TY - GEN
T1 - A Smart Cyber-Physical System Combining Large Language Models (LLMs) and Augmented Reality (AR) to Enhance Human Building Interaction during Building Operations and Maintenance Procedures
AU - Mohammadi, Mohsen
AU - Poudel, Oscar
AU - Assaad, Rayan H.
AU - Awada, Mohamad
AU - Assaf, Ghiwa
N1 - Publisher Copyright:
© ASCE.
PY - 2025
Y1 - 2025
N2 - The operation and maintenance of buildings are often time-sensitive and accuracy-dependent, requiring rapid and precise information processing. Oral communication supported by cognitive assistance can facilitate accurate decision-making, improving user experiences with building facilities and overall human-building interaction (HBI). This paper presents a novel cyber-physical system (CPS) integrating augmented reality (AR) and large language models (LLMs) to enable users to communicate orally with LLMs, providing guidance in diagnosing and resolving issues in building facilities, such as MEP or HVAC systems. The process involves converting user speech to text via custom libraries, transmitting the text to an LLM hosted on a web server through wireless communication, and displaying step-by-step guidance in the AR headset. Results demonstrated that the proposed CPS significantly improves user interaction with building facilities, enhancing situational awareness, task efficiency, and user satisfaction. This research introduces an innovative AR-LLM integration CPS that promotes a more engaging, personalized, and efficient HBI framework.
AB - The operation and maintenance of buildings are often time-sensitive and accuracy-dependent, requiring rapid and precise information processing. Oral communication supported by cognitive assistance can facilitate accurate decision-making, improving user experiences with building facilities and overall human-building interaction (HBI). This paper presents a novel cyber-physical system (CPS) integrating augmented reality (AR) and large language models (LLMs) to enable users to communicate orally with LLMs, providing guidance in diagnosing and resolving issues in building facilities, such as MEP or HVAC systems. The process involves converting user speech to text via custom libraries, transmitting the text to an LLM hosted on a web server through wireless communication, and displaying step-by-step guidance in the AR headset. Results demonstrated that the proposed CPS significantly improves user interaction with building facilities, enhancing situational awareness, task efficiency, and user satisfaction. This research introduces an innovative AR-LLM integration CPS that promotes a more engaging, personalized, and efficient HBI framework.
UR - https://www.scopus.com/pages/publications/105031154013
UR - https://www.scopus.com/pages/publications/105031154013#tab=citedBy
U2 - 10.1061/9780784486436.090
DO - 10.1061/9780784486436.090
M3 - Conference contribution
AN - SCOPUS:105031154013
T3 - Computing in Civil Engineering 2025: Computational and Intelligent Technologies - Selected Papers from the ASCE International Conference on Computing in Civil Engineering 2025
SP - 847
EP - 857
BT - Computing in Civil Engineering 2025
A2 - Jafari, Amirhosein
A2 - Zhu, Yimin
PB - American Society of Civil Engineers (ASCE)
T2 - ASCE International Conference on Computing in Civil Engineering, i3CE 2025
Y2 - 11 May 2025 through 14 May 2025
ER -