This paper presents a machine learning-based methodology for the classification and real-time statistical analysis of vehicular traffic to facilitate the assessment of traffic flow on important routes. We propose a system architecture model to integrate monitoring devices, data processing capabilities, and user interaction through interfaces, including a 3D WebGIS system utilized for the simulation of traffic system. Moreover, this study conducts experimental scenarios to evaluate the system's performance in the context of traffic management and monitoring in Da Nang.The results of this research not only provide valuable insights for planners in monitoring and coordinating traffic flow but also contribute to the construction of a Digital Twin system, thereby supporting the future development of smart city.