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Field Tests of Impulsive Acoustic Event Detection, Localization, and Classification Over Telecom Fiber Networks

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Field Tests of Impulsive Acoustic Event Detection, Localization, and Classification Over Telecom Fiber Networks We report distributed-fiber-optic-sensing results on impulsive acoustic events localization/classification over telecom networks. A deep-learning-based model was trained to classify starter-gun and fireworks signatures with high accuracy of > 99% using fiber-based-signal-enhancer and >97% using aerial coils.

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Template Matching Method with Distributed Acoustic Sensing Data and Simulation Data

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Template Matching Method with Distributed Acoustic Sensing Data and Simulation Data We propose a new method to detect acoustic signals by matching distributed acoustic sensing data with simulation. In the simulation of the dynamic strain on an optical fiber, the optical fiber layouts and the gauge length are properly incorporated. We apply the proposed method to the acoustic-source localization and demonstrate the method localizes the source accurately even under the layouts which include the straight optical fiber for the sensing points with the large gauge-length settings.

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Optical Fiber Sensing Technology Visualizing the Real World via Network Infrastructures – AI technologies for traffic monitoring

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Optical Fiber Sensing Technology Visualizing the Real World via Network Infrastructures – AI technologies for traffic monitoring Optical fibers have a sensing function that captures environmental changes around the fiber cable. According to the recent technology evolution of optical transmission and AI, the application of the fiber sensing has expanded and visualization accuracy has improved. We have proposed to monitor the traffic flow on the road using the existing optical fiber infrastructure along the road. In this paper, we propose a traffic flow analysis AI algorithm with high environmental resistance and show the evaluation results of traffic monitoring.

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