The paper results from preliminary research experiences focused on the use of Artificial Intelligence as a tool for processing the large amount of data that can be obtained from digitisation processes applied to the Architectural Heritage. The new interpretative scenarios will be outlined starting, on one hand, from a series of consolidated experiences in the field of three–dimensional survey, modelling and semantic enrichment, and, on the other, from the use of Augmented Reality tools for the fruition of the Heritage itself. The research aims to further investigate the great potential of processing point cloud models using Artificial Intelligence, to extrapolate, from the digitized data, information levels that go beyond shapes, offering better integration within the Building Information Modeling environment.

From AI to H-BIM: New Interpretative Scenarios in Data Processing

Federica Maietti
Writing – Original Draft Preparation
;
Marco Medici
Writing – Original Draft Preparation
;
Ernesto Iadanza
Writing – Original Draft Preparation
2021

Abstract

The paper results from preliminary research experiences focused on the use of Artificial Intelligence as a tool for processing the large amount of data that can be obtained from digitisation processes applied to the Architectural Heritage. The new interpretative scenarios will be outlined starting, on one hand, from a series of consolidated experiences in the field of three–dimensional survey, modelling and semantic enrichment, and, on the other, from the use of Augmented Reality tools for the fruition of the Heritage itself. The research aims to further investigate the great potential of processing point cloud models using Artificial Intelligence, to extrapolate, from the digitized data, information levels that go beyond shapes, offering better integration within the Building Information Modeling environment.
2021
9788835125280
Cultural Heritage, Point Cloud, Artificial Intelligence, H–BIM, Data Management
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11392/2463129
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