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In recent years, the use of Digital Twin (DT) technology has grown steadily to maintain high Indoor Environmental Quality (IEQ) while improving energy efficiency in buildings. However, the majority of studies still address these domains in parallel with limited real-time integration, multi-IEQ coverage or user-centred feedback loops. This paper performs a combined scientometric and thematic review of 109 peer-reviewed studies (2016–2025), retrieved from Scopus and Web of Science, following PRISMA methodology to map the conceptual evolution and methodological progress of IEQ-energy DT research field. Scientometric analysis reveals publication trends, co-citation and co-occurrence patterns and conceptual evolution using VOSviewer, while structured content analysis refines these insights into four main thematic clusters: (1) IEQ Monitoring through IoT Sensing, (2) IEQ and Energy Balance, (3) Digital Twin Frameworks and Applications, and (4) Control Actions. Together, these analyses indicate a technologically advanced but operationally fragmented field: IEQ modelling remains largely thermal-centric, feedback loops are incomplete, and real-time co-optimization is rarely validated beyond single-site pilots. Building on these findings, the study proposes a multi-layer conceptual framework that integrates data acquisition, hybrid modelling, semantic integration, and multi-objective control into a continuous adaptive loop. The framework operationalizes comfort-energy balance as a measurable, feedback-enabled condition, supporting the transition of DTs from static monitoring tools to self-learning and occupant-responsive systems. Overall, the study provides consolidated evidence and a forward-looking roadmap for interoperable and human-centered DTs capable of the dynamic regulation of IEQ and energy performance in smart and sustainable buildings.
Ageli et al. (Sat,) studied this question.