We demonstrate interconnected meshed optical networks as sensing-localization grid for earthquake early detection. We integrate noisy polarization evolution data induced by seven earthquakes, into a Waveplate model to enhance a machine-learning algorithm that accurately detects primary waves, improves urban safety and mimic real case scenarios.
Machine Learning-Driven Earthquake Early Warning Using Optical Fiber Mesh Networks / Awad, Hasan; Usmani, Fehmida; Virgillito, Emanuele; Bratovich, Rudi; Straullu, Stefano; Aquilino, Francesco; Proietti, Roberto; Pastorelli, Rosanna; Curri, Vittorio. - (2024), pp. 1-2. (Intervento presentato al convegno 2024 IEEE Photonics Conference, IPC 2024 tenutosi a Roma (Ita) nel 10-14 November, 2024) [10.1109/ipc60965.2024.10799809].
Machine Learning-Driven Earthquake Early Warning Using Optical Fiber Mesh Networks
Awad, Hasan;Usmani, Fehmida;Virgillito, Emanuele;Straullu, Stefano;Proietti, Roberto;Pastorelli, Rosanna;Curri, Vittorio
2024
Abstract
We demonstrate interconnected meshed optical networks as sensing-localization grid for earthquake early detection. We integrate noisy polarization evolution data induced by seven earthquakes, into a Waveplate model to enhance a machine-learning algorithm that accurately detects primary waves, improves urban safety and mimic real case scenarios.File | Dimensione | Formato | |
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IPC Machine Learning-Driven Earthquake Early Warning Using Optical Fiber Mesh Networks.pdf
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https://hdl.handle.net/11583/2997939