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Building Rooftop Analysis for Solar Panel Installation Through Point Cloud Classification - A Case Study of National Taiwan University

  • Aritra Pal
  • Yun-Tsui Chang
  • Chien-Wen Chen
  • Chen-Hung Wu
  • Pavan Kumar
  • Shang-Hsien Hsieh

As climate change intensifies, we must embrace renewable solutions like solar energy to combat greenhouse gas emissions. Harnessing the sun's power, solar energy provides a limitless and eco-friendly source of electricity, reducing our reliance on fossil fuels. Rooftops offer prime real estate for solar panel installation, optimizing sun exposure, and maximizing clean energy generation at the point of use. For installing solar panels, inspecting the suitability of building rooftops is essential because faulty roof structures or obstructions can cause a significant reduction in power generation. Computer vision-based methods proved helpful in such inspections in large urban areas. However, previous studies mainly focused on image-based checking, which limits their usability in 3D applications such as roof slope inspection and building height determination required for proper solar panel installation. This study proposes a GIS-integrated urban point cloud segmentation method to overcome these challenges. Specifically, given a point cloud of a metropolitan area, first, it is localized in the GIS map. Then a deep-learning-based point cloud classification model is trained to detect buildings and rooftops. Finally, a rule-based checking determines the building height, roof slopes, and their appropriateness for solar panel installation. While testing at the National Taiwan University campus, the proposed method demonstrates its efficacy in assessing urban rooftops for solar panel installation

  • Keywords:
  • Sustainable campus,
  • renewable energy,
  • point cloud segmentation,
  • deep learning,
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Aritra Pal

National Taiwan University, Taiwan (Province of China) - ORCID: 0000-0002-1644-7400

Yun-Tsui Chang

National Taiwan University, Taiwan (Province of China) - ORCID: 0000-0003-1515-4187

Chien-Wen Chen

National Taiwan University, Taiwan (Province of China)

Chen-Hung Wu

National Taiwan University, Taiwan (Province of China) - ORCID: 0000-0003-3997-1907

Pavan Kumar

National Taiwan University, Taiwan (Province of China)

Shang-Hsien Hsieh

National Taiwan University, Taiwan (Province of China)

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  • Publication Year: 2023
  • Pages: 1042-1048

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  • Publication Year: 2023

Chapter Information

Chapter Title

Building Rooftop Analysis for Solar Panel Installation Through Point Cloud Classification - A Case Study of National Taiwan University

Authors

Aritra Pal, Yun-Tsui Chang, Chien-Wen Chen, Chen-Hung Wu, Pavan Kumar, Shang-Hsien Hsieh

DOI

10.36253/979-12-215-0289-3.104

Peer Reviewed

Publication Year

2023

Copyright Information

© 2023 Author(s)

Content License

CC BY-NC 4.0

Metadata License

CC0 1.0

Bibliographic Information

Book Title

CONVR 2023 - Proceedings of the 23rd International Conference on Construction Applications of Virtual Reality

Book Subtitle

Managing the Digital Transformation of Construction Industry

Editors

Pietro Capone, Vito Getuli, Farzad Pour Rahimian, Nashwan Dawood, Alessandro Bruttini, Tommaso Sorbi

Peer Reviewed

Publication Year

2023

Copyright Information

© 2023 Author(s)

Content License

CC BY-NC 4.0

Metadata License

CC0 1.0

Publisher Name

Firenze University Press

DOI

10.36253/979-12-215-0289-3

eISBN (pdf)

979-12-215-0289-3

eISBN (xml)

979-12-215-0257-2

Series Title

Proceedings e report

Series ISSN

2704-601X

Series E-ISSN

2704-5846

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