AN INTEGRATED COMPUTATIONAL APPROACH FOR AI-ASSISTED BIM ANALYTICS AND DIGITAL TWIN DEVELOPMENT

Date

2026-1-14

Author

Şahin, Nilsu

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Building Information Modeling (BIM) integrates geometric representations with structured spatial and functional data, enabling reuse in interactive and operational digital twin applications beyond design and construction. Existing BIM models can be incorporated into computational pipelines to support indoor navigation and emergency evacuation in complex facilities. This thesis introduces an integrated framework for AI-assisted BIM analytics and digital twin development. It shows how Revit-based BIM data can be transformed into a unified pipeline for spatial analysis, navigation, and human-centred interaction within a Unity-based environment. The workflow separates geometric representations from structured spatial data to enable real-time indoor pathfinding with the A* algorithm, while accounting for key physical constraints relevant to evacuation. A large language model (LLM) serves as an interaction layer, translating computed routes into natural-language navigation instructions and supporting context-aware user queries. The system provides real-time visualization and interaction via a Unity-based digital twin, enabling interactive testing and demonstrations. The framework supports both algorithmic and human-centred evaluation. Thirty participants completed user evaluations using the System Usability Scale (SUS) and the Usefulness, Satisfaction, and Ease of Use (USE) Questionnaire. Overall, the proposed approach offers a scalable solution for integrating BIM-based navigation, AI-driven interaction, and immersive digital twins for indoor and emergency-oriented applications.

Subject Keywords

Building Information Modeling (BIM), Digital Twin, Large Language Model (LLM), AI-assisted Spatial Analysis, Indoor Navigation and Emergency Evacuation

URI

https://hdl.handle.net/11511/118785

Collections

Graduate School of Informatics, Thesis