An artificial intelligence and mixed reality approach for optimizing the bridge inspection workflow

Abstract: Detecting damage to bridges at an early stage is very important for financial and environmental reasons. This can only be achieved by regular and frequent inspections by experts, who mostly use paper based methods to document their findings. This paper aims to develop a concept for a bridge inspection tool using multiple types of hardware devices to support on-site bridge inspection personnel in assessing and documenting damages, employing combinations of both AI and MR technologies. Interviews will be conducted with structural inspectors from various companies and from different sectors to identify important requirements. The tool will be compatible with existing databases for infrastructure.