Enhancing preservation: Addressing humidity challenges in Indonesian heritage buildings through advanced detection methods point cloud data

• Room-specific conditions and observations help determine early-stage condensation risk • Properly ventilated rooms with fewer technical issues have lower condensation risk • BRDF and surface temperature are proven to be correlated with condensation detection. • Point clouds with low BRDF values represent a high condensation risk. 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.

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Institutions

Publication Details

Journal
Results in Engineering
Published
2024-11-08
DOI
https://doi.org/10.1016/j.rineng.2024.103292
Citations
5
Primary Topic
3D Surveying and Cultural Heritage
Type
article
Field-Weighted Citation Impact
4.17

Funders

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article

Enhancing preservation: Addressing humidity challenges in Indonesian heritage buildings through advanced detection methods point cloud data

Muhammad Arif Rahman, Carola Hein, Miktha Farid Alkadri, Yuliana Yuliana et al.
5 citations
Results in Engineering
3D Surveying and Cultural Heritage
4.17
article

Enhancing preservation: Addressing humidity challenges in Indonesian heritage buildings through advanced detection methods point cloud data

Muhammad Arif Rahman, Carola Hein, Miktha Farid Alkadri, Yuliana Yuliana, Muhammad Rafif Cahyadi Agung
article en
5 citations

Abstract

• Room-specific conditions and observations help determine early-stage condensation risk • Properly ventilated rooms with fewer technical issues have lower condensation risk • BRDF and surface temperature are proven to be correlated with condensation detection. • Point clouds with low BRDF values represent a high condensation risk. 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.

Results in EngineeringVol. 24
University of Indonesia (ID), Delft University of Technology (NL)
Universitas Indonesia, Direktorat Riset and Pengembangan, Universitas Indonesia
Sustainable cities and communities
Openalex Percentile: Top 6%
3D Surveying and Cultural Heritage
4.17
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Enhancing preservation: Addressing humidity challenges in Indonesian heritage buildings through advanced detection methods point cloud data — Muhammad Arif Rahman, Carola Hein, et al. · Results in Engineering (2024) | TGRS Research Map | TGRS