Design and implementation of LED lighting intelligent control system for expressway tunnel entrance based on Internet of things and fuzzy control

Ying Lu, Jin Wang, Xiaojun Bai and Hehan Wang

International Journal of Distributed Sensor Networks, 2020, vol. 16, issue 5, 1550147720925742

Abstract: Due to the special characteristics of highway tunnels and vehicles, the interior of the tunnel is required to provide appropriate lighting to ensure the safety of driving vehicles, especially at the entrance section of the tunnel. At present, most of the tunnel entrance lighting control system only considers one single factor, the brightness outside the tunnel. However, in practice, the required lighting brightness in the tunnel is also related to traffic flow, speed, and other factors. Comprehensively utilizing these factors to improve the control strategy is urgently needed. To deal with this problem, this article has designed a multi-source information acquisition system for tunnel lighting based on the Internet of things technology, which combined with fuzzy control theory in order to develop an intelligent control system for LED lighting at the entrance section of the tunnel. The designed system was implemented and long-term tested in a real highway tunnel. The experimental results have shown that the system designed in this article can automatically control the brightness of the lighting inside the tunnel according to the real-time measurements of the brightness outside the tunnel, traffic flow, speed, and so on. Furthermore, the utilizations of the system can minimize the human and power consumption of tunnel lighting while ensuring the safety of tunnel traffic.

Keywords: Expressway tunnel; LED lighting; intelligent control; Internet of things; fuzzy control theory (search for similar items in EconPapers)
Date: 2020
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
https://journals.sagepub.com/doi/10.1177/1550147720925742 (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:sae:intdis:v:16:y:2020:i:5:p:1550147720925742

DOI: 10.1177/1550147720925742

Access Statistics for this article

More articles in International Journal of Distributed Sensor Networks
Bibliographic data for series maintained by SAGE Publications ().