Extraction of façade features from multiple open data sources for BIPV potential
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Author / Producer
Date
2024-04
Publication Type
Conference Poster
ETH Bibliography
yes
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OPEN ACCESS
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Abstract
Building-integrated photovoltaics (BIPV) façades are becoming increasingly important
in achieving zero-carbon targets. Several methods estimate BIPV
potential and take into account the overall size, orientation, and shading aspects of
individual façades in Switzerland. However, various architectural façade components,
such as windows and balconies, are neglected in the estimations despite their significant
impact on the overall BIPV energy production. Therefore, we propose an approach that
integrates multiple open data sources and deep learning techniques to acquire
and analyze façade features essential for estimating facade BIPV potential accurately.
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Publication status
published
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Book title
Journal / series
Volume
Pages / Article No.
Publisher
ETH Zurich, Architecture and Building Systems
Event
Data Science for the Sciences Conference (DS4S 2024)
Edition / version
Methods
Software
Geographic location
Date collected
Date created
Subject
Feature extraction; Building facade; BIPV
Organisational unit
03902 - Schlüter, Arno / Schlüter, Arno
08060 - FCL / FCL