Machine Learning Based Analysis of Optical Fiber Sensing Intensity Data for Train Tracking Application

This paper introduces an implementation of a system allowing to denoise the intensity data sensed by a DAS system before analyzing it through a convolutional neural network for train tracking. The results obtained showed that it is possible to track a train by focusing only on the magnitude of signals without caring out complex treatments.