TY - GEN
T1 - Digital Twin-Based Health Maps for Construction Worker Health Monitoring
T2 - ASCE International Conference on Computing in Civil Engineering 2023: Resilience, Safety, and Sustainability, i3CE 2023
AU - Shayesteh, Shayan
AU - Jebelli, Houtan
AU - Messner, John
N1 - The work presented in this paper was supported financially by a National Science Foundation Award (No. ECCS-2222654). Any opinions, findings, conclusions, or recommendations expressed in this paper are those of the authors and do not necessarily reflect the views of the National Science Foundation.
PY - 2024
Y1 - 2024
N2 - The construction industry is known for its disproportionately high fatality and injury rates, making it one of the most hazardous industries in the US. Despite the significant risks involved, there is a lack of effective health monitoring in construction jobsites. While wearable physiological sensing and artificial intelligence advancements have introduced unique opportunities to assess workers' health status, there are still inefficiencies in representing that information to support managers' decision-making. Recently, the concept of digital twin (DT) has been used in various construction applications. Given the exponential growth of its enabling technologies, DT has great potential to transform worker health monitoring in construction jobsites. Therefore, this research investigates the feasibility of integrating workers' physiological responses with DT technology to generate health maps that deliver workers' aggregated health information to managers to reinforce their decision-making. The DT-based health maps are expected to enhance workers' occupational health and safety at construction jobsites.
AB - The construction industry is known for its disproportionately high fatality and injury rates, making it one of the most hazardous industries in the US. Despite the significant risks involved, there is a lack of effective health monitoring in construction jobsites. While wearable physiological sensing and artificial intelligence advancements have introduced unique opportunities to assess workers' health status, there are still inefficiencies in representing that information to support managers' decision-making. Recently, the concept of digital twin (DT) has been used in various construction applications. Given the exponential growth of its enabling technologies, DT has great potential to transform worker health monitoring in construction jobsites. Therefore, this research investigates the feasibility of integrating workers' physiological responses with DT technology to generate health maps that deliver workers' aggregated health information to managers to reinforce their decision-making. The DT-based health maps are expected to enhance workers' occupational health and safety at construction jobsites.
UR - https://www.scopus.com/pages/publications/85184098932
UR - https://www.scopus.com/inward/citedby.url?scp=85184098932&partnerID=8YFLogxK
U2 - 10.1061/9780784485248.059
DO - 10.1061/9780784485248.059
M3 - Conference contribution
AN - SCOPUS:85184098932
T3 - Computing in Civil Engineering 2023: Resilience, Safety, and Sustainability - Selected Papers from the ASCE International Conference on Computing in Civil Engineering 2023
SP - 492
EP - 499
BT - Computing in Civil Engineering 2023
A2 - Turkan, Yelda
A2 - Louis, Joseph
A2 - Leite, Fernanda
A2 - Ergan, Semiha
PB - American Society of Civil Engineers
Y2 - 25 June 2023 through 28 June 2023
ER -