Abstract
In the process of urban development in contemporary China, the requirements for safety inspection of building facades are increasing. However, the widely used inspection methods are mainly manual hand-held equipment inspection, there are problems such as relying on subjective judgment, slow inspection efficiency, dangerous working environment, etc., and the lack of transparent channels for users to understand the information of the building inspection, which makes it difficult to implement the follow-up maintenance. Therefore, this project researches from the three aspects of customer service, inspection means, and inspection service process, and builds a product service system for building facade inspection with the goal of improving the efficiency and accuracy of inspection, as well as enhancing the customer’s experience. The system contains both tangible and intangible parts, the tangible product is the drone and user APP, and the intangible part is the service process and experience for the owners. The system was tested for usability and the results showed a favorable user experience.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Hu, X., et al.: Research on the analysis of characteristics of external wall surface detachment in high-rise building and its prevention and control measures. Sichuan Build. Sci. 49(06), 57–67 (2023)
Chen, L., et al.: Study on intelligent detection and identification technology of building facade and auxiliary facilities damage. Construct. Technol. 52(03), 25–30+90 (2023)
Liang, H., et al.: Towards UAVs in construction: advancements, challenges, and future directions for monitoring and inspection. Drones 7(3), 202 (2023)
Cai, T., et al.: Detection of cracks in building facade based on UAV. Geotech. Investig. Surveying 50(04), 45–51 (2022)
Chen, J., et al.: Infrared thermal imaging detection of surface cracks in external insulation layer of building exterior wall. Laser Optoelectron. Prog. 59(22), 74–81 (2022)
Zhao, Y., et al.: Study on application of fine-tuning convolutional neural network in crack detection of building facade. Build. Struct. 54(03), 154–159 (2024)
Ko, P., Prieto, S.A., de Soto, B.G.: Develo** a free and open-source semi-automated building exterior crack inspection software for construction and facility managers. IEEE Access 11, 77099–77116 (2023). https://doi.org/10.1109/ACCESS.2023.3296793
Wang, G.: Service Design and Innovation. China Construction Industry Press, Bei**g (2017)
Liu, C., et al.: UAV autonomous inspection and crack detection towards building health monitoring. J. Tongji Univ. (Nat. Sci.) 50(07), 921–932+918 (2022)
Zhao, S., et al.: Structural health monitoring and inspection of dams based on UAV photogrammetry with image 3D reconstruction. Autom. Constr.. Constr. 130, 103832 (2021)
Wang, P., et al.: Intelligent development trend of building enclosure damage detection. J. Architect. Civil Eng. 39(04), 24–37 (2022)
Zhu, X., et al.: TPH-YOLOv5: Improved YOLOv5 based on transformer prediction head for object detection on drone-captured scenarios. In: Proceedings of the IEEE/CVF International Conference on Computer Vision 2021, pp. 2778–2788. IEEE Montreal (2021)
Acknowledgments
This study was funded by Key Teaching and Research Project of Anhui Province, China (2022jyxm1257) and National Student Innovation and Entrepreneurship Training Program, China (202210359066).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Ethics declarations
Disclosure of Interests
The authors have no competing interests to declare that are relevant to the content of this article.
Rights and permissions
Copyright information
© 2024 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Li, Y., Chen, J., Zhu, L., Yin, X. (2024). A Service System Design for Building Facade Inspection. In: Stephanidis, C., Antona, M., Ntoa, S., Salvendy, G. (eds) HCI International 2024 Posters. HCII 2024. Communications in Computer and Information Science, vol 2120. Springer, Cham. https://doi.org/10.1007/978-3-031-62110-9_35
Download citation
DOI: https://doi.org/10.1007/978-3-031-62110-9_35
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-62109-3
Online ISBN: 978-3-031-62110-9
eBook Packages: Computer ScienceComputer Science (R0)