Real-time classification of underwater earthquakes based on acoustic signals enables earlier, more reliable disaster preparation. Researchers have developed an AI-powered early warning system for tsunamis that uses acoustic technology and hydrophones to measure and classify underwater earthquakes
in the U.K. developed an early warning system that combines state-of-the-art acoustic technology with artificial intelligence to immediately classify earthquakes and determine potential tsunami risk.
“Tectonic events with a strong vertical slip element are more likely to raise or lower the water column compared to horizontal slip elements,” said co-author Bernabe Gomez. “Thus, knowing the slip type at the early stages of the assessment can reduce false alarms and enhance the reliability of the warning systems through independent cross-validation.”
In these cases, time is of the essence, and relying on deep ocean wave buoys to measure water levels often leaves insufficient evacuation time. Instead, the researchers propose measuring the acoustic radiation produced by the earthquake, which carries information about the tectonic event and travels significantly faster than tsunami waves. Underwater microphones, called hydrophones, record the acoustic waves and monitor tectonic activity in real-time.
The computational model triangulates the source of the earthquake from the hydrophones and AI algorithms classify its slip type and magnitude. It then calculates important properties like effective length and width, uplift speed, and duration, which dictate the size of the tsunami.
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