From BIM to Intelligent Buildings: An AI-Enabled Digital Twin for Real-Time Environmental Monitoring and Control

The transition from Building Information Modelling (BIM) to intelligent building operation requires digital systems that can connect design data with real-time environmental intelligence. An AI-enabled digital twin framework is presented that integrates BIM, Internet of Things (IoT), cloud analytics, and a game-engine environment to support real-time monitoring and comfort-oriented decision support. The system links building geome-try with live sensor streams and AI-driven prediction to visualize indoor conditions and generate adaptive environmental control parameters. An Ar-duino-based IoT prototype was deployed in office spaces to capture temper-ature and humidity data, which were transmitted to a cloud platform for AI-supported analysis and synchronized with a Unity-based DT. The case study illustrates how the framework facilitates continuous feedback between physical spaces and their digital counterparts, enabling responsive build-ing operations and human–AI collaboration. The results indicate that the approach demonstrates interoperability and practical feasibility in bridging design and operation, offering a practical pathway from BIM-centered repre-sentation toward intelligent, data-driven building environments.