Detection of Seismic Precursors with a Low-Cost Embedded System: Methodology and Results of a Geo-Electromagnetic Monitoring Study

Authors

Keywords:

seismic precursors, digital filters, signal analysis

Abstract

This study presents the development and validation of a low-cost embedded system for the detection of potential seismic precursors through monitoring the Earth's geomagnetic field. The system, based on a fluxgate magnetometer and a Raspberry Pi acquisition platform, allows the acquisition of raw data (RAW) with a sampling rate of 1 Hz. Relevant seismic events that occurred between 2017 and 2019 in Mexico were analyzed, applying digital processing techniques such as the moving average filter and the discrete wavelet transform (DWT). The results obtained were compared with records from the Tucson geomagnetic station (INTERMAGNET), showing similar anomalous patterns prior to seismic events, suggesting the viability of the proposed system to identify potential seismic precursors. It is concluded that this type of system can contribute to more accessible and scalable monitoring networks for seismic risk mitigation.

Downloads

Download data is not yet available.

Author Biography

  • M.C. Jaime Becerra, Universidad Autónoma de Sinaloa

    Jaime Andrés Becerra Jiménez es un Ingeniero Mecatrónico con más de 8 años de experiencia en el desarrollo de soluciones tecnológicas avanzadas, especializándose en inteligencia artificial, redes neuronales y sistemas embebidos. Posee una Maestría en Ciencias de la Información de la Universidad Autónoma de Sinaloa (2017-2019) y obtuvo su título de Ingeniería Mecatrónica en el Instituto Tecnológico de Culiacán (2010-2014).  

       

    Su experiencia incluye el trabajo con diversos lenguajes de programación como Python, C, C++ y Rust, destacando en programación concurrente, paralela y optimización de procesos. Tiene conocimiento avanzado en el diseño e implementación de algoritmos de aprendizaje supervisado y no supervisado, así como en el manejo de tecnologías como ROS/ROS2, bases de datos (SQL y NoSQL), Docker, Kubernetes y plataformas en la nube como AWS y Azure.  

                 

    Ha desarrollado sistemas embebidos utilizando plataformas como Arduino, PIC y placas SBC (Raspberry Pi, BeagleBone), e implementado soluciones de IA embebida. Su experiencia laboral incluye roles como Desarrollador de Sistemas Embebidos en Palo Verde R&D, donde trabajó en backends con Rust y Python para predicción de fallas y desarrollo de robots autónomos, e implementó sistemas con TensorFlow y NVIDIA Jetson para clasificación de imágenes industriales. También ha sido profesor universitario en la Universidad Autónoma de Occidente y la Universidad Autónoma de Sinaloa, impartiendo clases de electrónica, robótica, microcontroladores y programación. Además, ha trabajado como desarrollador independiente, creando sistemas personalizados y colaborando en proyectos de automatización industrial.

References

S. Harrigan et al., “Detection of Electromagnetic Seismic Precursors from Swarm Data by Enhanced Martingale Analytics,” Sensors, vol. 24, no. 11, Jun. 2024, doi: 10.3390/s24113654.

Y. Huang, P. Zhu, and S. Li, “Feasibility Study on Earthquake Prediction Based on Impending Geomagnetic Anomalies,” Applied Sciences (Switzerland), vol. 14, no. 1, Jan. 2024, doi: 10.3390/app14010263.

E. H. Vestine, “Winds in the upper atmosphere deduced from the dynamo theory of geomagnetic disturbance,” Journal of Geophysical Research (1896-1977), vol. 59, no. 1, pp. 93–128, 1954, doi: https://doi.org/10.1029/JZ059i001p00093.

D. Gordon and R. Brown, “Recent advances in fluxgate magnetometry,” IEEE Trans Magn, vol. 8, no. 1, pp. 76–82, 1972, doi: 10.1109/TMAG.1972.1067268.

A. Grinsted, J. Moore, and S. Jevrejeva, “Application of Cross Wavelet Transform and Wavelet Coherence to Geophysical Time Series,” Nonlinear Process Geophys, vol. 11, Apr. 2004, doi: 10.5194/npg-11-561-2004.

A. Baschirotto, E. Dallago, M. Ferri, P. Malcovati, A. Rossini, and G. Venchi, “A 2D micro-fluxgate earth magnetic field measurement systems with fully automated acquisition setup,” Measurement, vol. 43, no. 1, pp. 46–53, 2010, doi: https://doi.org/10.1016/j.measurement.2009.06.007.

J. P. Amezquita Sanchez, O. Chavez Alegria, M. Valtierra Rodriguez, J. A. L. Cruz Abeyro, J. R. Millan Almaraz, and A. Dominguez Gonzalez, “Detection of ULF Geomagnetic Anomalies Associated to Seismic Activity Using EMD Method and Fractal Dimension Theory,” IEEE Latin America Transactions, vol. 15, no. 2, pp. 197–205, Feb. 2017, doi: 10.1109/TLA.2017.7854612.

O. Chavez, J. R. Millan-Almaraz, J. Rodríguez-Reséndiz, J. P. Amezquita-Sanchez, M. Valtierra-Rodriguez, and J. A. L. Cruz-Abeyro, “DWT-based methodology for detection of seismic precursors on electric field signals in Mexico,” Geomatics, Natural Hazards and Risk, vol. 9, no. 1, pp. 281–294, 2018, doi: 10.1080/19475705.2018.1428229.

M. Tsutsui, “Behaviors of Electromagnetic Waves Directly Excited by Earthquakes,” Geoscience and Remote Sensing Letters, IEEE, vol. 11, pp. 1961–1965, Apr. 2014, doi: 10.1109/LGRS.2014.2315208.

F. Dudkin, V. Korepanov, D. Dudkin, V. Pilipenko, V. Pronenko, and S. Klimov, “Electric field of the power terrestrial sources observed by microsatellite Chibis-M in the Earth’s ionosphere in frequency range 1–60 Hz,” Geophys Res Lett, vol. 42, pp. 5686–5693, Apr. 2015, doi: 10.1002/2015GL064595.

A. Vajuravel, E. Khoshaba, F. Andrade, T. Garcia, and P. J. Chi, “A Low-cost SMART System for Real-Time Geomagnetic Field Monitoring,” in AGU Fall Meeting Abstracts, Dec. 2023, pp. GP01-04.

H. Kim et al., “Citizen science: Development of a low-cost magnetometer system for a coordinated space weather monitoring,” HardwareX, vol. 20, Dec. 2024, doi: 10.1016/j.ohx.2024.e00580.

B. M. De Groot and L. V. De Groot, “A low-cost device for measuring local magnetic anomalies in volcanic terrain,” Geoscientific Instrumentation, Methods and Data Systems, vol. 8, no. 2, pp. 217–225, Aug. 2019, doi: 10.5194/gi-8-217-2019.

Downloads

Published

2025-05-30

How to Cite

Detection of Seismic Precursors with a Low-Cost Embedded System: Methodology and Results of a Geo-Electromagnetic Monitoring Study. (2025). International Journal of Information Science and Technological Applications-UAS IJISTA, 1(1), 21-31. https://revistas.uas.edu.mx/index.php/IJISTA/article/view/1095