Augmenting visual inspection technologies — that have offered partial solutions to speed damage assessment in recent years — with a new machine learning approach, the researchers have created a system that they believe could enable efficient identification and inspection of problem areas by autonomous robots. Reported in the journal Automation in Construction, their multi-scale system combines computer vision with a deep-learning algorithm to pinpoint problem areas of cracking before directing a series of laser scans of the regions to create a “digital twin” computer model that can be used to assess and monitor the damage.
