A Real-Time Early Warning Seismic Event Detection Algorithm Using Smart Geo-Spatial Bi-Axial Inclinometer Nodes for Industry 4.0 Applications

Abstract

Earthquakes 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.

Recent Advances in Internet of Things Solutions for Early Warning Systems: A Review

“…Ali et al [ 53 ] proposed a cloud based wireless sensor and actuators network to alert from floods. The proposed system is to be deployed not only to monitor water levels so that warnings can be issued, but it also includes actuators that open watchman inlets to make water flow out if needed.…”

“…Tariq et al [ 53 ] proposed and tested a Seismic Wave Event Detection Algorithm (SWEDA) to achieve milliseconds earthquake detection and warning. It uses inclinometer nodes for Industry 4.0 and the CANOpen communication protocol for industrial IoT.…”

Real-time Gradient-Aware Indigenous AQI Estimation IoT Platform

“…Furthermore, the improvement potential in context-aware data processing model and thresholding for detection was discussed by Hasan et al in [22,23] for multi-sensor single-board node. The energy efficiency schemes were one major gap highlighted by [24].…”

“…The works Lebilium Waspmote [21] was Zigbee but needed GSM/GPRS support for outdoor sensing and have been more contributory if equipped with geo-spatial traces or cadastral layouts support for all the measured variables like AirBox [22]. An infrastructure embedded system was needed to accommodate the maximum sensing, minimum data processing, AQI estimation, and long-haul deployability [19][20][21][22][23].…”

A Temperature Independent Inclinometer Based on a Tapered Fiber Bragg Grating in a Fiber Ring Laser

“…Therefore, it is necessary to study inclinometers using different technologies to overcome these limitations. Besides, in other applications, for example, virtual reality technology, gesture recognition [ 7 ], intelligent machinery [ 8 ] and environment monitoring [ 9 ] a kind of inclinometer which is cost-effective, extremely accurate, and simple in structure is needed. Over the past few years, fiber-optic inclinometers have been widely investigated because of their inherent advantages, including long-term stability and reusability [ 10 , 11 , 12 , 13 ].…”