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Observational analysis reveals automated data processing for construction projects, suggesting better alignment with SDGs and ESG.
As sustainable development is gaining more and more attention, the construction industry continues to explore this aspect. Both Sustainable Development Goals (SDGs) and Environmental, Social and Governance (ESG) provide management goals for corporate sustainable development and assessment. However, due to the complexity of construction events and multiple data sources, sustainable development management in the construction industry is still hindered by the need for a large amount of labor costs. Therefore, this paper proposes an LLM-based sustainable development data processing framework for construction, which achieves three goals: (1) identifying indicators of SDGs and ESG assessment frameworks for construction projects, (2) mapping sustainable development indicators to construction events and data, and (3) developing an LLM-based localized data processing framework for construction sustainability. The proposed method can achieve rapid data processing of construction projects and provide information and information sources related to sustainable development goals. It realizes automated report generation or correlation traceability of sustainable development in construction projects.
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Gong et al. (2025) studied this question.
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