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Design and Implementation of the Transparent, Interpretable, and Multimodal (TIM) AR Personal Assistant.

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    We developed TIM, an AI-powered augmented reality system for task guidance. TIM provides adaptable, just-in-time feedback by understanding users and scenes, aiding in performance analysis and failure detection.

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    Area of Science:

    • Computer Science
    • Human-Computer Interaction
    • Artificial Intelligence

    Background:

    • Artificial intelligence (AI) assistants for task guidance are transitioning from concept to reality.
    • Complex systems require perceptual grounding, attention, reasoning, adaptive interfaces, and sensor data orchestration.
    • Posthoc analysis of system data is crucial for understanding user behavior and detecting failures.

    Purpose of the Study:

    • Introduce TIM, the first end-to-end AI-enabled task guidance system in augmented reality.
    • Address system challenges and propose design solutions for AI task guidance.
    • Demonstrate TIM's adaptability across diverse applications.

    Main Methods:

    • Developed an AI-enabled system for augmented reality task guidance.
    • Integrated user and scene detection capabilities.
    • Implemented adaptable, just-in-time feedback mechanisms.

    Main Results:

    • TIM successfully detects users and scenes within the augmented reality environment.
    • The system provides adaptive feedback tailored to user needs.
    • Demonstrated customization of TIM components for varied application requirements.

    Conclusions:

    • TIM represents a significant advancement in AI-enabled task guidance systems.
    • The system's adaptability and data analysis capabilities are key strengths.
    • TIM offers a flexible platform for various real-world applications.