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المؤلفTariq H.
المؤلفTouati F.
المؤلفAl-Hitmi M.A.E.
المؤلفCrescini D.
المؤلفMnaouer A.B.
تاريخ الإتاحة2020-04-23T14:21:34Z
تاريخ النشر2019
اسم المنشورApplied Sciences (Switzerland)
الرقم المعياري الدولي للكتاب20763417
معرّف المصادر الموحدhttp://dx.doi.org/10.3390/app9183650
معرّف المصادر الموحدhttp://hdl.handle.net/10576/14360
الملخصEarthquakes are one of the major natural calamities as well as a prime subject of interest for seismologists, state agencies, and ground motion instrumentation scientists. The real-time data analysis of multi-sensor instrumentation is a valuable knowledge repository for real-time early warning and trustworthy seismic events detection. In this work, an early warning in the first 1 micro-second and seismic wave detection in the first 1.7 milliseconds after event initialization is proposed using a seismic wave event detection algorithm (SWEDA). The SWEDA with nine low-computation-cost operations is being proposed for smart geospatial bi-axial inclinometer nodes (SGBINs) also utilized in structural health monitoring systems. SWEDA detects four types of seismic waves, i.e., primary (P) or compression, secondary (S) or shear, Love (L), and Rayleigh (R) waves using time and frequency domain parameters mapped on a 2D mapping interpretation scheme. The SWEDA proved automated heterogeneous surface adaptability, multi-clustered sensing, ubiquitous monitoring with dynamic Savitzky-Golay filtering and detection using nine optimized sequential and structured event characterization techniques. Furthermore, situation-conscious (context-aware) and automated computation of short-time average over long-time average (STA/LTA) triggering parameters by peak-detection and run-time scaling arrays with manual computation support were achieved. - 2019 by the authors.
راعي المشروعFunding: This publication was made possible by the NPRP grant # 8-1781-2-725 from the Qatar National Research Fund (a member of Qatar Foundation). The statements made herein are solely the responsibility of the authors.
اللغةen
الناشرMDPI AG
الموضوعApplied methods
الموضوعEarly warning
الموضوعEarthquake
الموضوعInclinometers
الموضوعInternet of Things (IoT)
الموضوعReal-time detection
الموضوعSeismic waves
العنوانA real-time early warning seismic event detection algorithm using smart geo-spatial bi-axial inclinometer nodes for Industry 4.0 applications
النوعArticle
رقم العدد18
رقم المجلد9


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