Recently, Image processing has advanced Faster and applied in many fields, including health, industry, and transportation. In the transportation sector, object detection is widely used to improve security, for example, in traffic security and passenger crossings at train stations. Some accidents occur in the train crossing area at the station, like passengers uncarefully when passing through the yellow line. So further security needs to be developed. Additional technology is required to reduce the number of accidents. This paper focuses on passenger detection applications at train stations using YOLOX and Edge AI Accelerator hardware. the performance of the AI accelerator will be compared with Jetson Orin Nano. The experimental results show that the Hailo-8 AI hardware accelerator has higher accuracy than Jetson Orin Nano (improvement of over 12%) and has lower latency than Jetson Orin Nano (reduced 20 ms).

翻译：近年来，图像处理技术发展迅速，已广泛应用于医疗、工业与交通等多个领域。在交通领域，目标检测技术被广泛用于提升安全性，例如在交通安防与火车站行人过街场景中。火车站站台区域仍会发生安全事故，例如乘客不慎越过黄色安全线。因此需要进一步发展安防技术，需借助额外技术手段降低事故发生率。本文聚焦于采用YOLOX模型与边缘AI加速器硬件的火车站行人检测应用，将AI加速器的性能与Jetson Orin Nano进行对比。实验结果表明：Hailo-8 AI硬件加速器相比Jetson Orin Nano具有更高检测精度（提升超过12%），同时具有更低延迟（减少20毫秒）。