Abstract. The focus of this paper is the analyses of various work pipelines, allowing to manage the transition from in-situ surveys to cloud of points and geometric meshes optimized for structural purposes. This topic is very challenging, and today is almost always performed through homemade, uncontrolled, approaches, requiring the passage of information between numerous codes. These unsupervised workflows often compromise the integrity and the reliability of the results. Here two experimental case studies are reported to check the performances of two pipelines, based on photographic and laser surveys, respectively. The proposed comparison is used to outline significant indications on how properly manage the transformation, in order to create a “true” digital twin of the given structure.

Artificial Intelligence (AI) is a trending topic in many research areas. In recent years, even building, civil, and structural engineering have also started to face with several new techniques and technologies belonging to this field, such as smart algorithms, big data analysis, deep learning practices, etc. This perspective paper collects the last developments on the use of AI in building engineering, highlighting what the authors consider the most stimulating scientific advancements of recent years, with a specific interest in the acquisition and processing of photographic surveys. Specifically, the authors want to focus both on the applications of artificial intelligence in the field of building engineering, as well as on the evolution of recently widespread technological equipment and tools, emphasizing their mutual integration. Therefore, seven macro-categories have been identified where these issues are addressed: photomodeling; thermal imaging; object recognition; inspections assisted by UAVs; FEM and BIM implementation; structural monitoring; and damage identification. For each category, the main new innovations and the leading research perspectives are highlighted. The article closes with a brief discussion of the primary results and a viewpoint for future lines of research.