Proceedings of the 2018 International Symposium on Communication Engineering & Computer Science (CECS 2018)

Research on the Application Prospect of Big Data Technology in Intelligent Transportation

Authors
Yan Hou
Corresponding Author
Yan Hou
Available Online July 2018.
DOI
10.2991/cecs-18.2018.13How to use a DOI?
Keywords
big data; intelligent transportation; application prospect.
Abstract

In the new era of Internet and big data, urban traffic has been effectively relieved, which mainly benefits from the reasonable application of big data technology. The fully expression of application advantages of big data has improved urban traffic jam and helped intelligent transportation service more perfect, guaranteeing the intelligent development of urban traffic transportation. This paper will mainly analyze the application of big data technology in intelligent transportation and understand the current status of heavy urban traffic combining with present urbanization. And the scientific plan of its application prospect will be made to timely relieve such situation and improve the service model of intelligent transportation.

Copyright
© 2018, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2018 International Symposium on Communication Engineering & Computer Science (CECS 2018)
Series
Advances in Computer Science Research
Publication Date
July 2018
ISBN
978-94-6252-571-9
ISSN
2352-538X
DOI
10.2991/cecs-18.2018.13How to use a DOI?
Copyright
© 2018, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Yan Hou
PY  - 2018/07
DA  - 2018/07
TI  - Research on the Application Prospect of Big Data Technology in Intelligent Transportation
BT  - Proceedings of the 2018 International Symposium on Communication Engineering & Computer Science (CECS 2018)
PB  - Atlantis Press
SP  - 67
EP  - 71
SN  - 2352-538X
UR  - https://doi.org/10.2991/cecs-18.2018.13
DO  - 10.2991/cecs-18.2018.13
ID  - Hou2018/07
ER  -