Construction of building design carbon emission factor database driven by big data and implementation of intelligent statistical software

This article focuses on the urgent need for carbon emission management throughout the entire lifecycle of construction projects under the background of the "dual carbon" strategy. It systematically explores the development path of building design carbon emission factor database construction and intelligent statistical software platform based on big data-driven approaches. At present, the construction industry has implicit carbon emissions throughout all stages, but the society still lacks sufficient attention to its emission reduction, and lacks continuous, accurate, and intelligent monitoring methods. To this end, this article integrates big data technology and introduces machine learning (ML) algorithms to construct a construction project carbon neutrality monitoring and management platform that integrates automatic carbon emission accounting, dynamic monitoring, intelligent warning, and data management. The platform architecture covers the data layer, algorithm layer, application layer, and interaction layer, supports multi-source heterogeneous data access, and realizes the visualization tracking and intelligent analysis of carbon footprint from design to demolition. The results indicate that the platform operates stably in multiple actual construction projects, significantly improving the efficiency of carbon data collection and decision support capabilities. This study provides practical technical tools for the low-carbon transformation of the construction industry.