The Roles of Artificial Intelligence in Reducing Carbon Emissions in the Construction Industry: China, Heibei
DOI:
https://doi.org/10.37934/araset.54.2.301316Keywords:
Artificial intelligence, carbon emissions, construction industry, life cycles, analytic hierarchy process, semi-structured interviewAbstract
Climate warming will have a profound impact on ecosystems, human society and economic development, so mitigating climate warming has become an important challenge facing the world. However, the construction industry is one of the important sources of global carbon emissions, and the use of digital technology had a revolutionary impact on the development of the construction industry. Artificial Intelligence plays an important role in digital technology, and its status and influence are further increasing. However, there is currently no comprehensive explanation of how Artificial Intelligence affects the construction industry’s carbon emissions. This study aims to explore the role of artificial intelligence on carbon emissions in the construction industry from multiple perspectives in the four life cycles of planning, design, operation & maintenance, and tear down. This study also to provide certain guidance for AI's participation in carbon reduction in the construction industry. The search of this study covers the three analysis dimensions of "efficiency improvement", "energy optimization" and "cost control", and analyses the contribution of Artificial Intelligence on carbon emissions in the construction industry by adopting mixed research methods. First, this study systematically analysed 85 publications collected in Scopus and Web of Science databases using PRISMA guidelines. Next, qualitative research method was used where semi-structured interview was use for data collection. Then Analytic Hierarchy Process was used to obtain the research results. Through research, the role of artificial intelligence in carbon reduction in the construction industry is further clarified, and the most obvious role of Artificial Intelligence in each life cycle is efficiency improvement. This research can provide reference and guidance for the use of AI in different life cycles.
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