Tsunami Prediction via Seismic Triangulation and Earthquake Magnitude Estimation Using Ground Based Seismic Data

Tsunami prediction is of paramount importance for safeguarding coastal communities against devastating natural disasters. While artificial intelligence models have garnered considerable attention in this domain, this research introduces a distinctive approach that utilizes signal processing techniques within the MATLAB environment. Addressing the critical problem of tsunami prediction, this methodology capitalizes on traditional techniques to estimate earthquake magnitude and locate the epicenter from seismic data. Leveraging the Fast Fourier Transform, Power Spectral Density analysis, and energy integration, the research refines the estimation of seismic event magnitudes. Additionally, an algorithm for detecting Primary (P) and Secondary (S) waves, along with triangulation techniques, is applied to determine the location of the epicenter precisely. These combined results enhance tsunami forecasting capabilities and reinforce community safety measures against the devastating impact of tsunamis.