Web platform for building roof maintenance inspection using UAS and artificial intelligence
International Journal of Building Pathology and Adaptation
ISSN: 2398-4708
Article publication date: 23 November 2023
Issue publication date: 4 February 2025
Abstract
Purpose
This work aims to develop a web platform for inspecting roof structures for technical assistance supported by drones and artificial intelligence. The tools used were HTML, CSS and JavaScript languages; Firebase software for infrastructure; and Custom Vision for image processing.
Design/methodology/approach
This study adopted the design science research approach, and the main stages for the development of the web platform include (1) creation and validation of the roof inspection checklist, (2) validation of the use of Custom Vision as an image recognition tool, and (3) development of the web platform.
Findings
The results of automatic recognition showed a percentage of 77.08% accuracy in identifying pathologies in roof images obtained by drones for technical assistance.
Originality/value
This study contributed to developing a drone-integrated roof platform for visual data collection and artificial intelligence for automatic recognition of pathologies, enabling greater efficiency and agility in the collection, processing and analysis of results to guarantee the durability of the building.
Keywords
Acknowledgements
This work was supported by the Ministry of Education of Brazil through CAPES (Agency for Support and Evaluation of Graduate Education), and by the Ministry of Science, Technology, Innovation, and Communication of Brazil through CNPq (National Council for Scientific and Technological Development) (Grant Number 421262/2018-4). The authors would also like to thank the company for the opportunity to develop this investigation.
Citation
Staffa Junior, L.d.B., Bastos Costa, D., Torres Nogueira, J.L. and Silva, A.S. (2025), "Web platform for building roof maintenance inspection using UAS and artificial intelligence", International Journal of Building Pathology and Adaptation, Vol. 43 No. 1, pp. 4-28. https://doi.org/10.1108/IJBPA-12-2022-0186
Publisher
:Emerald Publishing Limited
Copyright © 2023, Emerald Publishing Limited