Journal of the Computational Structural Engineering Institute of Korea (한국전산구조공학회논문집)

Computational Structural Engineering Institute of Korea (한국전산구조공학회)
권호 표지
DOI QR코드

DOI QR Code

Development of Web-based Construction-Site-Safety-Management Platform Using Artificial Intelligence

인공지능을 이용한 웹기반 건축현장 안전관리 플랫폼 개발

  • Siuk Kim (Division of Architectural Engineering, Dankook University) ;
  • Eunseok Kim (Changsoft I&I) ;
  • Cheekyeong Kim (Division of Architectural Engineering, Dankook University)
  • Received : 2023.12.14
  • Accepted : 2023.12.27
  • Published : 2024.04.30
Download PDF
⟨ Previous Next ⟩

Abstract

In the fourth industrial-revolution era, the construction industry is transitioning from traditional methods to digital processes. This shift has been challenging owing to the industry's employment of diverse processes and extensive human resources, leading to a gradual adoption of digital technologies through trial and error. One critical area of focus is the safety management at construction sites, which is undergoing significant research and efforts towards digitization and automation. Despite these initiatives, recent statistics indicate a persistent occurrence of accidents and fatalities in construction sites. To address this issue, this study utilizes large-scale language-model artificial intelligence to analyze big data from a construction safety-management information network. The findings are integrated into on-site models, which incorporate real-time updates from detailed design models and are enriched with location information and spatial characteristics, for enhanced safety management. This research aims to develop a big-data-driven safety-management platform to bolster facility and worker safety by digitizing construction-site safety data. This platform can help prevent construction accidents and provide effective education for safety practices.

4차 산업혁명 시대에 건설산업은 전통적인 업무 방식에서 디지털 프로세스로 전환하고 있다. 특히, 건설산업의 특성으로 인해 업무 절차의 변경에는 어려움이 따르며, 점진적인 디지털 전환 및 시행착오가 발생하고 있다. 건설현장의 안전관리 분야도 역시 이 흐름을 따라 모든 데이터의 디지털화와 자동화를 목표로 연구 및 시도가 활발히 진행되고 있다. 그러나 최근의 통계에 따르면, 건설업 안전사고는 계속해서 발생하고 있으며, 안전사고 사망자 수도 줄지 않고 있다. 본 연구는 이러한 문제를 해결하기 위해 건설공사 안전관리 종합정보망의 빅데이터를 대규모 언어모델 인공지능을 통해 분석하였다. 분석된 결과는 실시간으로 업데이트가 가능한 상세설계모델로부터 위치정보와 공간적 특성을 반영하여 안전관리가 필요한 현장모델링에 정보를 맵핑하였다. 해당 연구를 통해 건설현장 안전관리 데이터의 디지털화를 통한 시설물 및 근로자의 안전을 강화하고, 건설사고 예방 및 효과적인 교육 지시를 위한 빅데이터 기반 안전관리 플랫폼 개발을 목표로 한다.

Keywords

Acknowledgement

본 연구는 국토교통부/국토교통과학기술진흥원의 2024년도 지원으로 수행되었음(과제번호 : RS-2021-KA163269).

References

  1. Albert, L., Routh, C. (2021) Designing Impactful Construction Safety Training Interventions, Safety, 7(2), p.42. 
  2. Cao, Q., Wang, H. (2021) Research on Digital Transformation of Construction Industry, In ICCREM 2021, pp.398~405. 
  3. Chen, X., Chang-Richards, A.Y., Pelosi, A., Jia, Y., Shen, X., S iddiqui, M.K., Yang, N. (2022) Implementation of Technologies in the Construction Industry: a Systematic Review. Engineering, Constr. & Archit. Manag., 29(8), pp.3181~3209. 
  4. Dwivedi, Y.K., Sharma, A., Rana, N.P., Giannakis, M., Goel, P., Dutot, V. (2023) Evolution of Artificial Intelligence Research in Technological Forecasting and Social Change: Research Topics, Trends, and Future Directions, Technol. Forecast. & Soc. Chang., 192, p.122579. 
  5. Joo, S.U., Kim, C.K., Kim, S.U., Noh, J.O. (2017) BIM-Based Quantity Takeoff and Cost Estimation Guidelines for Reinforced Concrete Structures, J. Comput. Struct. Eng. Inst. Korea, 30(6), pp.567~576.  https://doi.org/10.7734/COSEIK.2017.30.6.567
  6. Kim, C.K. (2023) Strategy and Technology for Digital Transformation of Design and Construction of RC Structures, J. Comput. Struct. Eng. Inst. Korea, 36(4), pp.265~272.  https://doi.org/10.7734/COSEIK.2023.36.4.265
  7. Lundberg, O., Nylen, D., Sandberg, J. (2022) Unpacking Construction Site Digitalization: The Role of Incongruence and Inconsistency in Technological Frames, Constr. Manag. & Econ., 40(11-12), pp.987~1002. 
  8. Na, S., Heo, S., Han, S., Shin, Y., Roh, Y. (2022) Acceptance Model of Artificial Intelligence (AI)-based Technologies in Construction Firms: Applying the Technology Acceptance Model (TAM) in Combination with the Technology-Organisation-Environment (TOE) Framework, Build., 12(2), p.90. 
  9. Sepasgozar, S.M., Khan, A.A., Smith, K., Romero, J.G., Shen, X., Shirowzhan, S., Tahmasebinia, F. (2023) BIM and Digital Twin for Developing Convergence Technologies as Future of Digital Construction, Build., 13(2), p.441.
  10. Shen, X. (2017) Location-based Leading Indicators in BIM for Construction Safety, University of Alabama Libraries, p.108. 
  11. Zhou, Z., Wei, L., Yuan, J., Cui, J., Zhang, Z., Zhuo, W., Lin, D. (2023) Construction Safety Management in the Data-Rich era: A Hybrid Review based upon Three Perspectives of Nature of Dataset, Machine Learning Approach, and Research Topic, Adv. Eng. Inform., 58, p.102144.