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Al-Bayati, A J, Eiris, R, Hernandez, G O and Al-Bayati, M A (2023) Addressing social inequity in construction safety research: Personal protective equipment focus. Journal of Construction Engineering and Management, 149(12).
Deep, S, Gajendran, T, Jefferies, M and Jha, K N (2023) Developing subcontractor-general contractor relationships in the construction industry: Constructs and scales for analytical decision making. Journal of Construction Engineering and Management, 149(12).
Gebretekle, Y T and Fayek, A R (2023) Fuzzy agent-based modeling of competency and performance measures in construction. Journal of Construction Engineering and Management, 149(12).
Hadi, A, Cheung, F, Adjei, S and Dulaimi, A (2023) Evaluation of lean off-site construction literature through the lens of industry 4.0 and 5.0. Journal of Construction Engineering and Management, 149(12).
Han, J and Huang, H (2023) Cooperative behavior, supervision, and contract choice in PPP projects: An evolutionary game theory approach incorporating an other-regarding preference. Journal of Construction Engineering and Management, 149(12).
Hu, Z, Chan, W T and Hu, H (2023) Personalized construction safety interventions considering cognitive-related factors. Journal of Construction Engineering and Management, 149(12).
Lai, X, Huang, J, Lin, S, Hu, C, Mao, N, Liu, J and Chen, Q (2023) Efficiency scoring for subway tunnel construction based on shield-focused big data and Gaussian broad learning system. Journal of Construction Engineering and Management, 149(12).
Li, M, Lin, Q and Jin, H (2023) Research on near-miss incidents monitoring and early warning system for building construction sites based on blockchain technology. Journal of Construction Engineering and Management, 149(12).
Ling, F Y Y, Heng, G T H, Chang-Richards, A, Chen, X and Yiu, T W (2023) Impact of digital technology adoption on the comparative advantage of architectural, engineering, and construction firms in Singapore. Journal of Construction Engineering and Management, 149(12).
Luo, X, Li, X, Song, X and Liu, Q (2023) Convolutional neural network algorithm-based novel automatic text classification framework for construction accident reports. Journal of Construction Engineering and Management, 149(12).
Moohialdin, A S M, Lamari, F, Miska, M and Trigunarsyah, B (2023) Proximity activity intensity identification system in hot and humid weather conditions: Development and implementation. Journal of Construction Engineering and Management, 149(12).
- Type: Journal Article
- Keywords: activity intensity identification; computer vision; construction site; hot and humid weather conditions; nonintrusive; real-time; safety; workers
- ISBN/ISSN: 0733-9364
- URL: http://doi.org/10.1061/JCEMD4.COENG-13332
- Abstract:
Construction workers are exposed to heat stress risks due to the combined effects of hot and humid weather conditions (HHWCs) and physically demanding work. A real-time activity intensity identification (AII) is required to measure the impact of HHWCs using a nonintrusive approach. This research developed a real-time AII system based on computer vision analysis (CVA). It then combined the CVA system with real-time video recordings to approximate workers' activity intensity (AI) levels alongside HHWC records. A fundamental activities matrix was developed to build a list of measurable and identifiable features of site activities. These features were used to identify and link different postures to a crew's AI and safety status within a given context. In real-site conditions, the AII system instantly and unobtrusively approximated workers' AI and safety status under HHWCs. The system showed high detection performance with competitive deployment time, cost, and effort, outperforming previous related models. The results showed that formwork and steelwork are mostly moderate activities; however, moderate AI and HHWCs can create heat stress and fatigue and significantly affect workers' safety, resulting in heat-related injuries and accidents. This research gives researchers and practitioners insight into the challenges associated with measurement methods and solving practical site measurement issues. This research promotes innovative methods for real-site measurements and contributes to knowledge in the field of safety and productivity in the construction industry by employing new, innovative CVA technology. This technology has applications in the industry by deploying a practical tool that could support aligned improvement in the safety and productivity of construction workers working under HHWCs. Practical Applications The challenges of automated and real-time measurements have always been of great interest to construction safety and productivity practitioners, particularly measurements of nonintrusive systems and competitive deployment time, cost, and effort. Such problems have also resulted in a substantial delay in making safety- and productivity-related decisions, which are major reasons for the increasing number of hot and humid weather-related injuries and incidents, particularly with the growing threat of global warming. Furthermore, under HHWCs, construction companies have also incurred significant productivity losses. This study offers an automated, nonintrusive, real-time measuring system with competitive deployment time, cost, and effort to monitor activity intensity and weather-related risks. Hence, site decision makers can make timely safety- and productivity-related decisions to improve work safety and productivity.
Mostofi, F and Toǧan, V (2023) A data-driven recommendation system for construction safety risk assessment. Journal of Construction Engineering and Management, 149(12).
Shi, L, He, Y and Onishi, M (2023) Effect of the internal agency problem on risk-sharing incentive contracts in public-private partnership projects. Journal of Construction Engineering and Management, 149(12).
Siddika, A and Lu, M (2023) Project schedule acceleration optimization integrated with energy source-based assessment of occupational health and safety risks. Journal of Construction Engineering and Management, 149(12).
Taghaddos, M, Pereira, E, Osorio-Sandoval, C, Hermann, U and Abourizk, S (2023) A data-driven approach for deploying safety policies for schedule planning in industrial construction projects: A case study. Journal of Construction Engineering and Management, 149(12).
Thekinen, J D, Pandey, N, Mollaoglu, S, Duva, M, Frank, K and Zhao, D (2023) Detecting information bottlenecks in architecture engineering construction projects for integrative project management. Journal of Construction Engineering and Management, 149(12).
Venkatesh, P and Ergan, S (2023) Classification of challenges in achieving BIM-based safety-requirement checking in vertical construction projects. Journal of Construction Engineering and Management, 149(12).
Xiahou, X, Li, Z, Xia, J, Zhou, Z and Li, Q (2023) A feature-level fusion-based multimodal analysis of recognition and classification of awkward working postures in construction. Journal of Construction Engineering and Management, 149(12).
Xu, Z, Guo, X, Zhao, Y and Liu, X (2023) Performance of CFRP-bolted timber joints with slotted-in corrugated steel plates. Journal of Construction Engineering and Management, 149(12).
Xue, Y, Le, Y, Zhang, X and Jiang, K (2023) Exploring schedule risks in large airport operational readiness: Risk identification and the systematic model. Journal of Construction Engineering and Management, 149(12).
Yang, J, Zhong, B, Gao, H and Wang, Y (2023) Task decomposition and service composition on an innovative blockchain-based construction service trading platform to select construction services. Journal of Construction Engineering and Management, 149(12).
Yi, W, Wang, H, Zhen, L and Liu, Y (2023) Automated generation of horizontal precast slab stacking plans. Journal of Construction Engineering and Management, 149(12).
Zhou, T, Xia, P, Ye, Y and Du, J (2023) Embodied robot teleoperation based on high-fidelity visual-haptic simulator: Pipe-fitting example. Journal of Construction Engineering and Management, 149(12).