Advancing Task Guidance Systems: The ARGUS Framework for AI and ML-Assisted Augmented Reality
کلمات کلیدی:
ARGUS, Augmented Reality, Artificial Intelligence, Task Guidance, Context Recognition, Human-Computer Interaction, Reinforcement Learning, Adaptive Interfaces, Real-Time Systemsچکیده
This paper presents the ARGUS (Augmented Reality Guidance Using Smart-algorithms) framework, a pioneering system that integrates artificial intelligence (AI), machine learning (ML), and augmented reality (AR) to deliver adaptive, context-aware task guidance. Traditional guidance systems often lack flexibility and personalization; ARGUS addresses these limitations by incorporating multimodal perception, real-time decision-making, and reinforcement learning to personalize support and improve task performance. We detail its architecture—including the perception module, intelligence engine, visualization system, and user interface—and evaluate its effectiveness across industrial, healthcare, emergency response, and educational domains. Empirical results show up to 81% error reduction, 42% efficiency gains, and significant improvements in user satisfaction. This work underscores the transformative potential of intelligent AR guidance systems and highlights technical, ethical, and practical considerations for future development.
