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The intense development of novel data-driven and hybrid methods for structural health monitoring (SHM) has been demonstrated by field deployments on large-scale systems, including transport, wind energy, and building infrastructure. The actionability of SHM as an essential resource for life-cycle and resilience management is heavily dependent on the advent of low-cost and easily deployable sensors Nonetheless, in optimizing these deployments, a number of open issues remain with respect to the sensing side. These are associated with the type, configuration, and eventual processing of the information acquired from these sensors to deliver continuous behavioral signatures of the monitored structures. This book discusses the latest advances in the field of sensor networks for SHM. The focus lies both in active research on the theoretical foundations of optimally deploying and operating sensor networks and in those technological developments that might designate the next generation of sensing solutions targeted for SHM. The included contributions span the complete SHM information chain, from sensor design to configuration, data interpretation, and triggering of reactive action. The featured papers published in this Special Issue offer an overview of the state of the art and further proceed to introduce novel methods and tools. Particular attention is given to the treatment of uncertainty, which inherently describes the sensed information and the behavior of monitored systems.

Technology: general issues --- probabilistic data-interpretation --- Bayesian model updating --- error-domain model falsification --- iterative asset-management --- practical applicability --- computation time --- swarm-based parallel control (SPC) --- Internet of Things (IoT) --- soil–structure interaction (SSI) --- semi-active control --- adjacent buildings --- Bayesian inference --- model updating --- modal identification --- structural dynamics --- bridges --- sensor placement optimisation --- structural health monitoring --- damage identification --- mutual information --- evolutionary optimisation --- inertial sensor fusion --- instrumented particle --- MEMS --- sediment entrainment --- sensor calibration --- frequency of entrainment --- varying environmental and operational conditions --- damage detection and localization --- Gaussian process regression --- autoregressive with exogenous inputs --- distributed sensor network --- mode shape curvatures --- n/a --- soil-structure interaction (SSI)

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The intense development of novel data-driven and hybrid methods for structural health monitoring (SHM) has been demonstrated by field deployments on large-scale systems, including transport, wind energy, and building infrastructure. The actionability of SHM as an essential resource for life-cycle and resilience management is heavily dependent on the advent of low-cost and easily deployable sensors Nonetheless, in optimizing these deployments, a number of open issues remain with respect to the sensing side. These are associated with the type, configuration, and eventual processing of the information acquired from these sensors to deliver continuous behavioral signatures of the monitored structures. This book discusses the latest advances in the field of sensor networks for SHM. The focus lies both in active research on the theoretical foundations of optimally deploying and operating sensor networks and in those technological developments that might designate the next generation of sensing solutions targeted for SHM. The included contributions span the complete SHM information chain, from sensor design to configuration, data interpretation, and triggering of reactive action. The featured papers published in this Special Issue offer an overview of the state of the art and further proceed to introduce novel methods and tools. Particular attention is given to the treatment of uncertainty, which inherently describes the sensed information and the behavior of monitored systems.

probabilistic data-interpretation --- Bayesian model updating --- error-domain model falsification --- iterative asset-management --- practical applicability --- computation time --- swarm-based parallel control (SPC) --- Internet of Things (IoT) --- soil–structure interaction (SSI) --- semi-active control --- adjacent buildings --- Bayesian inference --- model updating --- modal identification --- structural dynamics --- bridges --- sensor placement optimisation --- structural health monitoring --- damage identification --- mutual information --- evolutionary optimisation --- inertial sensor fusion --- instrumented particle --- MEMS --- sediment entrainment --- sensor calibration --- frequency of entrainment --- varying environmental and operational conditions --- damage detection and localization --- Gaussian process regression --- autoregressive with exogenous inputs --- distributed sensor network --- mode shape curvatures --- n/a --- soil-structure interaction (SSI)

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In the past, when elements in sructures were composed of perishable materials, such as wood, the maintenance of houses, bridges, etc., was considered of vital importance for their safe use and to preserve their efficiency. With the advent of materials such as reinforced concrete and steel, given their relatively long useful life, periodic and constant maintenance has often been considered a secondary concern. When it was realized that even for structures fabricated with these materials that the useful life has an end and that it was being approached, planning maintenance became an important and non-negligible aspect. Thus, the concept of structural health monitoring (SHM) was introduced, designed, and implemented as a multidisciplinary method. Computational mechanics, static and dynamic analysis of structures, electronics, sensors, and, recently, the Internet of Things (IoT) and artificial intelligence (AI) are required, but it is also important to consider new materials, especially those with intrinsic self-diagnosis characteristics, and to use measurement and survey methods typical of modern geomatics, such as satellite surveys and highly sophisticated laser tools.

structural health monitoring --- jointless bridge --- high-speed railway --- bearing --- expansion device --- displacement analysis --- structural reliability estimation --- modal identification --- finite element model updating --- cyber-physical systems --- crowdsourcing --- temperature effects --- time-lag effect --- Fourier series expansion --- box-girder bridges --- structural engineering --- overall deformation monitoring --- perspective transformation --- edge detection --- close-range photogrammetry --- railway embankment --- condition assessment --- ground penetrating radar --- multi-attribute utility theory --- laser scanner --- line scanner --- structure monitoring --- deformation --- dynamic measurements --- scan-to-BIM --- point cloud --- HBIM --- FEM --- Rhinoceros --- terrestrial laser scanner (TLS) --- ground-based real aperture radar (GB-RAR) --- vibration frequency --- spectral analysis --- displacement --- structural health monitoring (SHM) --- vibration-based damage detection --- system identification --- subspace system identification (SSI) --- tie rod --- natural frequencies --- mode shapes --- root-mean-square error (RMSE) --- environmental monitoring --- long-range mapping --- MMS --- sub-millimetric EDM geodetic techniques --- damage detection --- damage localization --- hybrid approach --- neural network --- timber bridges --- stress-laminated timber decks --- monitoring --- humidity-temperature sensors --- wood moisture content --- multi-phase models --- finite element method --- moving load identification --- strain influence line --- load transverse distribution --- strain integral coefficient --- identification error --- n/a