Role of Artificial Intelligence in Structural Health Monitoring-A Brief Evaluation

Abstract

Artificial intelligence (AI) refers to the capacity of a machine or a computer to ‘think’ or reason in the way a human would, utilizing experience, learned facts, and flexible rules to solve problems that may not fit the standard outlines for a normal algorithm. From this follows the utilization of AI in various sectors, such as the information technology (IT) industry, media, healthcare and medicine, logistics, environmental sustainability, finance, business, and even judicial systems. Nowadays, the application of AI in the segment of engineering and materials science is also growing fast. Under this sector, AI can be implemented to replace trial-and-error lab work by predicting future models for the computational material discovery subsegment. In another subcategory of this segment, namely structural health and digital twins, AI can be applied for computer vision inspections for identifying cracks, corrosion, spalling, etc. Also, deep learning models can be implemented to analyze real-time data and to predict microscopic cracks, which is a next-to-impossible task for any human being. In this study, we explore the utilization of AI in various fields of civil engineering with a focus on the field of structural health monitoring. In this article, care has been taken to thoroughly investigate all the research done in the structural health monitoring (SHM) sector with the application of AI and its implications. Main emphasis has been given to the detection of different types of damage in a structural body using AI. Further, the research investigation has been narrowed down to the identification of cracks using this latest technology. Concrete conclusions have been drawn in the last segment, which highlights today’s challenges and their limitations.