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

Structural Health Monitoring (SHM) of civil structures has been constantly evolving with
novel methods, advancements in data science, and more accessible technology to address …

Structural condition identification based on monitoring data is important for automatic civil
infrastructure asset management. Nevertheless, the monitoring data are almost always …

With the growing number of well-aged bridges and the urgency in develo**
reliable,(pseudo-) real-time monitoring of structural safety and integrity, there is a worldwide …

Deep learning networks facilitate automated damage identification and performance
evaluation for concrete structures using electromechanical impedance/admittance …

Deep learning algorithms are transforming a variety of research areas with accuracy levels
that the traditional methods cannot compete with. Recently, increasingly more research …

The cross-scene problem within the field of guided wave-based interfacial debonding
detection in steel-reinforced concrete structures is a significant challenge. This issue arises …

Condition assessment and health monitoring (CAHM) of built assets requires effective and
continuous monitoring of any changes to the material and/or geometric properties of the …

Health monitoring technologies, empowered by sensor-driven information and model
updating, play an important role in assessing the status of civil structures and detecting …

Due to the inherent uncertainty and complexity of civil infrastructure, it is challenging to
simulate their structural dynamic responses accurately and efficiently. Existing model …