In this paper, we want to propose an investigation and a re-reading of the “Conventazzo” of San Pietro di Deca in Torrenova (ME), through the use of geomatics techniques (laser scanner, UAV—Unmanned Aerial Vehicle-photogrammetry and BIM—Building Information Modeling) and a reconstruction and representation of different morpho-typological phases that highlight the numerous changes that this structure has undergone over the years. Particular attention was given to the BIM/HBIM (Heritage BIM) construction, bearing in mind that, in particular, the use of HBIM software for cultural heritage cannot perfectly represent old buildings with complex notable and particularly detailed architecture. Specifically, a new methodology is presented in order to replicate the complex details found in antique buildings, through the direct insertion of various 3D model parts (.obj) (point cloud segmentation from laser scanner and UAV/photogrammetry survey) into a BIM environment that includes intelligent objects linked to form the smart model. By having a huge amount of information available in a single digital model (HBIM), and by including all the information acquired during the survey campaign, it is possible to study the morphotypological evolutions of the building without the need to carry out subsequent survey campaigns. The limit of the proposed methodology, compared to the most used methodologies (despite the good results obtained), is that it requires the use of many types of software and is very slow. The proposed methodology was put to the test on the reconstruction of the “Conventazzo” in San Pietro di Deca, Torrenova (Messina).
<p>3D modelling of archaeological and historical structures is the new frontier in the field of conservation science. Similarly, the identification of buried finds, which enhances their multimedia diffusion and restoration, has gained relevance. As such sites often have a high level of structural complexity and complicated territorial geometries, accuracy in the creation of 3D models and the use of sophisticated algorithms for georadar data analysis are crucial. This research is the first step in a larger project aimed at reclaiming the ancient villages located in the Greek area of southern Italy. The present study focuses on the restoration of the village of Africo (RC), a village hit by past flooding. The survey began with a laser scan of the church of St. Nicholas, using both the Faro Focus3D and the Riegl LMS-Z420i laser scanner. At the same time, georadar analyses were carried out in order to pinpoint any buried objects. In the processing phase, our own MATLAB algorithms were used for both laser scanner and georadar datasets and the results compared with those obtained from the scanners’ respective proprietary software. We are working to develop a tourism app in both augmented and virtual reality environments, in order to disseminate and improve access to cultural heritage. The app allows users to see the 3D model and simultaneously access information on the site integrated from a variety of repositories. The aim is to create an immersive visit, in this case, to the church of St. Nicholas.</p><p><strong>Highlights:</strong></p><ul><li><p>Use of different algorithms for registration of terrestrial laser scans and analysis of the data obtained.</p></li><li><p>3D acquisition, processing and restitution methodology from georadar data.</p></li><li><p>Implementation of a tourist app in both virtual and augmented reality by integrating geomatics methodologies.</p></li></ul>
<p><strong>Abstract.</strong> Modern surveying techniques, with the combined use of Unmanned Aerial Vehicles (UAV) with low-cost photographic sensors, and photogrammetric techniques, allows obtaining a precise virtual reconstruction of environment and object with centimetre accuracy. Recently, the diffusion of UAV allows the survey of extensive areas significantly reducing survey time and costs. The raw output obtainable from such survey operations consists of a three-dimensional point cloud. Numerous applications in architecture, monitoring and surveying and structural analysis require objects identification in the 3d scene to classify different element in the acquired scene and extract relevant information. Point cloud analysis, and in particular segmentation and classification techniques, are actually used to identify objects within the scenes, assign to a specific class and use them for subsequent studies. These techniques represent an open research theme and the key to add value to the entire process. Actual methodologies are based on 3d spatial analysis on the point cloud. In this paper, starting from photogrammetric reconstruction, a methodology for segmentation and classification of point cloud based on image analysis is presented. The object identification on the image’s dataset is performed using a Neural Network and subsequently the identified object on dataset are transfer into the 3d environment. This classification is performed to segment structural parts of bridges and viaduct, acquire geometric information, and perform a structural analysis to preserve relevant and ancient structure. A case study for the segmentation of the point cloud acquired with an aerial survey of a Viaduct is presented. The performed segmentation allows obtaining structural elements of different type of viaduct and bridges, is propaedeutic to verify the health of the structure and schedule maintenance intervention. The methodology can be applied to different type of bridges, from reinforced concrete to ancient masonry to preserve the state of conservation.</p>
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