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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).
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).
- Type: Journal Article
- Keywords: awkward working postures; deep learning; multimodal fusion; risk management; wearable sensors
- ISBN/ISSN: 0733-9364
- URL: http://doi.org/10.1061/JCEMD4.COENG-13795
- Abstract:
Developing approaches for recognition and classification of awkward working postures is of great significance for proactive management of safety risks and work-related musculoskeletal disorders (WMSDs) in construction. Previous efforts have concentrated on wearable sensors or computer vision-based monitoring. However, certain limitations need to be further investigated. First, wearable sensor-based studies lack reliability due to vulnerability to environmental interferences. Second, conventional computer vision-based recognition demonstrates classification inaccuracy under adverse environmental conditions, such as insufficient illumination and occlusion. To address the above limitations, this study presents an innovative and automated approach for recognizing and classifying awkward working postures. This approach leverages multimodal data collected from various sensors and apparatuses, allowing for a comprehensive analysis of different modalities. A feature-level fusion strategy is employed to train deep learning-based networks, including a multilayer perceptron (MLP), recurrent neural network (RNN), and long short-term memory (LSTM). Among these networks, the LSTM model achieves optimal performance, with an impressive accuracy of 99.6% and an F1-score of 99.7%. A comparison of metrics between single-modality and multimodal-fused training methods demonstrates that the incorporation of multimodal fusion significantly enhances the classification performance. Furthermore, the study examines the performance of the LSTM network under adverse environmental conditions. The accuracy of the model remains consistently above 90% in such conditions, indicating that the model's generalizability is enhanced through the multimodal fusion strategy. In conclusion, this study mainly contributes to the body of knowledge on proactive prevention for safety and health risks in the construction industry by offering an automated approach with excellent adaptability in adverse conditions. Moreover, this innovative attempt integrating diverse data through multimodal fusion may provide inspiration for future studies to achieve advancements.
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).