Structural Health Monitoring (SHM) systems have been widely used to guarantee the safe functioning of civil infrastructure to make satisfactory decisions on structural maintenance, repair, and rehabilitation. Although conventional SHM systems are one of the common tools for damage assessment of civil infrastructure, they have many drawbacks such as difficulty in assumptions to meet the real work, time-consuming, and focusing solely on the simplified quantitative analysis which cannot solve the real-world problems. Therefore, new techniques are being developed utilizing soft computing strategies, which can be applied to a number of SHM applications in civil engineering.

As a result, sophisticated tools and computing techniques, and technologies such as artificial intelligence, machine learning, deep learning, Internet of Things (IoT), and data mining approaches are employed for extracting valuable information from large amounts of data to overcome the drawbacks of conventional SHM systems. Hence, the information obtained from soft computing approaches must be valid, authentic, innovative, and understandable with meaningful relationships from large quantities of data.

This Special Issue aims to provide in-depth insights into the use of state-of-the-art SHM systems through emerging tools and advanced computing techniques to improve the smartification, performance, benefaction, sustainment, automation, cost-effectivity, and safety in civil structures. We welcome high-quality reviews and original research papers. Engineering practice applications and case studies that are under system identification and structural damage detection are also encouraged.

Potential topics include but are not limited to the following:

• Structural control and health monitoring
• System identification of linear and non-linear structures
• Input-output structural damage detection
• Output-only structural damage detection
• Local-based damage diagnosis
• Vibration-based damage assessment
• Building, bridge, and dam safety monitoring
• Experimental and operational modal analysis
• Non-destructive testing of structural damage
• Experimental and numerical validation
• Damaging process and crack propagation