Heritage buildings are valuable assets that represent national cultural identity. Proper building maintenance is a major issue for preservation, as building monitoring aspects and preventive measures are often only taken after physical damage happens. In the context of Indonesian heritage buildings, high levels of humidity which may cause condensation and soil dampness are often overlooked. Early detection methods are urgently required to effectively detect potential risks of condensation. This study aims to investigate condensation risk for heritage building surfaces by calculating thermal properties (i.e., emissivity, albedo) and Blinn–Phong BRDF values through the integration of thermal imaging and 3D scanning techniques. This approach supports architects and conservators in making informed decisions to protect and maintain cultural heritage structures. The study also highlights gaps in current Indonesian regulations regarding moisture presence and condensation risk detection in heritage buildings.@en

To date, the preservation techniques of heritage buildings in Indonesia are still limited to physical measurement, most of which are based on manual records. Consequently, lack of accuracy, cost and time consumption often lead to misinterpretation of crucial information during the decision-making process. This part includes physical amage (i.e., mold growth, flaking paint, water leaks), caused by condensation due to high relative humidity. Thanks to the development of advanced laser scanning technology, high-precision point cloud datasets can be obtained to conduct surface performance analysis. Furthermore, this study proposes an integrated computational method for detecting condensation risks in heritage buildings by making use of optical and thermal properties calculated from point cloud data. The proposed method specifically employs Blinn-Phong Bidirectional Reflectance Function (BRDF) model to calculate the distributed reflectance in a material based on the angle of incidence and material reflectance. Along with it, the point cloud measurement is also coupled with FLIR One Pro IR camera and HOBO data logger to analyze the thermal performances of the building surface. Ultimately, this study will provide architects with a better understanding regarding potential risks of condensation in the heritage building surface so that they can perform early detection tasks.@en

This study proposes a novel method of solar geometry by considering the potential application of point cloud data combined with the simulation of solar radiation. With the support of geometric and radiometric information stored in the point cloud such as position information (XYZ) color information (RGB), and reflection intensity (I), architects may compensate for missing information on the existing context during the simulation, especially due to the limited capacity of current 3D modelling sites. However, the dataset often comes in the format of unstructured point cloud data retrieved from merged data scans and as a result, the radiometric information is difficult to occupy due to multiple reference points. Through a 3D subtractive procedure, this study not only examines volumetric samples of the three-dimensional matrix that fulfills the criteria of solar envelopes but also finds the optimal values of the merged data scan for input of solar radiation. In this regard, simulation of solar radiation contributes to identifying the most and the least exposed areas to the sun in existing contexts. This provides information related to visible sun hours that can be used to perform ray tracing analysis between the proposed 3D plot and surrounding contexts. Our proposed method ultimately helps architects not only generate solar geometry based on real contextual settings but also to understand comprehensively the microclimate conditions of the design context.

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