To date, data mining (DM) techniques, ie artificial intelligence, machine learning, and
statistical methods have been utilized in a remarkable number of structural health monitoring …

In the age of the smart city, things like the Internet of Things (IoT) and big data analytics are
making big changes to the way traditional structural health monitoring (SHM) is done. Also …

The challenges of urban administration are growing, as the population, automobiles, and
cities rise. Making cities smarter is thus one of the most effective solutions to urban issues. A …

This review identifies current machine-learning algorithms implemented in building
structural health monitoring systems and their success in determining the level of damage in …

The development of Structural Health Monitoring (SHM) and Non-Destructive Testing (NDT)
techniques has rapidly evolved and matured over the past few decades. Advances in sensor …

Strategic major infrastructure ageing requires structural health monitoring usage to avoid
critical safety issues and disasters. Machine Learning can be a valuable tool to automate the …

The present work offers a comprehensive overview of methods related to condition
assessment of bridges through Structural Health Monitoring (SHM) procedures, with a …

High-power white light-emitting diodes (LEDs) have demonstrated superior efficiency and
reliability compared to traditional white light sources. However, ensuring maximum …

Compressed sensing (CS) for sensor-near vibration diagnostics represents a suitable
approach for the design of network-efficient structural health monitoring systems. This article …

Transfer learning techniques for structural health monitoring in bridge-type structures are
investigated, focusing on model generalizability and domain adaptation challenges. Finite …