Abstract

This dissertation explores the potential of AI-generated notes in supporting design communication and knowledge management within the Building Information Modelling (BIM) workflow. By comparing human-generated notes with AI-generated notes for both structured presentations and unstructured panel discussions, the study provides insights into the effectiveness of current AI models in capturing and summarizing design-related information. The findings highlight the strengths and limitations of AI-generated notes and identify key areas for improvement, including the need for better contextual understanding, the capture of emotional and subjective content, integration with visual elements, personalization options, continuous learning and adaptation, and seamless integration with BIM and knowledge management systems. The dissertation emphasizes the importance of AI-generated notes in facilitating better communication, collaboration, and knowledge sharing among project stakeholders and discusses the potential for AI to revolutionize the way design information is captured, managed, and utilized in the Architecture, Engineering, and Construction (AEC) industry.

Engineering and Architectural Design MEng

2020-24

Comparing Subjective Importance

Comparing Summary Lengths

Comparing AI Models

Comparing Subjective Importance