Edge-computing video analytics for real-time traffic monitoring in a smart city

Authors

Johan Barthelemy, University of WollongongFollow
Nicolas R. Verstaevel, University of WollongongFollow
Hugh I. Forehead, University of WollongongFollow
Pascal Perez, University of WollongongFollow

RIS ID

135246

Publication Details

Barthelemy, J., Verstaevel, N. R., Forehead, H. I. & Perez, P. (2019). Edge-computing video analytics for real-time traffic monitoring in a smart city. Sensors, 19 (9), 2048-1-2048-23.

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.