{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,3]],"date-time":"2026-06-03T15:25:48Z","timestamp":1780500348000,"version":"3.54.1"},"reference-count":34,"publisher":"MDPI AG","issue":"10","license":[{"start":{"date-parts":[[2024,5,10]],"date-time":"2024-05-10T00:00:00Z","timestamp":1715299200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"SM-Optics and the Ministry of University and Research 305","award":["E12B22000540006"],"award-info":[{"award-number":["E12B22000540006"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>We present the use of interconnected optical mesh networks for early earthquake detection and localization, exploiting the existing terrestrial fiber infrastructure. Employing a waveplate model, we integrate real ground displacement data from seven earthquakes with magnitudes ranging from four to six to simulate the strains within fiber cables and collect a large set of light polarization evolution data. These simulations help to enhance a machine learning model that is trained and validated to detect primary wave arrivals that precede earthquakes\u2019 destructive surface waves. The validation results show that the model achieves over 95% accuracy. The machine learning model is then tested against an M4.3 earthquake, exploiting three interconnected mesh networks as a smart sensing grid. Each network is equipped with a sensing fiber placed to correspond with three distinct seismic stations. The objective is to confirm earthquake detection across the interconnected networks, localize the epicenter coordinates via a triangulation method and calculate the fiber-to-epicenter distance. This setup allows early warning generation for municipalities close to the epicenter location, progressing to those further away. The model testing shows a 98% accuracy in detecting primary waves and a one second detection time, affording nearby areas 21 s to take countermeasures, which extends to 57 s in more distant areas.<\/jats:p>","DOI":"10.3390\/s24103041","type":"journal-article","created":{"date-parts":[[2024,5,13]],"date-time":"2024-05-13T11:18:17Z","timestamp":1715599097000},"page":"3041","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":12,"title":["Environmental Surveillance through Machine Learning-Empowered Utilization of Optical Networks"],"prefix":"10.3390","volume":"24","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7989-6879","authenticated-orcid":false,"given":"Hasan","family":"Awad","sequence":"first","affiliation":[{"name":"Department of Electronics and Telecommunications, Polytechnic University of Turin, 10129 Turin, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fehmida","family":"Usmani","sequence":"additional","affiliation":[{"name":"Department of Electronics and Telecommunications, Polytechnic University of Turin, 10129 Turin, Italy"},{"name":"School of Electrical Engineering and Computer Science (SEECS), National University of Sciences & Technology (NUST), Islamabad 45400, Pakistan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2682-6110","authenticated-orcid":false,"given":"Emanuele","family":"Virgillito","sequence":"additional","affiliation":[{"name":"Department of Electronics and Telecommunications, Polytechnic University of Turin, 10129 Turin, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rudi","family":"Bratovich","sequence":"additional","affiliation":[{"name":"SM-Optics, 20093 Cologno Monzese, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Roberto","family":"Proietti","sequence":"additional","affiliation":[{"name":"Department of Electronics and Telecommunications, Polytechnic University of Turin, 10129 Turin, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7834-2751","authenticated-orcid":false,"given":"Stefano","family":"Straullu","sequence":"additional","affiliation":[{"name":"LINKS Foundation, 10129 Turin, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8041-2392","authenticated-orcid":false,"given":"Francesco","family":"Aquilino","sequence":"additional","affiliation":[{"name":"LINKS Foundation, 10129 Turin, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rosanna","family":"Pastorelli","sequence":"additional","affiliation":[{"name":"SM-Optics, 20093 Cologno Monzese, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Vittorio","family":"Curri","sequence":"additional","affiliation":[{"name":"Department of Electronics and Telecommunications, Polytechnic University of Turin, 10129 Turin, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2024,5,10]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"100006","DOI":"10.1016\/j.rockmb.2022.100006","article-title":"Cross-fault Newton force measurement for Earthquake prediction","volume":"1","author":"He","year":"2022","journal-title":"Rock Mech. 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