Dr. Tariq Umar Tariq.Umar@uwe.ac.uk
Senior Lecturer in Construction Project Management
Dr. Tariq Umar Tariq.Umar@uwe.ac.uk
Senior Lecturer in Construction Project Management
Abbas Bozorgzadeh
Syed M Ahmed
Editor
Salman Azhar
Editor
Amelia Saul
Editor
Kelly Mahaffy
Editor
Rizwan Farooqui
Editor
A critical concern with the UK’s construction project progress monitoring and control techniques is their dependency on data collection, which is time-consuming and unproductive and may lead to various circumstances in managing projects. However, collecting and accurately analysing information from construction sites requires the development of technologies. As key AI technology, computer vision is a powerful tool for big data analysis which can address the
above challenges. This study explores the status of computer vision-construction project management (CV-CPM) adoption and the main barriers to and incentives for its adoption within UK construction sites. In this respect, an extensive review of literature covering the AI technology in construction management, the concept, function, and
usage of CV and its integration with CPM, including its benefits and drivers, and technical challenges was conducted with a specific focus on the UK construction industry. The study’s results indicated that construction practitioners are relatively aware of CV-CPM but lack competencies and skills. CV-CPM has been perceived to be relatively better than the traditional approach. Implications like the cost of implementation, lack of expertise, and resistance to change were the major challenges in CV-CPM adoption. Instead, technological development, decision-making, and competitiveness were classified as incentives for its adoption. The main contribution of this study is to provide construction professionals with a comprehensive list of barriers and incentives toward CV-CPM adoption. Industry
practitioners might benefit from this research's findings and detailed evaluations to develop successful adoption and transformation strategies as CV-CPM can accelerate the progress detection and data accessibility for outcomes.
Presentation Conference Type | Conference Paper (Published) |
---|---|
Conference Name | 13th International Conference on Construction in the 21st Century (CITC 13) |
Start Date | May 8, 2023 |
End Date | May 11, 2023 |
Acceptance Date | Mar 7, 2023 |
Online Publication Date | May 8, 2023 |
Publication Date | May 8, 2023 |
Deposit Date | Aug 14, 2023 |
Pages | 738-748 |
Book Title | Proceedings of the 13th International Conference on Construction in the 21st Century (CITC 13) |
ISBN | 9781732441644 |
Keywords | Computer vision, Project Management, Monitoring, Controlling, Artificial Intelligence, Performance, Productivity, Innovation, Automation |
Public URL | https://uwe-repository.worktribe.com/output/11024836 |
Publisher URL | https://www.citcglobal.com/ |
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Presentation / Conference Contribution
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