AI and AI-powered digital twins for smart, green, and zero-energy buildings: A systematic review of leading-edge solutions for advancing environmental sustainability goals.

Combining artificial intelligence (AI) with digital‑twin technology is changing how we design smart, green, and zero‑energy buildings. This research area gives a clear way to assess the newest computer tools that aim to improve environmental sustainability. By pulling together methods from recent studies, the framework helps you review and plan the use of AI‑based prediction models, real‑time thermal‑comfort control, and automated energy‑management systems. It looks at linking Building Information Modeling (BIM) with live sensor networks to create detailed virtual copies of buildings that can predict energy use, indoor air quality, and carbon emissions. The work also discusses major hurdles such as making data from different sources work together, integrating sensors,

and scaling algorithms for many climate zones. This document acts as a full‑featured guide for organizing research on intelligent building controls. It offers step‑by‑step procedures to simulate building performance, assess decarbonization options, and set solid benchmarks for meeting net‑zero energy targets in today’s cities. Using this approach, researchers can compare the cost of more complex calculations with the energy savings they provide.

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