Factors affecting implementation of computer vision-based technologies adopted for monitoring buildings construction projects

Abstract

Construction monitoring in dynamic construction site environments poses significant challenges for construction management. To overcome these challenges, the implementation of computer vision (CV) technologies for construction project monitoring has gained traction. This study focuses on investigating the factors influence the successful implementation of CV technologies in monitoring construction activities within building projects. A comprehensive methodology was employed, including a systematic review of CV technologies implemented in construction and qualitative surveys conducted with construction experts. Additionally, a quantitative questionnaire was developed, and the collected data was analysed using structural equation modelling. The findings reveal the presence of 10 factors categorized into four constructs. Notably, all 10 factors demonstrate high value factor loadings and statistical significance, and among the four constructs (device, jobsite, environment, human), device (0.82) has the highest impact on the implementation of CV-based technologies on the construction site, followed by jobsite condition (0.62), human (0.61), and environment (0.51) came in the last place. By addressing these influential factors and mitigating their effects, construction stakeholders can enhance the implementation of CV technologies for monitoring construction sites. This study contributes valuable insights that inform the implementation and optimization of CV technologies in construction projects, ultimately advancing the field of construction management.