Digital Transformation of Construction Site Safety Management: Technologies, Framework, and Practices

DOI: https://doi.org/10.62517/jsse.202608306

Author(s)

Rui Li

Affiliation(s)

Zibo Polytechnic University, Zibo, Shandong, China

Abstract

Construction sites remain among the most hazardous working environments, with falls, struck-by incidents, and equipment-related accidents causing persistent casualties worldwide. Conventional safety management relies heavily on manual inspection, paper-based records, and reactive correction, which limits timely hazard detection and weakens preventive capacity. This paper examines the digital transformation of construction site safety management through the integration of building information modelling, Internet of Things sensing, computer vision, and digital twin platforms. It reviews how these technologies shift site safety from after-the-event response to continuous, data-driven prevention. A four-layer implementation framework is proposed, covering data acquisition, transmission, analytics, and decision support, and is illustrated with representative applications such as automated personal protective equipment compliance checking and real-time hazard zone monitoring. The analysis shows that digital safety systems improve hazard identification accuracy, shorten warning latency, and support evidence-based supervision, while challenges related to data interoperability, deployment cost, and worker acceptance require structured safeguards. The study contributes a practical roadmap for contractors seeking to upgrade safety governance with measurable, scalable digital tools.

Keywords

Digital Transformation; Construction Safety; Building Information Modelling; Internet of Things; Computer Vision; Safety Management

References

[1] Rodrigues, F., Baptista, J. S., & Pinto, D. BIM approach in construction safety - A case study on preventing falls from height. Buildings, 2022, 12(1): 73. https://doi.org/10.3390/buildings12010073 [2] Rafindadi, A. D., Shafiq, N., & Othman, I. A conceptual framework for BIM process flow to mitigate the causes of fall-related accidents at the design stage. Sustainability, 2022, 14(20): 13025. https://doi.org/10.3390/su142013025 [3] Tariq, A., Ali, B., Ullah, F., & Alqahtani, F. K. Reducing falls from heights through BIM: A dedicated system for visualizing safety standards. Buildings, 2023, 13(3): 671. https://doi.org/10.3390/buildings13030671 [4] Riaz, M., He, J., Xie, K., Alsagri, H. S., Moqurrab, S. A., Alhakbani, H. A. A., & Obidallah, W. J. Enhancing workplace safety: PPE_Swin - A robust Swin Transformer approach for automated personal protective equipment detection. Electronics, 2023, 12(22): 4675. https://doi.org/10.3390/electronics12224675 [5] Tözer, K. D., Gürcanlı, G. E., Çelik, T., & Akboğa Kale, Ö. Safer designs with BIM based fall hazards identification and accident prevention. Safety Science, 2024, 169: 106346. https://doi.org/10.1016/j.ssci.2023.106346 [6] Elesawy, A., Abdelkader, E. M., & Osman, H. A detailed comparative analysis of You Only Look Once-based architectures for the detection of personal protective equipment on construction sites. Eng, 2024, 5(1): 347-366. https://doi.org/10.3390/eng5010019 [7] Luo, Q., Sun, C., Li, Y., Qi, Z., & Zhang, G. Applications of digital twin technology in construction safety risk management: A literature review. Engineering, Construction and Architectural Management, 2024, 32(6): 3587-3607. https://doi.org/10.1108/ECAM-11-2023-1095 [8] Ellul, C., Hamilton, N., Pieri, A., & Floros, G. Exploring data for construction digital twins: Building health and safety and progress monitoring twins using the Unreal Gaming Engine. Buildings, 2024, 14(7): 2216. https://doi.org/10.3390/buildings14072216 [9] Al-Khiami, M. I., & ElHadad, M. M. Enhancing construction site safety using AI: The development of a custom YOLOV8 model for PPE compliance detection. In Proceedings of the 2024 European Conference on Computing in Construction (pp. 577-584). https://doi.org/10.35490/EC3.2024.307 [10] Williams, T., Wong, C., Dobos, J., Martinez, P., & Kassem, M. Digital twin for safety on construction sites: A real-time risk monitoring system combining wearable sensors and 4D BIM. In Proceedings of the 2024 European Conference on Computing in Construction. https://doi.org/10.35490/EC3.2024.252