Most civil infrastructure worldwide is currently past its design life. This situation has
precipitated the need for more systematic inspections and continual monitoring of …

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

With the advancement of deep learning, data-driven structural damage identification (SDI)
has shown considerable development. However, collecting vibration signals related to …

Indirect bridge health monitoring (iBHM) has gained significant attention in recent years as
an alternative to direct bridge monitoring techniques. iBHM leverages the use of a vehicle …

Pipeline leakage and water deposits can cause serious consequences, such as
environmental pollution, safety accidents, and economic losses. Therefore, effective …

Bridges hold an imperative role in the transportation network and infrastructure. Continuous
monitoring of their condition is crucial for the efficient operation of transportation facilities …

Environmental Sound Recognition (ESR) plays a crucial role in smart cities by accurately
categorizing audio using well-trained Machine Learning (ML) classifiers. This application is …

Environmental effects may lead to cracking, stiffness loss, brace damage, and other
damages in bridges, frame structures, buildings, etc. Structural Health Monitoring (SHM) …

For the purpose of maintaining and prolonging the service life of civil constructions,
structural damage must be closely monitored. Monitoring the incidence, formation, and …

With the ever-increasing number of well-aged bridges carrying traffic loads beyond their
intended design capacity, there is an urgency to find reliable and efficient means of …