Risques physiques, mécaniques ou de sécurité
Lei, J., Yi, C., Hu, H., Qing, T., Kang, Y., Mi, Y., . . . Xu, H. (2026). Real-time fatigue monitoring using sEMG and HRV sensors for industrial operators under swing conditions. Sensors, 26(15). https://doi.org/10.3390/s26154761 
Mesfer, M., Matar, A., Saif, R., Saleh, A., Ahmed, I., Awawdeh, M. et Bashir, A. (2026). Design of intelligent embedded system for personal protective equipment detection and face recognition access control. IAES International Journal of Artificial Intelligence, 15(4), 3176-3188. http://doi.org/10.11591/ijai.v15.i4.pp3176-3188
Mostofi, F., Rouhikia, M., Tokdemir, O. B., Toğan, V. et Adeli, H. (2026). Emotionally intelligent construction safety monitoring via integration of machine learning and expert-informed electroencephalogram-related features. Journal of Civil Engineering and Management, 32(6), 769-784. https://doi.org/10.3846/jcem.2026.27817
Shi, J.-J., Zhang, Z.-X., Hu, Z.-H., Lu, J.-W., Ni, L.-L., Yuan, X.-J. et Huang, A.-C. (2026). Integrating CRITIC-VIKOR and XGBoost for intelligent risk assessment of hot work in a chemical industrial park. Journal of Loss Prevention in the Process Industries, 104, article 106157. https://doi.org/10.1016/j.jlp.2026.106157
Topolska, K., Woźniak, Z. et Hoła, B. (2026). Application of machine learning and deep learning methods for the prediction of near misses and occupational accidents in the construction industry. Archives of Civil and Mechanical Engineering, 26(5), article 244. https://doi.org/10.1007/s43452-026-01606-2
Wen, H. et Amin, T. (2026). Interpretable deep learning for risk representation: A risk model for construction safety. ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering, 12(4), article 04026060. https://doi.org/10.1061/AJRUA6.RUENG-1933
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