DIBRIS, University of Genoa, via Dodecaneso, 35, 16146 Genoa, Italy.
DIFI, University of Genoa, via Dodecaneso, 33, 16146 Genoa, Italy.
Sensors (Basel). 2023 May 30;23(11):5210. doi: 10.3390/s23115210.
We present a device- and network-based solution for automatic passnger counting that operates on the edge in real time. The proposed solution consists of a low-cost WiFi scanner device equipped with custom algorithms for dealing with MAC address randomization. Our low-cost scanner is able to capture and analyze 802.11 probe requests emitted by passengers' devices such as laptops, smartphones, and tablets. The device is configured with a Python data-processing pipeline that combines data coming from different types of sensors and processes them on the fly. For the analysis task, we have devised a lightweight version of the DBSCAN algorithm. Our software artifact is designed in a modular way in order to accommodate possible extensions of the pipeline, e.g., either additional filters or data sources. Furthermore, we exploit multi-threading and multi-processing for speeding up the entire computation. The proposed solution has been tested with different types of mobile devices, obtaining promising experimental results. In this paper, we present the key ingredients of our edge computing solution.
我们提出了一种基于设备和网络的自动乘客计数解决方案，该解决方案在边缘实时运行。所提出的解决方案由一个低成本的 Wi-Fi 扫描器设备组成，该设备配备了用于处理 MAC 地址随机化的定制算法。我们的低成本扫描仪能够捕获和分析乘客设备（如笔记本电脑、智能手机和平板电脑）发出的 802.11 探测请求。该设备配置有一个 Python 数据处理管道，该管道将来自不同类型传感器的数据组合在一起，并实时处理它们。对于分析任务，我们设计了 DBSCAN 算法的轻量级版本。我们的软件工件采用模块化方式设计，以适应管道的可能扩展，例如，附加的过滤器或数据源。此外，我们利用多线程和多处理来加快整个计算速度。已经使用不同类型的移动设备对提出的解决方案进行了测试，得到了有希望的实验结果。在本文中，我们介绍了边缘计算解决方案的关键要素。
