Abstract Machine learning (ML) has become the most successful branch of artificial
intelligence (AI). It provides a unique opportunity to make structural engineering more …

Structural health monitoring (SHM) and damage assessment of civil engineering
infrastructure are complex tasks. Structural health and strength of structures are influenced …

Annually, millions of dollars are spent to carry out defect detection in key infrastructure
including roads, bridges, and buildings. The aftermath of natural disasters like floods and …

Abstract Applications of Machine Learning (ML) algorithms in Structural Health Monitoring
(SHM) have become of great interest in recent years owing to their superior ability to detect …

Artificial intelligence (AI) is proving to be an efficient alternative approach to classical
modeling techniques. AI refers to the branch of computer science that develops machines …

Over the last two decades, the integration of big data and deep learning technologies has
demonstrated remarkable effectiveness across various domains of civil engineering, leading …

The dramatic spread of urbanization in modern cities requires smart solutions to address
critical issues such as mobility, healthcare, energy, and civil infrastructure. The Internet of …

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 …

Recently, there has been a growing interest in deploying smart materials as sensing
components of structural health monitoring systems. In this arena, piezoelectric materials …

Structural health monitoring (SHM) systems are used to analyze the health of infrastructures
such as bridges, using data from various types of sensors. While SHM systems consist of …