Structural Health Monitoring
adminAbout ArtIStE and Structural Health Monitoring
Structural Health Monitoring
Monitoring structural health and degradation in structures is a key point for modern infrastructure networks as well as in cities and historical constructions.
Maintaining continuous structural performance depends highly on monitoring the occurrence, formation, and propagation of damage.
Numerous monitoring and detection approaches have been developed to provide practical means for early warning against structural damage or any type of anomaly.
Meanwhile, with emerging computing power and sensing technology in the last decade, Machine Learning (ML) algorithms have become more feasible and extensively used in structural damage detection with interesting performance and promising accuracy.
The scientific community has an increasing interest in this field, and the ArtIStE research group has the main aim to provide a wide exchange of experience and knowledge in the field that different research groups are developing separately.
