Chapter 8 - Applications of computer vision-based structural health monitoring and condition assessment in future smart cities

Abstract

It is generally accepted that artificial intelligence (AI)-enabled computer vision will drive the next revolution in information modeling and decision-making actualizing the vision of future smart cities. Furthermore, due to the recent advances in sensors and computing technologies, the use of vision-based approaches provides an unprecedented opportunity to complement traditional structural health monitoring and nondestructive evaluation technologies, which will ultimately improve the resilience of structural systems. Moreover, vision-based methods are generally contactless and appropriate to be incorporated in mobile sensing robots such as unmanned aerial vehicles and unmanned ground vehicles, providing a transformative monitoring platform for civil infrastructures. This chapter surveys the recent theoretical, computational, and experimental advances in the use of computer vision and machine learning approaches for structural identification, control, damage detection, and health monitoring. To this end, fundamental theories of various computer vision techniques are discussed with reference to practical examples within the scope of autonomous civil infrastructure condition assessment. Some of the recent research trends are also presented along with a roadmap for future research directions.