Bridge management with AI, UAVs, and BIM

Abstract

Artificial intelligence (AI) has significantly advanced infrastructure monitoring, particularly through machine learning and deep learning techniques. In bridge management, combining AI with Building Information Modeling (BIM) and unmanned aerial vehicles (UAVs) enhances accuracy, efficiency, and safety. This paper reviews AI, UAV, and BIM applications, focusing on technology integration and algorithm performance. A systematic literature review using the PRISMA framework analyzed 4436 papers from Scopus and Web of Science. Findings indicate that AI is mainly applied to damage detection, primarily through Convolutional Neural Networks (CNNs), while UAVs provide high-resolution imaging, and BIM serves as a platform for data storage and visualization. Key challenges include the lack of standardized datasets, limited automation in decision-making, and weak interoperability among these technologies. Future research should focus on dataset availability, hybrid AI models, and integrated automation strategies. This review highlights key areas to enhance AI-based bridge management.