Proposal for a System Model for Offline Seismic Event Detection in Colombia

Julián Miranda, Angélica Flórez, Gustavo Ospina, Ciro Gamboa, Carlos Flórez and Miguel Altuve
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Julián Miranda: Faculty of Systems and Informatics Engineering, Pontifical Bolivarian University, Bucaramanga 680006, Colombia
Angélica Flórez: Faculty of Systems and Informatics Engineering, Pontifical Bolivarian University, Bucaramanga 680006, Colombia
Gustavo Ospina: Faculty of Civil Engineering, Pontifical Bolivarian University, Bucaramanga 680006, Colombia
Ciro Gamboa: Faculty of Electrical and Electronic Engineering, Pontifical Bolivarian University, Bucaramanga 680006, Colombia
Carlos Flórez: Faculty of Civil Engineering, Francisco de Paula Santander University, Cúcuta 540003, Colombia
Miguel Altuve: Faculty of Electrical and Electronic Engineering, Pontifical Bolivarian University, Bucaramanga 680006, Colombia

Future Internet, 2020, vol. 12, issue 12, 1-17

Abstract: This paper presents an integrated model for seismic events detection in Colombia using machine learning techniques. Machine learning is used to identify P-wave windows in historic records and hence detect seismic events. The proposed model has five modules that group the basic detection system procedures: the seeking, gathering, and storage seismic data module, the reading of seismic records module, the analysis of seismological stations module, the sample selection module, and the classification process module. An explanation of each module is given in conjunction with practical recommendations for its implementation. The resulting model allows understanding the integration of the phases required for the design and development of an offline seismic event detection system.

Keywords: seismic event detection; detection model; seismology; classification (search for similar items in EconPapers)
JEL-codes: O3 (search for similar items in EconPapers)
Date: 2020
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