New Early Tsunami Warning System Employs AI and Rapidly-Moving Deep-Sea Sound Waves: Tsunamis are massive waves of water that may move as quickly as jet aircraft across deep oceans. They are caused by earthquakes that occur deep below the surface of the water or by volcanic eruptions. As they migrate inland, their structures become ever more towering, dealing devastating blows to people’s lives and the livelihoods they depend on in coastal communities.
In spite of the fact that they have the capacity to do catastrophic damage, tsunamis may be especially stealthy, which is why reliable early warning systems are required to forecast when they will strike. And the present warning systems, which are dependent on sea buoys and seismic sensors to identify earthquakes that occur underwater, aren’t always precise in anticipating the hazards that the subsequent tsunamis would pose.
Acoustic-gravity waves, which are the subject of research that was headed by Cardiff University, are something that has been presented as a potential solution to this problem. These waves can move considerably more quickly than tsunami waves.
Acoustic-gravity waves are sound waves that occur naturally and travel thousands of kilometers into the deep water at a speed that is substantially quicker than that of tsunami waves. These waves contain essential information about earthquakes and the sources of the tsunamis that they generate.
Integrating acoustic technology with artificial intelligence (AI) allows the new system to monitor tectonic activity in real time, allowing it to rapidly categorize earthquakes that occur under the ocean’s surface and assess the likelihood of tsunamis occurring.
Dr. Usama Kadri, co-author of the study, explains, “Our research demonstrates how to obtain rapid and accurate information about the size and scale of tsunamis by monitoring acoustic-gravity waves.” According to Dr. Kadri, “these waves travel through the water much faster than tsunami waves, allowing more time for evacuation before landfall.” Our research demonstrates how to quickly and accurately obtain information regarding the magnitude and scope of tsunamis.
Researchers measured the amount of acoustic radiation created by 200 earthquakes that rocked the Pacific and Indian Oceans by listening to sound recordings (acoustic radiation) that were caught by underwater microphones (hydrophones). This allowed the researchers to construct this method.
After that, the group used a computer model in order to pinpoint the source of the tectonic event, utilizing the aforementioned hydrophone recordings in addition to the data from the already existing sea buoys and seismic sensors.
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And lastly, the artificial intelligence algorithms categorized the slip type of the earthquake (the kind of fault that creates the earthquake), the magnitude of the earthquake, and other essential aspects that affect the size of the tsunami wave.
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Real-time categorization of undersea earthquakes, which are what cause tsunamis, would allow for earlier and more accurate tsunami warnings. This is because the danger of a tsunami is greatly dependent on the characteristics of the earthquake that causes it.
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