Port Intelligent Supervision Based On 5G Edge Computing Boxes

In this paper, an edge computing box design method based on deep learning and embedded system is proposed to address the problems of complex harbor operating environment and frequent safety accidents. The computing box is based on Nvidia's Jetson Nano hardware architecture, and a Pedestrian net deep neural network model specialized in human and vehicle detection is developed through TensorRT and Deepstream. The computational box designed by this method supports secondary development and fast iteration, and can be flexibly adapted to various mainstream video processing AI models. Experiments show that the computational box has good computational real-time performance and extremely fast inference speed, which guarantees the deploy ability of port security and intelligent supervision in embedded terminal equipment.