Earthquake Prediction and Alert System Using IoT Infrastructure and Cloud-Based Environmental Data Analysis

Applied Sciences, Journal Year: 2024, Volume and Issue: 14(22), P. 10169 - 10169

Published: Nov. 6, 2024

Earthquakes are one of the most life-threatening natural phenomena, and their prediction is constant concern among scientists. The study proposes that abrupt weather parameter value fluctuations may influence occurrence shallow seismic events by focusing on developing an innovative concept combines historical meteorological data collection to predict potential earthquakes. A machine learning (ML) model utilizing ML.NET framework was designed implemented. An analysis undertaken identify which modeling approach, prediction, or classification performs better in forecasting events. trained a dataset 8766 records corresponding period from 1 January 2001 5 October 2024. achieved accuracy 95.65% for earthquake based conditions Vrancea region, Romania. authors proposed unique alerting algorithm conducted case evaluates multiple predictive models, varying parameters, methods effective event specific conditions. findings demonstrate combining Internet Things (IoT)-based environmental monitoring with AI improve preparedness. IoT-based application developed using C# ASP.NET enhance public warning capabilities, leveraging Azure cloud infrastructure. also created hardware prototype real-time alerting, integrating M5Stack platform ESP32 MPU-6050 sensors validation. testing phase results describe methodology various scenarios.

Language: Английский

Detecting the Bull’s-Eye Effect in Seismic Inversion Low-Frequency Models Using the Optimized YOLOv7 Model

Applied Geophysics, Journal Year: 2024, Volume and Issue: unknown

Published: June 27, 2024

Language: Английский