The Evolving Science of Earthquake Prediction

Earthquake prediction has long been seen as impossible. While countries like Japan, Mexico, and the US use early warning systems, these only react seconds before shaking begins. Now, advances in artificial intelligence (AI), machine learning (ML), and the Internet of Things (IoT) are beginning to reshape what might be possible.
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MIT researchers have shown how ML can detect patterns in seismic data, including slow earthquakes—minor shifts that often precede major quakes. AI is helping in seismic wave analysis, aftershock forecasting, and even predicting fault ruptures in lab settings where humans detect nothing.
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A broader scientific review supports these developments. AI models—such as deep learning, SVM, and ANN—perform well when integrated with traditional tools like GPS, satellite data, and seismometers. However, many models still overlook hydrogeological factors like underground water flow and fluid pressure, which may hold the key to better predictions.
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IoT technology supports this by collecting real-time, location-specific data from sensors, feeding AI systems and refining accuracy. Still, challenges like limited sensor coverage and high computational demands remain.
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While precise prediction remains out of reach, the combination of AI, IoT, and geoscience brings us closer than ever.
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Cathcart Technology stands in solidarity with everyone affected by the recent earthquake in Thailand. Our thoughts are with all those impacted. From all of us at Cathcart Technology, we’re sending strength, compassion, and hope to our community as recovery efforts continue.

Sources: The role of artificial intelligence and IoT in prediction of earthquakes 
and How machine learning might unlock earthquake prediction