| Issue |
ITM Web Conf.
Volume 47, 2022
2022 2nd International Conference on Computer, Communication, Control, Automation and Robotics (CCCAR2022)
|
|
|---|---|---|
| Article Number | 01021 | |
| Number of page(s) | 7 | |
| Section | Computer Science and System Design, Application | |
| DOI | https://doi.org/10.1051/itmconf/20224701021 | |
| Published online | 23 June 2022 | |
Design and implementation of intelligent monitoring system for public transport applications
1 College of Information Science and Technology, Zhongkai University of Agriculture and Engineering, Guangzhou, China
2 College of Computer Science, Guangdong University of Technology, Guangzhou, China
3 Datong Coal Mine Group Wajinwan Coal Industry Co., Ltd., Datong, China
* Corresponding author: Joan.hjq1980@zhku.edu.cn
With the rapid development of automobile technologies and great economic growth, cars have become more and more popular for their convenience. However, the increase in cars has caused serious air pollution and increased the probability of traffic accidents. This paper investigates the design and implementation of intelligent monitoring and early warning system, which can detect the traffic conditions and provide environmental monitoring data. To achieve a comprehensive monitor for both inside and outside the public transport, this system is based on the STC12C5A16S2 micro-controller and loaded with all kinds of sensors, such as alcohol sensors, temperature and humidity sensors, toxic gas sensors, photosensitive sensors and light sensors etc. If the system detects any abnormal situation, it will generate early warning signs in time to inform the driver and the traffic regulatory departments. Consequently, our intelligent monitoring system can protect the safety of passengers and reduce the incidence of traffic accidents.
Key words: Public transport / Environment monitoring / Early-warning / Intelligent control
© The Authors, published by EDP Sciences, 2022
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.