Detection with an Emergency Alert Mechanism
Abstract
This paper proposes a deep learning based Internet of vehicles system, which consists of an in-vehicle infotainment telematics platform with collisions detection sensors, a cloud based deep learning training server, and a web-based service platform. The proposed system implements deep learning based techniques to achieve traffic accident collisions detection and to provide related emergency announcement. As a result, the experimental result showed that the accuracy of traffic accident collisions detection can be achieved up to 96% and the average response time for related emergency announcement is approximately 7 seconds.
Year
DOI
Venue
2018
10.1109/ICCE-Berlin.2018.8576197
2018 IEEE 8th International Conference on Consumer Electronics - Berlin (ICCE-Berlin)
Keywords
Field
DocType
automotive,deep learning,driver assistance,driving safety,Internet of vehicles (IoV),traffic accident collisions detection
Computer science,Response time,Real-time computing,Traffic accident,Artificial intelligence,Deep learning,Telematics,Cloud computing,The Internet
Conference
ISSN
ISBN
Citations 
2166-6814
978-1-5386-6096-6
0
PageRank 
References 
Authors
0.34
0
7
Name
Order
Citations
PageRank
Liang-Bi Chen12618.40
Ke-Yu Su211.03
Yu-Ching Mo300.68
Wan-Jung Chang41312.53
Wei-Wen Hu524.14
Jing-Jou Tang632.84
Chao-Tang Yu702.03