Cultural heritage documentation, analysis and management using building information modelling: State of the art and perspectives

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Abstract

This chapter presents current issues relating to the use of a building information modelling (BIM) approach in the field of cultural heritage, which is better known as historic-BIM (H-BIM). Technological innovation in the field of automatic metric data acquisition (e.g., 3D laser scanning, digital photogrammetry techniques) requires data processing to produce a coherent parametric model that is congruent with metric survey information. Working with historical artefacts, this process becomes very complex, because the existing tools used to support BIM methodologies are mainly oriented towards new design interventions. From this perspective, the aim of our research is to explore the state of the art of current data acquisition techniques and their integration to obtain a master model, which is defined in the literature as an “inventory BIM model”. We will analyse the different scan-to-BIM approaches aimed at creating building object model (BOM) components that, using different acquisition techniques to obtain geometric data, allow the user to define the level of accuracy with which they are generated; in addition, the integrated development of new technologies for existing management (in terms of data enrichment of non-geometric information) will be analysed. Future research perspectives in this field are directed toward the design of a mechatronic system that optimizes computing systems, thus improving the efficiency and effectiveness of the entire process, and making use of a wealth of interdisciplinary knowledge in order to arrange a hierarchy of knowledge that can be shared with other professionals involved in interventions for the protection of cultural heritage.

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Chiabrando, F., Donato, V., Lo Turco, M., & Santagati, C. (2018). Cultural heritage documentation, analysis and management using building information modelling: State of the art and perspectives. Intelligent Systems, Control and Automation: Science and Engineering, 92, 181–202. https://doi.org/10.1007/978-3-319-68646-2_8

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