智能独立边缘物联网设备,用于智能城市的交通量统计

A. Philip, Amal Jacob, Tejus K, A. S, Aakash Ashok, Divya Kb
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引用次数: 0

摘要

交通量统计调查有助于分析在一段时间内通过特定路段的车辆数量和类别。这项工作建议设计和开发一个独立的边缘设备,以获得道路上的车辆数量,基于汽车、公共汽车、卡车、两轮车和机动三轮车等类别。YOLO v8模型和深度排序算法部署在Jetson nano作为边缘设备。设计了一个交互式仪表板,通过指定时间来获取每辆车的数量和类别。深度学习模型使用定制的真实世界数据集进行训练,并进一步优化以部署在Jetson nano上。因此,Jetson nano可以作为车辆计数的边缘物联网设备。对所提模型的分析显示出令人满意的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Smart Standalone Edge IoT Device for Traffic Volume Counting in Smart Cities
Traffic volume counting survey helps to get an analysis of number and class of vehicles passing through a particular road segment over a period. The work proposes design and development of a standalone edge device to obtain count of vehicles on road based on category like car, bus, truck, two wheeler and auto rickshaws. The YOLO v8 model along with Deep Sort algorithm is deployed over Jetson nano proposed as an edge device. An interactive dashboard is designed to obtain the count and class of each vehicle by specifying a time. The deep learning models are trained using custom real-world datasets and further optimized to be deployed on Jetson nano. Thus, Jetson nano serves as an edge IoT device for vehicle counting. The analysis of the proposed model indicates promising results.
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