Abstract
The increasing number of buildings, due to erosion and extraordinary effects, has increasingly made technological advancements focused on innovative methods possible. This has become more prominent alongside traditional practices such as visual inspection and destructive building diagnostic methods. Thanks to the continuous development of tools, technologies and methodologies, the accurate and detailed digital mapping of buildings (including all their aspects) is available. Among these solutions, the laser scanner point cloud is the most popular due to its high level of detail. The newly emerging and now widespread survey procedures based on laser, photogrammetric remote sensing reflect a real-time, current state of the buildings, which maximizes the accuracy of the Building Information Model (BIM) - Historic Building Information Model (HBIM) completed in the later phases and helps detect structural or surface defects. This study presents the analyzing techniques of point clouds to diagnose buildings, assess their condition, identify errors, and develop sustainability strategies. It also explores areas that require further research and development to enhance the effectiveness of these methods. In the first phase of the paper, the currently used point cloud generation technologies (e.g.: laser scanning, photogrammetry, light detection and ranging (LiDAR)) will be presented with their advantages and disadvantages. The research methodology was conducted using the VOSviewer software to visually analyze bibliometric networks from a dataset of scientific publications, focusing on trends in structural health monitoring and highlighting key areas such as damage detection, computer vision, and AI-based techniques. In the second phase of the study, the possibilities of the analysis of point clouds and image processing-based survey options for structural diagnostic purposes will be explained and presented. The evaluation of the three damage detection methodologies (Geometrical features, Color and intensity information, Combined Method) highlights their complexity, technological requirements, cost, practical applicability, and accuracy. During the analysis, the goal is to map and systematize innovative methods supported by digital tools for diagnostic tasks in existing buildings.
