Abstract
The current traffic monitoring system adopts the centralized cloud computing mode, which brings pressure on the computing load and network bandwidth of the cloud computing center. The edge computing platform based on edge devices can effectively solve the above problems by migrating some computing tasks to edge devices for execution. Vehicle detection and tracking is the core technology of intelligent traffic monitoring system, but its operation on edge devices will be limited by storage memory and computing speed. Therefore, it is necessary to simplify the network model to adapt to the operation on edge devices. This paper proposes a vehicle tracking algorithm based on YOLOX and DeepSORT and deploys it on the edge device Jetson Nano. Our experiment shows that the proposed method can meet the real-time requirements of edge devices.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
