## 2 The Vision of IoPVT-Enabled Outdoor Health Monitoring
### Three-Dimensional Integration: Humans, Technology, and Environment  
A fundamental principle underlying this vision for IoPVT-enabled outdoor safety monitoring is the understanding that humans, technology, and the environment constitute an interdependent triad. To effectively monitor health and safety outside the four walls of buildings, we need to consider how these three pillars are connected, how they each shape the other and, ultimately, how they form the environment in which residents thrive or not. _Human_ individuals and communities whose well-being and safety the system aims to protect and enhance are the core of this three-dimensional integration. HAR serves as a critical element, focusing on identifying and interpreting movement patterns, behavior, and physiological signals [32]. By continuously monitoring individuals' activities, whether walking up an icy staircase in Montreal, commuting to work along rural roads, or navigating a coastal city's rising sea levels, the system gains insights into people's needs, vulnerabilities, and responses to their surroundings. In the long run, human-focused data lead to faster action depending on context, personalization, and more just safety policies that honor individual privacy and cultural environments. The _technological_ layer refers to tools, platforms, and analytic capabilities that enable proactive outdoor safety monitoring. This means not just physical sensors and devices implemented on the ground, for example, environmental monitors, wearable health sensors, and structural integrity gauges, but it also includes the underlying computing backbone [33, 34]. Edge nodes, fog computing platforms, and cloud-based analytics engines work together to aggregate data, process them efficiently, and transform raw inputs into actionable intelligence. This integrated dataset is extracted for patterns and anomalies by AI-driven algorithms and simulated in the Metaverse environment to visualize and simulate potential interventions [35]. This technology enablement layer should be designed to evolve, such as advances in hardware, newer AI techniques, and better communication networks, to make it more scalable, reliable, and resilient. The _environment_, which includes both built and natural surroundings, is complex due to the many factors that influence human health and safety [19, 36]. Urban landscapes might include complex infrastructure and seasonal risks. At the same time, rural communities can grapple with localized industrial or agricultural issues, and coastal areas have to deal with the impacts of climate change, such as flooding and heavy storms. The system embeds sensors in different terrains to track environmental conditions such as air quality, temperature, wind, precipitation, and structural integrity, mapping them in the Metaverse through the modeling of dynamic factors to holistically consider the awareness of environmental stressors [37]. This perspective guides risk evaluations and strengthens the formulation of context-sensitive risk reduction measures, ensuring that interventions are appropriately tailored to regional ecological and infrastructural contexts. Adaptability and improvement rely on continuous feedback loops across these three dimensions of integrated solutions [38]. Understanding human behavior helps decide where and how sensors might be placed or what predictive models to fine-tune. Environmental changes that stress new technological infrastructure require sensor placement adjustments, data fusion techniques, and analytical approaches. Technology, in turn, improves the quality, timeliness, and usefulness of data, allowing systems to meet human needs more effectively and adapt to changing environmental conditions. Adaptability through cyclical reinforcement means that the three elements remain in equilibrium with each other, with each one informing and refining the other. Framing outdoor safety monitoring as a synergy of humans, technology, and the environment lays the groundwork for a responsive, context-aware ecosystem.