ArticleScientific reports2026
BIM-integrated carbon footprint assessment for sustainable buildings using real-time monitoring and optimization.
Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Abstract
The substantial contribution of the building sector to global carbon emissions highlights the limitations of conventional static assessment approaches and motivates the exploration of real-time, operation-oriented carbon management strategies. This study proposes and evaluates an integrated Building Information Modeling (BIM)-Internet of Things (IoT)-Artificial Intelligence (AI) framework for dynamic carbon footprint monitoring and operational optimization in green buildings. The proposed framework focuses on system-level integration and closed-loop decision support, rather than on the development of novel AI algorithms. A four-layer architecture is designed to integrate BIM-based static building information with IoT-driven real-time operational data, enabling continuous carbon assessment and multi-objective operational optimization. The framework was deployed over a 12-month period in a 15,000 m
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