Exploring Vision-Based Technologies for Ergonomic Training in Construction Education

ORCID

Rokooei: https://orcid.org/0000-0001-8543-653X

MSU Affiliation

College of Architecture, Art and Design; Department of Building Construction Science

Creation Date

2026-10-30

Abstract

Musculoskeletal disorders (MSDs) are a critical concern in construction, frequently caused by repetitive motions, awkward postures, and heavy lifting. These risks are prevalent not only in industry but also in educational settings where students engage in handson tasks that mirror real-world conditions. This study investigates the integration of vision-based technologies, specifically Snapshot Ergonomics, into construction education to assess and address ergonomic risks. Snapshot Ergonomics uses video-based motion capture, artificial intelligence (AI), and machine learning (ML) to classify postures as Safe, Cautious, or Hazardous. Three key fabrication activities – wood framing, steel welding, and cladding/finishing – were analyzed with a sample size of nine participants across distinct task variations. Results revealed that neck and elbow postures frequently exhibited hazardous positions, emphasizing the need for ergonomic interventions. This paper discusses the feasibility, scalability, and implications of these tools in improving safety education, ultimately fostering a proactive safety culture in construction.

Keywords

construction, ergonomic, musculoskeletal disorders, posture

Publication Date

7-19-2025

Publication Title

Proceedings of the 10th International Conference on Civil, Structural and Transportation Engineering (ICCSTE 2025)

Publisher

International Academy of Science, Engineering and Technology

Rights

© Copyright 2025, International ASET Inc. – All rights reserved

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Digital Object Identifier (DOI)

https://doi.org/10.11159/iccste25.284