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arXiv · 2409.03667

Threat Classification on Deployed Optical Networks Using MIMO Digital Fiber Sensing, Wavelets, and Machine Learning

Khouloud Abdelli·Henrique Pavani·Christian Dorize·Sterenn Guerrier·Haik Mardoyan·Patricia Layec·Jeremie Renaudier
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Abstract

We demonstrate mechanical threats classification including jackhammers and excavators, leveraging wavelet transform of MIMO-DFS output data across a 57-km operational network link. Our machine learning framework incorporates transfer learning and shows 93% classification accuracy from field data, with benefits for optical network supervision.

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Khouloud Abdelli, Henrique Pavani, Christian Dorize, Sterenn Guerrier, Haik Mardoyan, Patricia Layec, Jeremie Renaudier. 2024-09-05. Threat Classification on Deployed Optical Networks Using MIMO Digital Fiber Sensing, Wavelets, and Machine Learning. https://arxiv.org/abs/2409.03667

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