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A traffic data collection and analysis method based on wireless sensor network

机译:基于无线传感器网络的流量数据收集与分析方法

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摘要

Abstract With the rapid development of urbanization, collecting and analyzing traffic flow data are of great significance to build intelligent cities. The paper proposes a novel traffic data collection method based on wireless sensor network (WSN), which cannot only collect traffic flow data, but also record the speed and position of vehicles. On this basis, the paper proposes a data analysis method based on incremental noise addition for traffic flow data, which provides a criterion for chaotic identification. The method adds noise of different intensities to the signal incrementally by an improved surrogate data method and uses the delayed mutual information to measure the complexity of signals. Based on these steps, the trend of complexity change of mixed signal can be used to identify signal characteristics. The numerical experiments show that, based on incremental noise addition, the complexity trends of periodic data, random data, and chaotic data are different. The application of the method opens a new way for traffic flow data collection and analysis.
机译:摘要随着城市化的快速发展,收集和分析交通流量数据对于建立智能城市具有重要意义。本文提出了一种基于无线传感器网络(WSN)的新型交通数据收集方法,其不能仅收集业务流量数据,而且还记录车辆的速度和位置。在此基础上,本文提出了一种基于增量噪声的数据分析方法,用于交通流数据,这提供了混沌识别的标准。该方法通过改进的代理数据方法逐步增加对信号的不同强度的噪声,并使用延迟的互信息来测量信号的复杂性。基于这些步骤,混合信号的复杂性变化的趋势可用于识别信号特性。数值实验表明,基于增量噪声添加,周期性数据,随机数据和混沌数据的复杂性趋势是不同的。该方法的应用为流量流数据收集和分析开辟了一种新方法。

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