## 4 Results and Discussions
### Applications in Occupational Health and Safety in Manufacturing
#### 4.2.1 Continuous Monitoring and Risk Prediction  
Advanced emerging technologies are revolutionizing continuous monitoring and risk prediction in workplace safety and ergonomics. These include DTs, AI, big data analytics, wearable technologies and sensors, and immersive technologies. As detailed in Table 6, these technologies offer comprehensive solutions for improving worker well-being, enhancing safety, and optimizing workplace design through continuous monitoring and risk prediction. \begin{table}
\begin{tabular}{p{113.8 pt} p{113.8 pt} p{113.8 pt} p{113.8 pt}} \hline \hline
**Technology** & **Key Applications for Continuous Monitoring and Risk Prediction** & **Benefits** & **References** \\ \hline  & & - & More precise and comprehensive risk assessment & \\  & Comprehensive ergonomic and safety assessment and prediction: & - & Improved efficiency in workplace planning and design & \\ DTs & Monitoring worker movements and WMSDs risks, simulating human activities in virtual environments for ergonomic analysis & - & Real-time insights into worker well-being and system status & [3; 9; 13; 19; 22; 5; 43; 46; 62; 63; 64; 65; 66; 67; 68; 69; 70; 71; 72; 73; 74; 75; 76; 77; 78; 79; 80; 81; 82; 83; 84; 85; 86; 87; 88; 89; 90; 91; 9  
DTs play a central role in enhancing workplace risk management by improving both safety and effectiveness. As indicated in Table 6, DTs are continuously updated with real-time data to provide enhanced safety monitoring and visualization. DTs, when integrated with IoT and sensor technologies, enable the continuous monitoring of human posture and ergonomic stressors to predict musculoskeletal risks. For example, DTs support comprehensive ergonomic and safety assessments by monitoring worker movements and WMSD risks, often integrating with digital exoskeleton models [79], which enhance workplace accessibility and human-machine collaboration. Similarly, human DTs are crucial for ergonomic assessments, simulating human activities to reduce fatigue and workload, and monitoring, optimizing, and predicting processes for human well-being. AI and multi-source data further enhance these models by enabling real-time simulation and assessment of worker \begin{table}
\begin{tabular}{p{113.8 pt} p{113.8 pt} p{113.8 pt} p{113.8 pt}} \hline \hline
**Technology** & **Key Applications for Continuous Monitoring and Risk Prediction** & **Benefits** & **References** \\ \hline \hline \multirow{6}{*}{AI \& Big Data Analytics} & \multirow{6}{*}{Intelligent hazard identification and predictive safety management: Analyzing vast data for risk evaluation, predicting equipment failures, understanding human emotions for mental health support, and indentifying environmental threats (e.g., noise, hazardous gases) for proactive intervention.} & - Automation of risk detection and alerts - Proactive mental health support and intervention - Enhanced predictive capabilities for equipment maintenance and incident prevention & [4, 6, 7, 8, 16, 18, 19, 46, 76] \\  & & & \\ \cline{1-1}  & & & \\ \cline{1-1}  & & & \\ \cline{1-1}  & & & \\ \cline{1-1}  & & & \\ \hline \hline \end{tabular}
\end{table} 
Table 6: _Cont._movements. For example, this integrated approach enables proactive safety interventions, triggering preventive actions to assist workers during emergencies [53]. Moreover, DTs also contribute to workplace design, product and process improvement, and reduction of WMSDs and stress by predicting fatigue and suggesting timely actions. This reflects a shift from reactive compliance to anticipatory safety, aligned with the Safety 4.0 framework. Additionally, integrating DT-based live monitoring with AR-powered notifications significantly improves process safety and enhances hazard prevention. AI-based algorithms and big data analytics are pivotal for intelligent hazard identification and in predictive safety management. Big data enables real-time OSH monitoring through continuous data collection and processing and helps organizations track safety performance and make informed decisions to prevent accidents.