Integration of AI-Based Ergonomics in Early-Stage Building Design: A Framework for Enhancing Occupational Health in Construction Projects

Author(s)

Arlovia Acevedo Noboa ,

Download Full PDF Pages: 13-20 | Views: 4 | Downloads: 1 | DOI: 10.5281/zenodo.21909715

Volume 15 - July 2026 (07)

Abstract

This article presents a novel framework for incorporating artificial intelligence (AI) algorithms, specifically machine learning and computer vision, during the early design stages of architectural and engineering processes, aimed at predicting ergonomic risks in construction projects. [1] [7] [13].
Unlike existing approaches that consider ergonomics only during the construction or operational phases, this proposal moves prevention forward to the design stage, when spatial and functional decisions already have a direct impact on occupational health [4] [8] [9].
The system merges digital modeling with data mining tools applied to posture analysis, physical loads, and areas of potential ergonomic risk, integrating these into Building Information Modeling (BIM) platforms commonly used in construction [1] [7] [13]. The strategy also aims to prevent work-related accidents, injuries, and fatalities, thereby improving productivity and reducing costs in civil construction [11] [12].
It is flexible in its alignment with various international standards and scalable at a global level [6] [10]. This research contributes to a broader and more proactive vision of engineering design, in line with the principles of human and technological sustainability promoted by the Journal of Engineering, Design and Technology.

Keywords

Artificial Intelligence, Ergonomics, Early-Stage Design, Occupational Health, Construction Safety, Predictive Modeling

References

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