TY - JOUR
T1 - Internet of things (IoT) driven structural health monitoring for enhanced seismic resilience
T2 - A rigorous functional analysis and implementation framework
AU - Alsehaimi, Abdullah
AU - Houda, Moustafa
AU - Waqar, Ahsan
AU - Hayat, Saleh
AU - Ahmed Waris, Faizan
AU - Benjeddou, Omrane
N1 - Publisher Copyright:
© 2024 The Authors
PY - 2024/6
Y1 - 2024/6
N2 - Civil engineering infrastructures are increasingly becoming exposed to seismic loads, and at such a stage there is an increased need for alternative methods to fortify and enhance the resilience. The present study deals with the intricate linkage of internet of things (IoT) devices and the resilience of structures in a seismically affected zone. From the literature, the role of adaptive structural control, data acquisition and transmission, early warning systems, integration with building standards and codes, and real-time analytics and monitoring have been found to be the topmost aspects of ensuring resilience to seismic events. The seismically affected area of concern provides an in-depth analysis of the practical applications of the IoT in buildings in a seismic area. A survey was distributed to 239 respondents, and a very solid 58.99 % response rate proved the interest and participation of the respondents in the study. Using Partial Least Squares Structural Equation Modelling (PLS-SEM), the researchers frame a measurement model which is applied to analyze the reliability and validity of the IoT constructs. Further, the bootstrap resampling mechanisms are adopted to test the five hypotheses rigorously. The findings establish robust connections between adaptive structural control, data acquisition, early warning systems, integration with building codes and standards, real-time monitoring and analytics, and IoT, contributing to enhanced seismic resilience. Infrastructure developers can draw management implications from these findings, while empirical researchers can utilize the verified framework to guide future studies.
AB - Civil engineering infrastructures are increasingly becoming exposed to seismic loads, and at such a stage there is an increased need for alternative methods to fortify and enhance the resilience. The present study deals with the intricate linkage of internet of things (IoT) devices and the resilience of structures in a seismically affected zone. From the literature, the role of adaptive structural control, data acquisition and transmission, early warning systems, integration with building standards and codes, and real-time analytics and monitoring have been found to be the topmost aspects of ensuring resilience to seismic events. The seismically affected area of concern provides an in-depth analysis of the practical applications of the IoT in buildings in a seismic area. A survey was distributed to 239 respondents, and a very solid 58.99 % response rate proved the interest and participation of the respondents in the study. Using Partial Least Squares Structural Equation Modelling (PLS-SEM), the researchers frame a measurement model which is applied to analyze the reliability and validity of the IoT constructs. Further, the bootstrap resampling mechanisms are adopted to test the five hypotheses rigorously. The findings establish robust connections between adaptive structural control, data acquisition, early warning systems, integration with building codes and standards, real-time monitoring and analytics, and IoT, contributing to enhanced seismic resilience. Infrastructure developers can draw management implications from these findings, while empirical researchers can utilize the verified framework to guide future studies.
KW - Adaptive structural control
KW - Building standards
KW - Data transmission
KW - Early warning systems
KW - Real-time analytics
KW - Seismic resilience
UR - http://www.scopus.com/inward/record.url?scp=85194704270&partnerID=8YFLogxK
U2 - 10.1016/j.rineng.2024.102340
DO - 10.1016/j.rineng.2024.102340
M3 - Article
AN - SCOPUS:85194704270
SN - 2590-1230
VL - 22
JO - Results in Engineering
JF - Results in Engineering
M1 - 102340
ER -