| Title | Edge-Computing Video Analytics for Real-Time Traffic Monitoring in a Smart City |
|---|---|
| ID_Doc | 38227 |
| Authors | Barthélemy, J; Verstaevel, N; Forehead, H; Perez, P |
| Title | Edge-Computing Video Analytics for Real-Time Traffic Monitoring in a Smart City |
| Year | 2019 |
| Published | Sensors, 19, 9 |
| Abstract | The increasing development of urban centers brings serious challenges for traffic management. In this paper, we introduce a smart visual sensor, developed for a pilot project taking place in the Australian city of Liverpool (NSW). The project's aim was to design and evaluate an edge-computing device using computer vision and deep neural networks to track in real-time multi-modal transportation while ensuring citizens' privacy. The performance of the sensor was evaluated on a town center dataset. We also introduce the interoperable Agnosticity framework designed to collect, store and access data from multiple sensors, with results from two real-world experiments. |
| https://www.mdpi.com/1424-8220/19/9/2048/pdf?version=1556781090 |
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