The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Citation
Articles | Volume XLII-2
https://doi.org/10.5194/isprs-archives-XLII-2-909-2018
https://doi.org/10.5194/isprs-archives-XLII-2-909-2018
30 May 2018
 | 30 May 2018

BUILDING INFORMATION MODELS FOR MONITORING AND SIMULATION DATA IN HERITAGE BUILDINGS

D. P. Pocobelli, J. Boehm, P. Bryan, J. Still, and J. Grau-Bové

Keywords: HBIM, Dynamo, weathering, heritage buildings, environmental modelling, environmental monitoring

Abstract. This paper analyses the use of BIM in heritage buildings, assessing the state-of-the-art and finding paths for further development. Specifically, this work is part of a broader project, which final aim is to support stakeholders through BIM. Given that humidity is one of the major causes of weathering, being able to detect, depict and forecast it, is a key task. A BIM model of a heritage building – enhanced with the integration of a weathering forecasting model – will be able to give detailed information on possible degradation patterns, and when they will happen. This information can be effectively used to plan both ordinary and extraordinary maintenance. The Jewel Tower in London, our case study, is digitised using combined laser scanning and photogrammetry, and a virtual model is produced. The point cloud derived from combined laser scanning & photogrammetry is traced out in with Autodesk Revit, where the main volumetry (gross walls and floors) is created with parametric objects. Surface characterisation of the façade is given through renderings. Specifically, new rendering materials have been created for this purpose, based on rectified photos of the Tower. The model is then integrated with moisture data, organised in spreadsheets and linked to it via parametric objects representing the points where measurements had been previously taken. The spatial distribution of moisture is then depicted using Dynamo. This simple exercise demonstrates the potential Dynamo has for condition reporting, and future work will concentrate on the creation of a complex forecasting model to be linked through it.