{"id":4635,"date":"2023-08-24T17:56:14","date_gmt":"2023-08-24T17:56:14","guid":{"rendered":"https:\/\/dailyai.com\/?p=4635"},"modified":"2023-08-24T19:25:08","modified_gmt":"2023-08-24T19:25:08","slug":"researchers-harness-satellite-data-to-create-accurate-tsunami-warning-system","status":"publish","type":"post","link":"https:\/\/dailyai.com\/it\/2023\/08\/researchers-harness-satellite-data-to-create-accurate-tsunami-warning-system\/","title":{"rendered":"I ricercatori sfruttano i dati satellitari per creare un accurato sistema di allarme tsunami"},"content":{"rendered":"<p><b>I ricercatori hanno utilizzato l'intelligenza artificiale per identificare i cambiamenti nell'atmosfera terrestre generati quando si formano le onde di tsunami in mare.\u00a0<\/b><\/p>\n<p><span style=\"font-weight: 400;\">Questo potrebbe allungare notevolmente il tempo di allerta per le comunit\u00e0 costiere esposte al rischio di tsunami.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Valentino Constantinou della Terran Orbital Corporation, con sede in Florida, spiega: \"Non esiste una rete globale per il rilevamento delle onde di tsunami e l'installazione di hardware fisico, come i sistemi basati su boe, \u00e8 costosa. Ma sappiamo che le piccole costellazioni di satelliti stanno proliferando ovunque\".<\/span><\/p>\n<p><span style=\"font-weight: 400;\">La velocit\u00e0 dei segnali prodotti dai terremoti in mare \u00e8 influenzata dalla densit\u00e0 delle particelle cariche nella ionosfera terrestre, che si trova a circa 300-350 chilometri dalla superficie. <\/span><\/p>\n<p><span style=\"font-weight: 400;\">Quando uno tsunami genera onde d'urto che salgono nell'atmosfera, alterano la densit\u00e0 di queste particelle cariche, provocando lievi ma rilevabili modifiche nei segnali ricevuti dai satelliti.<\/span><\/p>\n<p><span style=\"font-weight: 400;\"><a href=\"https:\/\/www.jpl.nasa.gov\/news\/scientists-look-to-skies-to-improve-tsunami-detection\">Ricerca precedente<\/a> condotto dal Jet Propulsion Laboratory della NASA e dall'Universit\u00e0 Sapienza di Roma in Italia, ha portato a un metodo computazionale per misurare le fluttuazioni della densit\u00e0 delle particelle cariche dovute agli tsunami.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Partendo da questo presupposto, Constantinou e il suo team hanno convertito i dati, originariamente in formato monodimensionale, in immagini bidimensionali. Queste immagini sono state poi analizzate da modelli di intelligenza artificiale alla ricerca di segni legati agli tsunami.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Il team ha addestrato il sistema di intelligenza artificiale utilizzando i dati di tre specifici tsunami indotti da terremoti: quello cileno del 2010, quello giapponese del 2011 e quello canadese del 2012.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Hanno testato l'efficacia del modello su un quarto tsunami causato dal terremoto di Illapel del 2015 in Cile. L'IA \u00e8 stata esaminata per valutare quanto fosse in grado di differenziare i cambiamenti indotti dallo tsunami dal rumore di fondo ionosferico standard.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Per ridurre al minimo i falsi positivi, i ricercatori hanno filtrato i disturbi causati dalle stazioni di terra in comunicazione con i satelliti sopraelevati.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Secondo Quentin Brissaud del NORSAR, una fondazione di ricerca sismica norvegese non collegata allo studio, questa metodologia ha dato \"risultati piuttosto buoni\" con un tasso di precisione di rilevamento superiore a 90%. Tuttavia, Brissaud ha sottolineato che sarebbero necessari ulteriori dati per accertare l'affidabilit\u00e0 di questo sistema per diversi tipi di tsunami.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Quentin Brissaud osserva che \"la rarit\u00e0 dei grandi tsunami rende difficile l'analisi e la previsione di questi eventi\".<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Una delle sfide per la realizzazione di un sistema di allerta tsunami globale \u00e8 la necessit\u00e0 di condividere i dati a livello internazionale. Come dice Constantinou, \"i dati sono spesso in possesso dei governi o dei partner commerciali che gestiscono i satelliti. Non c'\u00e8 un unico posto dove raccogliere i dati per un sistema globale\".<\/span><\/p>\n<h2><span style=\"font-weight: 400;\">Per saperne di pi\u00f9 sullo studio<\/span><\/h2>\n<p><span style=\"font-weight: 400;\">Questo <\/span><a href=\"https:\/\/arxiv.org\/pdf\/2308.04611.pdf\"><span style=\"font-weight: 400;\">studio<\/span><\/a><span style=\"font-weight: 400;\"> combina i dati satellitari con l'apprendimento automatico (ML) per analizzare i cambiamenti nell'atmosfera terrestre innescati dagli tsunami.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Sebbene il rilevamento degli tsunami sia progredito di recente, molte coste hanno ancora una copertura inadeguata da parte dei sistemi di allerta precoce.\u00a0<\/span><\/p>\n<p>Ecco come funziona:<\/p>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">I ricercatori hanno sviluppato un framework basato sull'intelligenza artificiale per identificare i primi segnali di tsunami monitorando le perturbazioni ionosferiche itineranti (TID) nella ionosfera terrestre. Queste perturbazioni influenzano il contenuto totale di elettroni (TEC), rilevabile attraverso il sistema globale di navigazione satellitare (GNSS).<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Questo approccio sfrutta i dati di pi\u00f9 sistemi satellitari come GPS, Galileo, GLONASS e BeiDou. Offre una copertura in tempo reale e in mare aperto, che rappresenta un valido complemento per le aree geografiche non accessibili ai tradizionali sistemi di allerta basati su boe.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Il modello AI utilizza reti neurali convoluzionali (CNN) addestrate sui dati storici degli tsunami di Maule del 2010, Tohoku del 2011 e Haida-Gwaii del 2012. Successivamente \u00e8 stato convalidato con i dati dello tsunami di Illapel del 2015, ottenendo un punteggio di precisione di 91,7%.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Il sistema impiega una strategia di mitigazione dei falsi positivi (FPM), che riduce significativamente il tasso di falsi allarmi.<\/span><\/li>\n<\/ul>\n<p>Molti sistemi di IA vengono impiegati per prevedere i disastri ambientali, tra cui <a href=\"https:\/\/dailyai.com\/it\/2023\/08\/googles-ai-flood-detection-system-predicts-floods-four-days-in-advance\/\">Hub alluvionale di Google<\/a>che \u00e8 stato recentemente ampliato per coprire altre regioni.<\/p>","protected":false},"excerpt":{"rendered":"<p>I ricercatori hanno utilizzato l'intelligenza artificiale per identificare i cambiamenti nell'atmosfera terrestre generati quando le onde di tsunami iniziano a formarsi in mare.  Questo potrebbe allungare notevolmente i tempi di allerta per le comunit\u00e0 costiere esposte al rischio di tsunami. Valentino Constantinou della Terran Orbital Corporation, con sede in Florida, spiega: \"Non esiste una rete globale per rilevare le onde di tsunami e l'installazione di hardware fisico, come i sistemi basati sulle boe, \u00e8 costosa. Ma sappiamo che le piccole costellazioni di satelliti stanno proliferando ovunque\". La velocit\u00e0 dei segnali prodotti dai terremoti in mare \u00e8 influenzata dalla densit\u00e0 delle particelle cariche nella ionosfera terrestre, che si trova a circa 300-350 chilometri dalla superficie.<\/p>","protected":false},"author":2,"featured_media":4636,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[84],"tags":[337,105],"class_list":["post-4635","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-industry","tag-climate-science","tag-machine-learning"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.4 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Researchers harness satellite data to create accurate tsunami warning system | DailyAI<\/title>\n<meta name=\"description\" content=\"Researchers have proven that AI can identify changes in Earth&#039;s atmosphere generated when tsunami waves start forming at 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