## 4 Results and Discussions
### Emerging Digital Technologies
#### 4.1.8 Integration of Digital Technologies for Creating Advanced Digital Ecosystem
COBOTS are interconnected with all major components (IoT, AI, CPS, DTs, and immersive technologies) to enable intelligent, safe, and ergonomic collaborations. They rely on AI and big data for intelligent and safe operation and can be monitored and controlled remotely in immersive virtual environments. IoT, sensors, and MoCap feed real-time data into DTs to support COBOTS. CPS integrates physical and digital systems, linking both DTs and COBOTS. Moreover, the immersive layer also visualizes HRC scenarios, simulates adjustments, and provides AR/VR guidance to human workers, enhancing situational awareness and decision-making. Figure 13: An advanced digital ecosystem for enhancing OHS in manufacturing. This conceptual diagram integrates DTs, IM, immersive interfaces, COBOTS, and other enabling technologies, including IoT, sensors, AI, big data analytics, MoCap, and CPS. Arrows indicate the dynamic data flow and interaction between the components, which support predictive safety, immersive training, and human-centric design. The arrows in Figure 13 illustrate the flow of data, influences, and interactions between the key components of the DT-based IM ecosystem. For instance, arrows flowing into the DT represent real-time input sources such as IoT, sensors, MoCap, AI, big data analytics, and CPS, which feed real-time data and intelligence into the DT. The feeding of real-time data aids in the simulation and monitoring of the environment. Similarly, the arrows from DT to IM show that DT is a foundational building block of the IM and indicate how DTs enable the construction of immersive spaces, contributing digital intelligence to the IM. Likewise, arrows into the IM represent technologies like immersive technologies, AI, and big data analytics that enable interaction and functionality within the metaverse. For instance, the arrows from AI and big data to DT and IM reflect their roles in real-time analytics and predictive modeling. Furthermore, bidirectional arrows with COBOTS indicate interactive feedback loops. For example, bidirectional arrows with COBOTS reflect their dual role of receiving real-time input for adaptive behavior and feeding back performance data to the DT and AI layers. These interactions enable COBOTS to operate safely, intelligently, and collaboratively with other components and humans. For instance, in IM, COBOTS can be monitored and controlled remotely using immersive virtual environments. Similarly, bidirectional arrows from and into immersive interfaces such as VR and AR support interaction in both directions. They function as two-way communication, that is, both input mechanisms (for training actions or commands) and output channels (for visualizations and scenario feedback), helping connect the physical and virtual worlds. From an OHS perspective, this digital ecosystem fosters a proactive and predictive environment. It supports hazard prediction and prevention, immersive safety training, real-time monitoring, ergonomic optimization, and continuous improvement of safety protocols, ultimately transforming manufacturing safety into a dynamic and data-driven process. In short, the arrows map the ecosystem's interdependencies, showing how data flows, technologies interact, and systems co-evolve to support a smart, immersive, and human-centric industrial environment from an Industry 5.0 perspective, addressing RQ1, RQ2, and RQ3. The integration of DT, IM, and enabling technologies into an interconnected and unified digital safety ecosystem represents the central contribution of this study. As shown in Figure 13, each technology plays a distinct and synergistic role in facilitating immersive training, ergonomic design, hazard forecasting, and collaborative safety. These technologies form an integrated safety system in which human data continuously shapes machine behavior in real time. This holistic framework (integrated approach) advances beyond siloed applications by enabling real-time, human-centered decision-making in smart manufacturing environments.