Integrating augmented reality and LLM for enhanced cognitive support in critical audio communications
Year: 2024
Type: article
Abstract: Operation and Maintenance (O&M) missions are often time-sensitive and accuracy-dependent, requiring rapid and precise information processing in noisy, chaotic environments where oral communication can lead to cognitive overload and impaired decision-making. Augmented Reality (AR) and Large Language Models (LLMs) offer potential for enhancing situational awareness and lowering cognitive load by integrating digital visualizations with the physical world and improving dialogue management. However, synthesizing these technologies into a real-time system that effectively aids operators remains a challenge. This study explores the integration of AR and GPT-4, an advanced LLM, in time-sensitive O&M tasks, aiming to enhance situational awareness and manage cognitive load during oral communications. A customized AR system, incorporating the Microsoft HoloLens2 for cognitive monitoring and GPT-4 for decision making assistance, was tested in a human subject experiment with 30 participants. The 2×2 factorial experiment evaluated the effects of AR and LLM assistance on task performance and cognitive load. Results demonstrated significant improvements in task accuracy and reductions in cognitive load, highlighting the effectiveness of AR and LLM integration in supporting O&M missions. These findings emphasize the need for further research to optimize operational strategies in mission critical environments.
Authors: Fang Xu, Tianyu Zhou, Tri Nguyen, Haohui Bao, Christine Lin, Jing Du
Institution: University of Florida
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $3,790
OpenAlex ID: W4404055092