AI-aided Enhanced Low-cost Dense Seismic Monitoring

Abstract

Earthquakes are very dangerous events. Massive urban earthquakes continue to kill and injure hundreds of thousands of people and cause long-term damage to people, societies, and businesses. The motivation and research behind choosing this topic is to use Artificial intelligence to get better results of seismic events/activities. Keeping in the view accuracy and more effective monitoring of seismic activities, our hypothesis says that using the deep learning in a wise way can bring up an economy-friendly method for efficient analysis of seismology activities in Pakistan. Our goal throughout the whole project will be to gather seismic data with the help of sensors and process them on different technologies to produce the best output on which we can deliver the crystalclear analysis of seismic activities. So, overcoming this problem would not be a big level as there are many approaches that can be implemented. At the end of this project, we hope to have accurate monitoring of seismic events while keeping it a low-cost methodology. Using convolutional neural networks to distinguish between explosive and tectonic origins at local distances, they demonstrated that generated models can successfully identify the source type of events with an accuracy of greater than 99.9%