| Title |
Implementation of Vehicle Traffic Analysis Using Background Subtraction in The Internet of Things (IoT) Architecture |
| ID_Doc |
41058 |
| Authors |
Sofwan, A; Surur, FA; Arfan, M; Handoyo, E; Alvin, ASY; Somantri, M; Enda, WS |
| Title |
Implementation of Vehicle Traffic Analysis Using Background Subtraction in The Internet of Things (IoT) Architecture |
| Year |
2018 |
| Published |
|
| DOI |
|
| Abstract |
Vehicle traffic analysis is one of the features that are provided in a smart city application. A camera is used to capture vehicles that are moving through on the road. Background subtraction is applied in order to detect the moving object, i.e., Gaussian Mixture Model. The system is developed under the Internet of Things (IoT) architecture, which all devices are associated using Internet connection. The calculated value is transmitted into cloud and received at the virtual server. Data are saved to a database and are able to be accessed through a web interface. We observe the applied system provides a good performance in terms of average accuracy exceeds 95.64%. |
| Author Keywords |
Internet of Things; background subtraction; Gaussian Mixture Model; vehicle traffic; smart city |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Conference Proceedings Citation Index - Science (CPCI-S) |
| EID |
WOS:000517590900005 |
| WoS Category |
Computer Science, Artificial Intelligence; Computer Science, Information Systems |
| Research Area |
Computer Science |
| PDF |
|