Blockchain-enhanced computer vision approach for remote safety inspection in construction
Engineering, Construction and Architectural Management
ISSN: 0969-9988
Article publication date: 13 September 2024
Abstract
Purpose
Computer vision (CV) offers a promising approach to transforming the conventional in-person inspection practices prevalent within the construction industry. However, the reliance on centralized systems in current CV-based inspections introduces a vulnerability to potential data manipulation. Unreliable inspection records make it challenging for safety managers to make timely decisions to ensure safety compliance. To address this issue, this paper proposes a blockchain (BC) and CV-based framework to enhance safety inspections at construction sites.
Design/methodology/approach
This study adopted a BC-enhanced CV approach. By leveraging CV and BC, safety conditions are automatically identified from site images and can be reliably recorded as safety inspection data through the BC network. Additionally, by using this data, smart contracts coordinate inspection tasks, assign responsibilities and verify safety performance, managing the entire safety inspection process remotely.
Findings
A case study confirms the framework’s applicability and efficacy in facilitating remote and reliable safety inspections. The proposed framework is envisaged to greatly improve current safety inspection practices and, in doing so, contribute to reduced accidents and injuries in the construction industry.
Originality/value
This study provides novel and practical guidance for integrating CV and BC in construction safety inspection. It fulfills an identified need to study how to leverage CV-based inspection results for remotely managing the safety inspection process using BC. This work not only takes a significant step towards data-driven decision-making in the safety inspection process, but also paves the way for future studies aiming to develop tamper-proof data management systems for industrial inspections and audits.
Keywords
Acknowledgements
This research was conducted with the support of the “National R&D Project for Smart Construction Technology (No.RS-2020-KA156291)” funded by the Korea Agency for Infrastructure Technology Advancement under the Ministry of Land, Infrastructure and Transport, and managed by the Korea Expressway Corporation. Also, this research was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (No. NRF-2022R1A2B5B02002553 and No. RS-2023-00217322). Additionally, this research was supported by the Chung-Ang University Graduate Research Scholarship in 2023 and the Chung-Ang University Research Grants in 2022.
Citation
Kim, D., Yang, J., Lee, D., Lee, D., Rahimian, F. and Park, C. (2024), "Blockchain-enhanced computer vision approach for remote safety inspection in construction", Engineering, Construction and Architectural Management, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/ECAM-03-2024-0385
Publisher
:Emerald Publishing Limited
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