Earthquake Prediction and Alert System Using IoT Infrastructure and Cloud-Based Environmental Data Analysis
Earthquakes are one of the most life-threatening natural phenomena, and their prediction is of constant concern among scientists. The study proposes that abrupt weather parameter value fluctuations may influence the occurrence of shallow seismic events by focusing on developing an innovative concept...
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MDPI AG
2024-11-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/14/22/10169 |
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| author | Cosmina-Mihaela Rosca Adrian Stancu |
| author_facet | Cosmina-Mihaela Rosca Adrian Stancu |
| author_sort | Cosmina-Mihaela Rosca |
| collection | DOAJ |
| description | Earthquakes are one of the most life-threatening natural phenomena, and their prediction is of constant concern among scientists. The study proposes that abrupt weather parameter value fluctuations may influence the occurrence of shallow seismic events by focusing on developing an innovative concept that combines historical meteorological and seismic data collection to predict potential earthquakes. A machine learning (ML) model utilizing the ML.NET framework was designed and implemented. An analysis was undertaken to identify which modeling approach, value prediction, or data classification performs better in forecasting seismic events. The model was trained on a dataset of 8766 records corresponding to the period from 1 January 2001 to 5 October 2024. The achieved accuracy of the model was 95.65% for earthquake prediction based on weather conditions in the Vrancea region, Romania. The authors proposed a unique alerting algorithm and conducted a case study that evaluates multiple predictive models, varying parameters, and methods to identify the most effective model for seismic event prediction in specific meteorological conditions. The findings demonstrate the potential of combining Internet of Things (IoT)-based environmental monitoring with AI to improve earthquake prediction accuracy and preparedness. An IoT-based application was developed using C# with ASP.NET framework to enhance earthquake prediction and public warning capabilities, leveraging Azure cloud infrastructure. The authors also created a hardware prototype for real-time earthquake alerting, integrating the M5Stack platform with ESP32 and MPU-6050 sensors for validation. The testing phase and results describe the proposed methodology and various scenarios. |
| format | Article |
| id | doaj-art-a0a10fcf43a946769c0af08e149bf16f |
| institution | OA Journals |
| issn | 2076-3417 |
| language | English |
| publishDate | 2024-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj-art-a0a10fcf43a946769c0af08e149bf16f2025-08-20T02:08:12ZengMDPI AGApplied Sciences2076-34172024-11-0114221016910.3390/app142210169Earthquake Prediction and Alert System Using IoT Infrastructure and Cloud-Based Environmental Data AnalysisCosmina-Mihaela Rosca0Adrian Stancu1Department of Automatic Control, Computers, and Electronics, Faculty of Mechanical and Electrical Engineering, Petroleum-Gas University of Ploiesti, 39 Bucharest Avenue, 100680 Ploiesti, RomaniaDepartment of Business Administration, Faculty of Economic Sciences, Petroleum-Gas University of Ploiesti, 39 Bucharest Avenue, 100680 Ploiesti, RomaniaEarthquakes are one of the most life-threatening natural phenomena, and their prediction is of constant concern among scientists. The study proposes that abrupt weather parameter value fluctuations may influence the occurrence of shallow seismic events by focusing on developing an innovative concept that combines historical meteorological and seismic data collection to predict potential earthquakes. A machine learning (ML) model utilizing the ML.NET framework was designed and implemented. An analysis was undertaken to identify which modeling approach, value prediction, or data classification performs better in forecasting seismic events. The model was trained on a dataset of 8766 records corresponding to the period from 1 January 2001 to 5 October 2024. The achieved accuracy of the model was 95.65% for earthquake prediction based on weather conditions in the Vrancea region, Romania. The authors proposed a unique alerting algorithm and conducted a case study that evaluates multiple predictive models, varying parameters, and methods to identify the most effective model for seismic event prediction in specific meteorological conditions. The findings demonstrate the potential of combining Internet of Things (IoT)-based environmental monitoring with AI to improve earthquake prediction accuracy and preparedness. An IoT-based application was developed using C# with ASP.NET framework to enhance earthquake prediction and public warning capabilities, leveraging Azure cloud infrastructure. The authors also created a hardware prototype for real-time earthquake alerting, integrating the M5Stack platform with ESP32 and MPU-6050 sensors for validation. The testing phase and results describe the proposed methodology and various scenarios.https://www.mdpi.com/2076-3417/14/22/10169earthquake detectionearthquake predictionprocessing of seismic dataAI methodsmachine learningIoT infrastructure |
| spellingShingle | Cosmina-Mihaela Rosca Adrian Stancu Earthquake Prediction and Alert System Using IoT Infrastructure and Cloud-Based Environmental Data Analysis Applied Sciences earthquake detection earthquake prediction processing of seismic data AI methods machine learning IoT infrastructure |
| title | Earthquake Prediction and Alert System Using IoT Infrastructure and Cloud-Based Environmental Data Analysis |
| title_full | Earthquake Prediction and Alert System Using IoT Infrastructure and Cloud-Based Environmental Data Analysis |
| title_fullStr | Earthquake Prediction and Alert System Using IoT Infrastructure and Cloud-Based Environmental Data Analysis |
| title_full_unstemmed | Earthquake Prediction and Alert System Using IoT Infrastructure and Cloud-Based Environmental Data Analysis |
| title_short | Earthquake Prediction and Alert System Using IoT Infrastructure and Cloud-Based Environmental Data Analysis |
| title_sort | earthquake prediction and alert system using iot infrastructure and cloud based environmental data analysis |
| topic | earthquake detection earthquake prediction processing of seismic data AI methods machine learning IoT infrastructure |
| url | https://www.mdpi.com/2076-3417/14/22/10169 |
| work_keys_str_mv | AT cosminamihaelarosca earthquakepredictionandalertsystemusingiotinfrastructureandcloudbasedenvironmentaldataanalysis AT adrianstancu earthquakepredictionandalertsystemusingiotinfrastructureandcloudbasedenvironmentaldataanalysis |