Modern-day life is driven by electronic devices connected to the internet. The emerging research field of the Internet-of-Things (IoT) has become popular, just as there has been a steady increase in the number of connected devices. Since many of these devices are utilised to perform CV tasks, it is essential to understand their power consumption against performance. We report the power consumption profile and analysis of the NVIDIA Jetson Nano board while performing object classification. The authors present an extensive analysis regarding power consumption per frame and the output in frames per second using YOLOv5 models. The results show that the YOLOv5n outperforms other YOLOV5 variants in terms of throughput (i.e. 12.34 fps) and low power consumption (i.e. 0.154 mWh/frame).

翻译：现代日常生活离不开连接互联网的电子设备。随着联网设备数量持续增长，新兴的物联网（IoT）研究领域日益受到关注。由于许多此类设备被用于执行计算机视觉任务，理解其性能与功耗之间的权衡关系至关重要。本文报告了NVIDIA Jetson Nano开发板在执行目标分类任务时的功耗特征及分析结果。作者针对使用YOLOv5模型进行每帧功耗与帧率输出进行了深入分析。结果表明，YOLOv5n在吞吐量（即12.34 fps）和低功耗（即0.154 mWh/帧）方面均优于其他YOLOv5变体。