A method for visualizing urban road events using distributed acoustic sensing

Abstract This study presents the construction of an urban underground sensing system using distributed acoustic sensing (DAS) technology, which utilizes the existing optical fiber infrastructure around urban roads for communication. To address the challenges posed by the complexity and variability of DAS data in infrastructure monitoring environments such as urban roads, as well as the difficulty and poor effectiveness of raw data visualization, a novel method for visualizing DAS data is proposed. This method involves preprocessing the data through wavelet threshold denoising, combining it with the root-mean-square (RMS) energy index to generate a visualization, and applying the dynamic threshold method to remove and suppress abnormal data indicators. Finally, this paper tested the visualization performance to assess the effectiveness of the proposed method in improving urban road safety management. The study focused on three typical urban road safety risk events: vehicle driving, construction, and road subsurface cavity incidents. The results demonstrate the efficacy of the data visualization method, showing improved visualization of vehicle trajectory directions and numbers, construction segment behaviors, and approximate road subsurface cavity locations in the time domain compared to the original data.