Conventional damage detection techniques are gradually being replaced by state-of-the-art
smart monitoring and decision-making solutions. Near real-time and online damage …

The recent development of machine learning (ML) and Deep Learning (DL) increases the
opportunities in all the sectors. ML is a significant tool that can be applied across many …

Bridges play a crucial role in modern societies, regardless of their culture, geographical
location, or economic development. The safest, economical, and most resilient bridges are …

The health monitoring system of a bridge is an important guarantee for the safe operation of
the bridge and has always been a research hotspot in the field of civil engineering. This …

Damage detection and safety assessment play a prominent role in the integrity management
of bridge structures. Environmental and operational variability are the leading factors that …

Abstract Machine learning is one of the key pillars of industry 4.0 that has enabled rapid
technological advancement through establishing complex connections among …

There is a need for reliable structural health monitoring (SHM) systems that can detect local
and global structural damage in existing steel bridges. In this paper, a data-based SHM …

Tunnelling-induced ground deformations inevitably affect the safety of adjacent
infrastructures. Accurate prediction of tunnelling-induced deformations is of great importance …

A digital twin of a geotechnical project (eg, a reclamation or ground improvement project) is
a virtual model that aims to continuously learn from actual observations (eg, site …

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 …