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Detection and Identification of Human Locomotion by Distributed Acoustic Sensing with Deep Neural Networks

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Abstract

This paper reports intrusion detection using distributed acoustic sensors based on phase- sensitive enhanced Rayleigh scattering optical time-domain reflectometry. Vibration data induced by human locomotion was analyzed by convolution neural networks and achieve over 76.25% accuracy on human identification.

© 2020 The Author(s)

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