We investigate distributed fiber optic sensing and machine-learning-based image analysis for road-speed estimation. Synthetic phase-sensitive optical time-domain reflectometer (φ-OTDR) traces are generated by the simulation of random road features such as car density and speed. Consecutive φ-OTDR traces are stacked generating images that are submitted to a convolutional neural network (CNN) for classification. The evaluated CNN-based classifier exhibits high accuracy at sufficiently high car densities.
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