Affordable Instrument Design for Seismic Monitoring, Early Warning Systems and Control Actions to Risk Mitigation

Garcia, Arturo; Aguilar, Antonio Noe Perez

doi:10.1109/controlo.2018.8516414

Cited by 1 publication

(1 citation statement)

References 1 publication

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“…On the other hand, the most common microcontrollers use Raspberry Pi, as in [ 56 ]. Other studies, such as the one presented in [ 57 ], use Arduino, whereas the authors in [ 58 ] use an FPGA. Once again, the characteristic to be noted in the microcontroller selection is the low cost and efficiency, along with the ability to already have or be able to integrate wireless communication modules and analog–digital converters easily.…”

Section: Structural Health Monitoring Systemsmentioning

confidence: 99%

A Systematic Review of Structural Health Monitoring Systems to Strengthen Post-Earthquake Assessment Procedures

López-Castro

Haro

Arcos-Avilés

et al. 2022

Sensors

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Structural health monitoring (SHM) is vital to ensuring the integrity of people and structures during earthquakes, especially considering the catastrophic consequences that could be registered in countries within the Pacific ring of fire, such as Ecuador. This work reviews the technologies, architectures, data processing techniques, damage identification techniques, and challenges in state-of-the-art results with SHM system applications. These studies use several data processing techniques such as the wavelet transform, the fast Fourier transform, the Kalman filter, and different technologies such as the Internet of Things (IoT) and machine learning. The results of this review highlight the effectiveness of systems aiming to be cost-effective and wireless, where sensors based on microelectromechanical systems (MEMS) are standard. However, despite the advancement of technology, these face challenges such as optimization of energy resources, computational resources, and complying with the characteristic of real-time processing.

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Section: Structural Health Monitoring Systemsmentioning

confidence: 99%