The advent of Low Power Wide Area Networks (LPWAN) has enabled the feasibility of wireless sensor networks for environmental traffic sensing across urban areas. In this study, we explore the usage of LoRaWAN end nodes as traffic sensing sensors to offer a practical traffic management solution. The monitored Received Signal Strength Indicator (RSSI) factor is reported and used in the gateways to assess the traffic of the environment. Our technique utilizes LoRaWAN as a long-range communication technology to provide a largescale system. In this work, we present a method of using LoRaWAN devices to estimate traffic flows. LoRaWAN end devices then transmit their packets to different gateways. Their RSSI will be affected by the number of cars present on the roadway. We used SVM and clustering methods to classify the approximate number of cars present. This paper details our experiences with the design and real implementation of this system across an area that stretches for miles in urban scenarios. We continuously measured and reported RSSI at different gateways for weeks. Results have shown that if a LoRaWAN end node is placed in an optimal position, up to 96% of correct environment traffic level detection can be obtained. Additionally, we share the l

翻译：低电广域网(LPWAN)的出现使得无线传感器网络在城市地区进行环境交通遥感的可行性成为城市地区的环境交通遥感的可行性。在这项研究中,我们探索使用LoRaWAN终端节点作为交通感应器,以提供一个切实可行的交通管理解决方案。监测到的接收信号强度指标(RSSI)系数被报告并用于网关,以评估环境交通情况。我们的技术利用LoRaWAN作为远程通讯技术提供大型系统。在这项工作中,我们提出了一个使用LoRaWAN装置来估计交通流量的方法。LoRaWAN终端装置然后将其包传送到不同的网关。LORAWAN终端装置将受到公路上汽车数量的影响。我们使用SVM和集群方法对车辆的大致数量进行分类。本文详细介绍了我们在城市景象长达数英里的地区设计和实际实施这一系统的经验。我们连续几周在不同关口持续测量和报告RSISI。结果显示,如果LRAWAN终端节点处于最佳位置,则可以分享到正确的交通水平的96%。