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Book Chapter

Image Segmentation Applied to Urban Surface and Aerial Constraints Analysis

  • Marco Lorenzo Trani
  • Federica Madaschi

The rapid progress of artificial intelligence (AI) has prompted the exploration of its potential applications in the construction industry, although at a slower rate. Since the starting point of a design is the analysis of the site’s constraints, the purpose of the ongoing research is the application of artificial intelligence in risk assessment for site areas. The primary objective of this research project is to develop an interactive map that employs AI to identify potential surface and aerial interferences. This map aims to support planners, engineers, and architects during the site context analysis phase by providing real-time visualization of obstacles. The interactive map allows users to explore and analyze identified obstacles, enabling cluster markers and filtering of features. The results obtained from applying this approach in Milan, Italy, demonstrate its functionality and usability, highlighting the tool's ability to provide valuable information in both localized and citywide scenarios. Potential improvements such as size assessment and advanced marker generation are also being examined to enhance the management of surface and air interferences. The goal is to enhance the tool's functionality, accuracy, and planning efficiency in construction projects

  • Keywords:
  • Image Segmentation,
  • Risk Assessment,
  • Construction Site,
  • Clustering Techniques,
+ Show More

Marco Lorenzo Trani

Politecnico di Milano, Italy

Federica Madaschi

Politecnico di Milano, Italy

  1. Couto, João & José, Frederico & Santos, Barros & Rahnemay, Emilia & Kohlman Rabbani, Emilia. (2017). How Time Constraints Affect Safety Conditions at Construction Sites: Analysis of the Perception of Portuguese Construction Participants. EJGE. 2. 563.
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  4. Liu, Y. (2021). Efficient Fully Convolutional Networks for Dense Prediction Tasks. [University of Adelaide]. https://hdl.handle.net/2440/134023
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  6. Trani, M. L. (2012). Construction Site Design, Santarcangelo di Romagna (I), Maggioli Editore, 2012.
  7. Pan, Y., & Zhang, L. (2022). Integrating BIM and AI for Smart Construction Management: Current Status and Future Directions. Archives of Computational Methods in Engineering, 30(2), 1081–1110. DOI: 10.1007/s11831-022-09830-8
  8. Ranftl, R., Bochkovskiy, A., & Koltun, V. (2021). Vision Transformers for Dense Prediction. 2021 IEEE/CVF International Conference on Computer Vision (ICCV). DOI: 10.1109/iccv48922.2021.01196
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  • Publication Year: 2023
  • Pages: 907-916

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  • Publication Year: 2023

Chapter Information

Chapter Title

Image Segmentation Applied to Urban Surface and Aerial Constraints Analysis

Authors

Marco Lorenzo Trani, Federica Madaschi

DOI

10.36253/979-12-215-0289-3.90

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

36

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