###### Abstract
The reliability equations in [25] were a noticeable contribution for ISCS and should be evaluated by R composed of (1) intrinsic capability (IC), (2) application parameters (AP), and (3) human factor (HF) governed by probability of false alarm (POFA), and (4) probability of detection (POD). Further study of SHM variables [26] led to the fact that vibration and acoustic factors by are most vital and instantaneous that can demolish grids of structures in the nick of time, all the rest are transients, i.e., only contribute to aging and decay. The review of eight [27] methods--(1) vibration-based damage identification (VBDI) methods; (2) natural frequency-based methods (NFM), (3) mode shape-based methods (MSM), (4) mode shape curvature/strain mode shape-based methods (MSCS), (5) dynamically measured flexibility-based methods (DMFM), (6) matrix update based methods (MUM), (7) non-linear methods (NLM), and (8) artificial neural network methods (ANNM)--applied to ISCS can be very useful in interpreting the global displacement response of regional and urban structures to identify local changes in it. A common gap observed in [24; 25; 26; 27] was an adaptive event capturing pre-triggering and post-triggering that guided the entire data manipulation leading to immeasurable real-time delays and computational costs. On the other hand, the real-time event capturing holds a momentous significance in the credibility of any real-world event detection application. The standard short-time average and long-time average (STA/LTA) triggering algorithm [28] has been the one most applied and used by state agencies [29] in the USA and EU. STA/LTA is a very resource-efficient algorithm. The adaptive STA/LTA used by the waveform correlation event detection [30] system and the Hoadley gas field, Alberta, Canada [31], was the nearest contestant with much more resource requirement. The S/L-Kurt method [32] was more effective than the standard (STA/LTA) mechanism for arrivals because it reduces any bias in the short-term kurtosis (STK) and long-term kurtosis (LTK) window limited to desktop machines in Industry 4.0 applications. The S/L-Kurt-assisted real-time seismic evaluation [33] and interpretation [34] is considered as, so far, the most critical of all the displacement-based SHM procedures using time series analysis. The nature of displacement data is that it consists of time series and is further modularized into a pattern of windows by application of the Dempster-Shafer theory of evidence [35], handled through the matrix and statistical techniques. The demonstration and significance [36] of window sizes for STA and MER; STK for MCM and LTA; and LTK and PAI-K for field microseismic data sets streamlined by IKK's method, ZTR's method, JER-AIC, [PERSON]'s method, and S/L-Kurt [37] were found to be more precise for constraint cases with a gap in the networked sensor detection mechanisms. However, the contribution [38] was based on a machine with i7-4720 HQ CPU having clock 2.60 GHz and 16 GB RAM size that limited its canvas in ubiquitous Industry 4.0 applications due to complex and high computation costs as well as automated ADC calibration. The geo-seismic sensing capabilities for [1; 2; 3; 4; 5; 6; 7; 8; 9; 10; 11; 12; 13] and real-time limitations in [13; 14; 15; 16; 17; 18; 19; 20; 21; 22; 23] methods had sequenced output gaps based on [1; 2; 3] enormities. The clustered and networked ISCS assessments raised new complexities in assessments only possible for geographical area network solutions at the cloud level [9]. The application constraint methodological sequence [17; 18; 19; 20; 21; 22; 23; 24; 25; 26; 27; 28; 29; 30; 31; 32; 33; 34; 35; 36; 37; 38] was very important in seismic event characterization as an earthquake after following and considering all the above discussed methodologiesand procedures.