Intelligent acquisition algorithm of dynamic traffic data based on Internet of Things

In order to improve the intelligent traffic management and dispatching capabilities, it is required to optimize the design of intelligent acquisition of dynamic traffic data and optimize the processing of traffic data information by dynamically mining traffic data. Therefore, an intelligent acquisition algorithm of dynamic traffic data based on Internet of Things is proposed in this paper. In this algorithm, the distributed wireless sensor networking is used to construct an Internet of Things model of traffic data acquisition and optimize deployment and design of Internet of Things nodes for data acquisition; the adaptive weighted algorithm is used to process the fusion of dynamic traffic data to extract spectral characteristic quantity of dynamic traffic data, and the spectrum analysis method is used to perform anomaly detection to dynamic traffic data; then the detection results are conducted with fuzzy clustering, so as to realize intelligent acquisition of dynamic traffic data in Internet of Things environment. The simulation results show that in acquisition of dynamic traffic data, this method has high acquisition accuracy under different SNR. In this paper, when the SNR is 4 dB, the acquisition accuracy is 100, while the traditional method is up to 16 dB, the acquisition accuracy is 100. The proposed method has the advantages of high accuracy, good data recall, strong anti-interference ability during acquisition and good self-adaptability.