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Cyber-physical systems for structural health monitoring: sensing technologies and intelligent computing

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Abstract

A new generation of systems appeared with the birth of Cyber-Physical Systems (CPS) that integrated computational and physical capabilities. CPS represents an emerging domain as it has an important interest in the literature due to its interaction with Structural Health Monitoring System applications. In this paper, we present a deep investigation of SHM and wireless sensing technologies towards an efficient CPS. Structural Health Monitoring (SHM) based on wireless sensor networks (WSNs) has the potency to reduce the cost of installation and maintenance of public and private infrastructure. Many types of research are interested in SHM using WSN due to its application domain diversity and its importance in public safety. WSN networks can be a prominent candidate to solve many SHM problems thanks to its implementation simplicity and its significant cost reductions. We present a comprehensive survey about SHM based on new technologies and methods including the internet of things (IoT), Software-defined Networking (SDN), fog and cloud computing. SHM application domains are also highlighted with analytic research domains, projects, testbeds, and experimental works. Besides that, this investigation pinpoints SHM functionalities (damage detection, prognostic and risk assessment) and Artificial Intelligence (AI) contributions for SHM such as sensor placement and clustering and its benefits on energy optimization. The main challenges of WSN design, energy consumption, damage prediction, SHM mobility, SHM large scale were presented and discussed.

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Abbreviations

ABC:

Artificial Bee Colony

ACO:

Ant Colony Optimization

ABC:

Artificial Bee Colony

ACO:

Ant Colony Optimization

AI:

Artificial Intelligence

BECAS:

Bridge Engineering Condition Assessment System

BS:

Base Station

CDOM:

Colored Dissolved organic matter

CI:

Critical Infrastructure

CPS:

Cyber-Physical Systems

DT:

Damage Detection

DE:

Differential Evolution

EB:

Employed Bee

EC:

Evolutionary Computation

FBG:

Fiber Bragg Grating

FBP-WSNs:

Fully Battery Powered WSNs

FEH-WSNs:

Full Harvesting WSNs

FFSS:

Fission Fusion Social Structure

FRP:

Fiber Reinforced Polymer

GA:

Genetic Algorithm

GAF:

Geographic Adaptive Fidelity

GBDD:

Grid-Based Data Dissemination

GL:

Global Leader

IGA:

Improved Genetic Algorithm

IoT:

Internet of Things

IRF:

Impulse Response Function

ITD:

Ibrahim Time Domain

LEACH:

Low Energy Adaptive Clustering Hierarchy

LL:

Local Leader

LOA:

Lion Optimization Algorithm

LT:

Life Time

MEMS:

Microelectromechanical Systems

MPS:

Mobile Phone Sensing

NDE:

Non-destructive Evolution Monitoring

NL:

Network Life Time

OB:

Onlooker Bee

OF:

Open Flow

PEGASIS:

Power Efficient Gathering in Sensor Information System

PEH-WSNs:

Partial Energy Harvesting WSNs

PSO:

Particle Swarm Optimization

PSOGA:

Particle Swarm Optimization with Genetic Algorithm

PZT:

Lead Zirconate Titanate

RA:

Risk Assessment

SB:

Scout Bee

SCDOT:

South Carolina Department of Transportation

SDN:

Software Defined Network

SHM:

Structural Health Monitoring

SM:

Spider Monkey

SMO:

Spider Monkey Optimization

SMS:

Structural Monitoring System

SPIN:

Sensor Protocol Information Negotiation

SSA:

Squirrel Search Algorithm

WSN:

Wireless Sensor Network

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  1. Digital Research Center of SFAX (CRNS), Laboratory of Signals, systeMs, aRtificial Intelligence and neTworkS (SM@RTS), University of Sfax, Sfax, Tunisia

    Wael Doghri, Ahlem Saddoud & Lamia Chaari Fourati

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  1. Wael Doghri
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Doghri, W., Saddoud, A. & Chaari Fourati, L. Cyber-physical systems for structural health monitoring: sensing technologies and intelligent computing. J Supercomput 78, 766–809 (2022). https://doi.org/10.1007/s11227-021-03875-5

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