| Title |
Smart Traffic Light Scheduling in Smart City Using Image and Video Processing |
| ID_Doc |
38336 |
| Authors |
Razavi, M; Hamidkhani, M; Sadeghi, R |
| Title |
Smart Traffic Light Scheduling in Smart City Using Image and Video Processing |
| Year |
2019 |
| Published |
|
| DOI |
10.1109/iicita.2019.8808836 |
| Abstract |
The growing population and increased vehicles lead to the main challenges in urban life. Therefore, the role of traffic management will save time and fuel consumption and reduce environmental pollution. In recent years, Internet of Things (IoT) and smart cities drive a new field of intelligent traffic management. In this paper, a new method for traffic light control is presented by using the combination of IoT and image and video processing techniques. In the proposed models, traffic light scheduling is determined based on the density and the number of passing vehicles. Moreover, it is implemented by Raspberry-Pi board and OpenCV tool. The analytical and experimental results indicate the efficiency provided by the proposed models in intelligent traffic management. |
| Author Keywords |
Internet of things; Smart city; Traffic management; Raspberry Pi; Image and video processing |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Conference Proceedings Citation Index - Science (CPCI-S) |
| EID |
WOS:000701425000007 |
| WoS Category |
Computer Science, Software Engineering; Telecommunications |
| Research Area |
Computer Science; Telecommunications |
| PDF |
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