Machine Learning-Driven Earthquake Early Warning Using Optical Fiber Mesh Networks
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.
Authors
- Rosanna Pastorelli
- Stefano Straullu
- Roberto Proietti (ORCID: https://orcid.org/0000-0001-6378-7005)
- Vittorio Curri (ORCID: https://orcid.org/0000-0003-0691-0067)
- Emanuele Virgillito (ORCID: https://orcid.org/0000-0003-2682-6110)
- Hasan Awad (ORCID: https://orcid.org/0000-0002-7989-6879)
- Rudi Bratovich
- Fehmida Usmani (ORCID: https://orcid.org/0000-0002-6462-9997)
- Francesco Aquilino (ORCID: https://orcid.org/0000-0002-8041-2392)
Institutions
- Politecnico di Torino (IT)
- LINKS Foundation (IT)
Publication Details
- Published
- 2024-11-10
- DOI
- https://doi.org/10.1109/ipc60965.2024.10799809
- Citations
- 1
- Primary Topic
- Seismology and Earthquake Studies
- Type
- article
- Field-Weighted Citation Impact
- 0.35