Extraction of façade features from multiple open data sources for BIPV potential


Date

2024-04

Publication Type

Conference Poster

ETH Bibliography

yes

Citations

Altmetric

Data

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.

Publication status

published

External links

Editor

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 check_circle
08060 - FCL / FCL

Notes

Funding

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