## 6 Future Research Directions  
Our systematic review reveals significant opportunities for future research in the integration of VR, AI, and IoT technologies. While current implementations demonstrate considerable promise, there are still notable gaps in both the range of applications explored and the maturity of developed systems. Future research efforts should address these gaps while expanding into unexplored domains and tackling the challenges identified in this review. Research in AIoT, DTs, and XR technologies presents exciting possibilities for transforming various sectors. A key area for future investigation is the development of more advanced AI models capable of analyzing real-time data within AIoT systems, particularly focusing on their ability to learn from larger and continuously expanding datasets. Future systems could benefit from incorporating crowd intelligence to enhance both data collection and model training processes. Generative and agentic AI (LLMs) and conversational AI (Chatbots), will significantly improve human-computer interactions within DTs and XR environments by allowing for fast and easy generation of simulations, more intuitive communication and adaptive interaction. They will generate roles/agents playing in simulated environments, and natural responses employing various forms of feedback, such as verbal, visual, haptic and more. Generative AI will assist in XR by creating dynamic, context-aware simulation/virtual environments and objects that adapt to user behavior and real-world conditions captured through IoT sensors. Agentic AI will generate multi-agent systems for role-playing simulation. Such agents will autonomously and collaboratively perform complex tasks and alter environments (either virtual or real world ones) without being bound to user input. Instead, these systems will be continuously enhanced based on events and goal-driven decision making, demonstrating proactive behavior by analyzing sensor data. Furthermore, the introduction of FL in such systems, as well as PETs and decentralized architectures without a single point of failure has the potential to significantly enhance the security of future systems, bringing them closer to an acceptable threshold. Another crucial research direction lies in improving human-digital twin interactions within XR environments. This includes creating more natural interfaces for DT manipulation, implementing various interaction methods such as speech and gesture control, and developing feedback systems that engage multiple human senses while enhancing the realism of virtual environments. The development of dynamic ever-evolving DTs that can automatically update and adapt to real-time changes in their physical counterparts is also an interesting research direction. Attempting to also incorporate semantics for data homogenization and standardization will also be an important addition in future systems, making them more interoperable. Additionally, future work should aim to bridge the gap between theoretical advancements and real-world applications. Many proposed systems and theoretical frameworks currently face challenges in practical implementation. To address this, researchers should conduct long-term studies evaluating the impact of VR-AI-IoT systems on real-world users and communities. Collaboration with industry partners and public institutions will be essential for testing and implementing integrated solutions in real-world settings. Regarding specific application field directions, a promising one for future research on this synergistic technological approach is smart transportation and mobility. The potential for VR to simulate traffic patterns and enable teleoperation, AI to optimize route planning and facilitate MaaS (Mobility as a Service), and IoT to provide real-time vehicle data, could enhance urban mobility systems and create standardized mobility platforms.