AI-Driven Digital Twin Framework for Smart Building Automation and User-Centred Renovation

Description

The global trend of urbanization coupled with resource scarcity has emphasized the need for innovative solutions to improve building automation. This research explores how Digital Twin (DT) technology enhanced with Artificial Intelligence (AI) can provide real-time simulations and predictive models for more efficient building automatic control systems. Leveraging a combination of building information modelling (BIM) deep learning and game-engine technology the research creates a dynamic and participatory renovation framework. Wearable sensors and environmental sensors are used to collect personal thermal comfort data and environmental conditions. This information is used within a Digital Twin platform to predict human needs and automatically control building facilities ensuring the indoor environment meets every user’s requirement. By investigating AI’s role in optimizing renovation processes and stakeholder engagement the study enhances the lifecycle performance of buildings while promoting sustainability data security human comfort and overall renovation quality.

Period	1 Mar 2025 → …
Examinee	Yixuan Wang
Examination held at
Degree of Recognition	International