Researchers tap artificial intelligence technology for development of tsunami warning system

A tsunami is a series of giant waves caused by either an earthquake or volcanic eruption. The events are not rare, and according to a global database, tsunamis that cause death and destruction happen about twice a year. Areas of the U.S. that are at the highest risk for impacts from a tsunami are Hawaii, Alaska and the West Coast.

One of the most powerful and destructive forces in nature may now be easier to detect due to the advancement of tsunami early-warning technology by university researchers.

In a recent publication in the scientific journal of Physics of Fluids, researchers detailed how members used underwater microphones to measure sound waves produced by earthquakes and develop early warning technology.

According to NOAA, tsunami waves can be triggered by changes in terrain and reach 100 feet high. Due to the power of the fast-moving water, they can be destructive for coastal communities and carry debris out to sea.


Buoys and other observation devices are used to detect and observe these giant waves as they move across the ocean, but sometimes their discovery can be imprecise, leading to inaccurate and delayed warnings.

Earthquakes are known to produce sound radiation, which travels faster than the tectonic event and associated tsunami waves.

Researchers said the introduction of underwater microphones and the use of artificial intelligence helped them triangulate the magnitude and power of the underwater current quicker than current detection methods.

"Acoustic radiation travels through the water column much faster than tsunami waves. It carries information about the originating source, and its pressure field can be recorded at distant locations, even thousands of kilometers away from the source. The derivation of analytical solutions for the pressure field is a key factor in the real-time analysis," Usama Kadri, a co-author of the publication, said in a statement.

Work being completed at the University of California and Cardiff University in the United Kingdom is part of a larger project that experts hope will enhance hazard warning systems.