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- W2938860145 abstract "Existing buildings often have low energy efficiency standards. For the preparation of retrofits, reliable high-quality data about the status quo is required. However, state-of-the-art analysis methods mainly rely on on-site inspections by experts and hence tend to be cost-intensive. In addition, some of the necessary devices need to be installed inside the buildings. As a consequence, ownershesitate to obtain sufficient information about potential refurbishment measures for their houses and underestimate possible savings. Remote sensing measurement technologies have the potential to provide an easy-to-use and automatable way to energetically analyze existing buildings objectively. To prepare an energetic simulation of the status quo and of possible retrofitscenarios, remote sensing data from different data sources have to be merged and combined with additional knowledge about the building. This contribution presents the current state of a project on the development of new and the optimization of conventional data acquisition methods for the energetic analysis of existing buildings solely based on contactless measurements, generalinformation about the building, and data that residents can obtain with little effort. For the example of a single-family house in Morschenich, Germany, geometrical, semantical, and physical information are derived from photogrammetry and quantitative infrared measurements. Both are performed with the help of unmanned aerial vehicles (UAVs) and are compared to conventional methods for energy efficiency analysis regarding accuracy of and necessary effort for input data for building energy simulation. The concept of an object-oriented building model for measurement data processing is presented. Furthermore, an outlook is given on the project involving advanced remote sensing techniques such as ultrasound and microwave radar application for the measurement of additional energetic building parameters." @default.
- W2938860145 created "2019-04-25" @default.
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- W2938860145 date "2018-01-01" @default.
- W2938860145 modified "2023-09-23" @default.
- W2938860145 title "Building Tomograph – From Remote Sensing Data of Existing Buildings to Building Energy Simulation Input" @default.
- W2938860145 hasPublicationYear "2018" @default.
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