Seismic Data Analysis and Earthquake Prediction with IoT Sensors and SmartGRU Model

Tectonic plate movement causes a slow accumulation of stress in the Earth’s lithosphere, especially around plate borders, leading to earthquakes. Anearthquakeoccurswhenthisstressovercomesfrictionalongafaultor exceeds the strength of the surrounding rock.Accurate earthquake predictionremainschallengingduetothecomplexityofseismicdataandthe limitations of traditional methods.This creates a pressing need for modelscapableofreal-timeanalysisandhighpredictionaccuracy.TheInternetofThings(IoT)providesanovelmethodfordetectingearthquakes using a variety of sensors to collect vital seismic data,such as latitude, longitude,depth,magnitude,and time.IoT controllers and centralized systems process and analyze this data to enable efficient monitoring and forecasting.Furthermore,withthehelpofamachinelearningmodel named Bidirectional Gated Recurrent Unit (Bi-GRU), which integrates sophisticated data fusion and advanced machine learning techniques.Our proposed study model, SmartGRU, demonstrates how to improve earthquake prediction systems by combining IoT sensors with a Bi-GRU machine learning model that incorporates an emerging approach.