一种基于无源Wi-Fi的城市流量监测系统

2022 IEEE International Conference on Industry 4.0, Artificial Intelligence, and Communications Technology (IAICT) Pub Date : 2022-07-28 DOI:10.1109/IAICT55358.2022.9887478

M. Bertolusso, G. Pettorru, M. Spanu, M. Fadda, M. Sole, M. Anedda, D. Giusto

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引用次数: 0

摘要

本文提出了一种基于Wi-Fi嗅探设备和使用机器学习技术进行实时数据处理的创新车辆监控系统。我们的解决方案涉及构建一个基于神经网络的多类分类器，该分类器可以根据接收到的信号强度对来自多个源的传入Wi-Fi信号进行分类。通过训练神经网络来预测不同车辆(0-30Km/h、30-60Km/h、60-90Km/h、90-120Km/h)和0-15Km/h的行人速度区间对应的不同输出类，从而实现该方案的求解。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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A passive Wi-Fi based monitoring system for urban flows detection

This paper presents an innovative vehicle monitoring system based on Wi-Fi sniffing devices and real-time data processing using machine learning techniques. Our solution involves the construction of a neural network-based multiclass classifier that can classify the incoming Wi-Fi signal from many sources based on the received signal strength. The solution was carried out by training the neural network to predict different output classes corresponding to different vehicular (0-30Km/h,30-60Km/h, 60-90Km/h, 90-120Km/h) and several pedestrian speed ranges among 0-15Km/h.

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2022 IEEE International Conference on Industry 4.0, Artificial Intelligence, and Communications Technology (IAICT)

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