In recent years, the improvement of sensors and methodologies for 3D reality-based surveying has exponentially enhanced the possibility of creating digital replicas of the real world. LiDAR technologies and photogrammetry are currently standard approaches for collecting 3D geometric information of indoor and outdoor environments at different scales. This information can potentially be part of a broader processing workflow that, starting from 3D surveyed data and through Building Information Models (BIM) generation, leads to more complex analyses of buildings’ features and behavior (Figure 1). However, creating BIM models, especially of historic and heritage assets (HBIM), is still resource-intensive and time-consuming due to the manual efforts required for data creation and enrichment. Improve 3D data processing, interoperability, and the automation of the BIM generation process are some of the trending research topics, and benchmark datasets are extremely helpful in evaluating newly developed algorithms and methodologies for these scopes. This paper introduces the InCUBE dataset, resulting from the activities of the recently funded EU InCUBE project, focused on unlocking the EU building renovation through integrated strategies and processes for efficient builtenvironment management (including the use of innovative renewable energy technologies and digitalization). The set of data collects raw and processed data produced for the Italian demo site in the Santa Chiara district of Trento (Italy). The diversity of the shared data enables multiple possible uses, investigations and developments, and some of them are presented in this contribution.

FROM 3D SURVEYING DATA TO BIM TO BEM: THE INCUBE DATASET / Roman, O.; Farella, E. M.; Rigon, S.; Remondino, F.; Ricciuti, S.; Viesi, D.. - In: INTERNATIONAL ARCHIVES OF THE PHOTOGRAMMETRY, REMOTE SENSING AND SPATIAL INFORMATION SCIENCES. - ISSN 2194-9034. - XLVIII-1/W3-2023:(2023), pp. 175-182. [10.5194/isprs-archives-XLVIII-1-W3-2023-175-2023]

FROM 3D SURVEYING DATA TO BIM TO BEM: THE INCUBE DATASET

O. Roman;
2023-01-01

Abstract

In recent years, the improvement of sensors and methodologies for 3D reality-based surveying has exponentially enhanced the possibility of creating digital replicas of the real world. LiDAR technologies and photogrammetry are currently standard approaches for collecting 3D geometric information of indoor and outdoor environments at different scales. This information can potentially be part of a broader processing workflow that, starting from 3D surveyed data and through Building Information Models (BIM) generation, leads to more complex analyses of buildings’ features and behavior (Figure 1). However, creating BIM models, especially of historic and heritage assets (HBIM), is still resource-intensive and time-consuming due to the manual efforts required for data creation and enrichment. Improve 3D data processing, interoperability, and the automation of the BIM generation process are some of the trending research topics, and benchmark datasets are extremely helpful in evaluating newly developed algorithms and methodologies for these scopes. This paper introduces the InCUBE dataset, resulting from the activities of the recently funded EU InCUBE project, focused on unlocking the EU building renovation through integrated strategies and processes for efficient builtenvironment management (including the use of innovative renewable energy technologies and digitalization). The set of data collects raw and processed data produced for the Italian demo site in the Santa Chiara district of Trento (Italy). The diversity of the shared data enables multiple possible uses, investigations and developments, and some of them are presented in this contribution.
2023
Roman, O.; Farella, E. M.; Rigon, S.; Remondino, F.; Ricciuti, S.; Viesi, D.
FROM 3D SURVEYING DATA TO BIM TO BEM: THE INCUBE DATASET / Roman, O.; Farella, E. M.; Rigon, S.; Remondino, F.; Ricciuti, S.; Viesi, D.. - In: INTERNATIONAL ARCHIVES OF THE PHOTOGRAMMETRY, REMOTE SENSING AND SPATIAL INFORMATION SCIENCES. - ISSN 2194-9034. - XLVIII-1/W3-2023:(2023), pp. 175-182. [10.5194/isprs-archives-XLVIII-1-W3-2023-175-2023]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11572/398029
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