In recent years, advanced digital technologies have driven an outstanding paradigm shift in the field of architectural heritage, particularly for building modelling, historical documentation and touristic promotion. Nonetheless, they show great potentialities in the field of assessment and control of the state of conservation of heritage buildings. In particular, close-range and aerial photogrammetry have increasingly relied on low-cost and user-friendly tools and procedures, with a high degree of automation that makes them accessible to specialists who are foremost involved in architectural diagnosis and conservation, rather than in remote sensing sciences. In this framework, this paper provides a scoping review of 117 publications, based on the PRISMA protocol, from Scopus and Web of Science databases, related to the employment of photogrammetric models and methods, with specific focus on the targets and purposes of the diagnostic process, including decay mapping, structural monitoring and modelling, non-destructive investigation and multi-source documentation. In detail, the results point out that current studies mainly support robust processing of large amounts of information from direct observation of surface alterations, systematic correlation between materials, construction characteristics, visible anomalies and experimental measurements, as well as multi-disciplinary collaborative workflows through remote inspection and harmonized data management. Further improvements were identified, including standardization of acquisition procedures, automatization of elaboration pipelines, integration of real-time data, validation of diagnosis decision-making support tools and scalability to networks of assets.

Nowadays, built heritage condition assessment is realized through on-site or photo-aided visual inspections, reporting pathologies manually on drawings, photographs, notes. The knowledge of the state of conservation goes through subjective and time or cost consuming procedures. This is even relevant for a historic building characterized by geometrical and morphological complexity and huge extension, or at risk of collapse. In this context, advancements in the field of Computer Vision and Artificial Intelligence provide an opportunity to address these criticalities. The proposed methodology is based on a Mask R-CNN model, for the detection of decay morphologies on built heritages, and, particularly on historic buildings. The experimentation has been carried out and validated on a highly heterogeneous dataset of images of historic buildings, representative of the regional Architectural Heritage, such as: castles, monasteries, noble buildings, rural buildings. The outcomes highlighted the significance of this remote, non-invasive inspection technique, in support of the technicians in the preliminary knowledge of the building state of conservation, and, most of all, in the decay mapping of some particular classes of alterations (moist area, biological colonization).

Nowadays, built heritage condition assessment is realized through on-site or photo-aided visual inspections, reporting pathologies manually on drawings, photographs, notes. The knowledge of the state of conservation goes through subjective and time or cost consuming procedures. This is even relevant for a historic building characterized by geometrical and morphological complexity and huge extension, or at risk of collapse. In this context, advancements in the field of Computer Vision and Artificial Intelligence provide an opportunity to address these criticalities. The proposed methodology is based on a Mask R-CNN model, for the detection of decay morphologies on built heritages, and, particularly on historic buildings. The experimentation has been carried out and validated on a highly heterogeneous dataset of images of historic buildings, representative of the regional Architectural Heritage, such as: castles, monasteries, noble buildings, rural buildings. The outcomes highlighted the significance of this remote, non-invasive inspection technique, in support of the technicians in the preliminary knowledge of the building state of conservation, and, most of all, in the decay mapping of some particular classes of alterations (moist area, biological colonization).