The Roles of Artificial Intelligence in Reducing Carbon Emissions in the Construction Industry: China, Heibei

Authors

  • Jiachen Sun School of Housing, Building and Planning, Universiti Sains Malaysia, 11700 Gelugor, Pulau Pinang, Malaysia
  • Terh Jing Khoo School of Housing, Building and Planning, Universiti Sains Malaysia, 11700 Gelugor, Pulau Pinang, Malaysia
  • Atasya Osmadi School of Housing, Building and Planning, Universiti Sains Malaysia, 11700 Gelugor, Pulau Pinang, Malaysia
  • Deng Bin School of Housing, Building and Planning, Universiti Sains Malaysia, 11700 Gelugor, Pulau Pinang, Malaysia
  • Shihua Lu School of Housing, Building and Planning, Universiti Sains Malaysia, 11700 Gelugor, Pulau Pinang, Malaysia
  • Xiaolu Zhang 33rd F, CSCEC Science and Industry Corporation Ltd., No. 3331 Zhongxin Road, Yuehai Street, Nanshan District, Shenzhen, Guangdong, China

DOI:

https://doi.org/10.37934/araset.54.2.301316

Keywords:

Artificial intelligence, carbon emissions, construction industry, life cycles, analytic hierarchy process, semi-structured interview

Abstract

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.

Downloads

Author Biographies

Jiachen Sun, School of Housing, Building and Planning, Universiti Sains Malaysia, 11700 Gelugor, Pulau Pinang, Malaysia

sunjiachen@student.usm.my

Terh Jing Khoo, School of Housing, Building and Planning, Universiti Sains Malaysia, 11700 Gelugor, Pulau Pinang, Malaysia

terhjing@usm.my

Atasya Osmadi, School of Housing, Building and Planning, Universiti Sains Malaysia, 11700 Gelugor, Pulau Pinang, Malaysia

a.osmadi@usm.my

Deng Bin, School of Housing, Building and Planning, Universiti Sains Malaysia, 11700 Gelugor, Pulau Pinang, Malaysia

sjhxlmy@163.com

Shihua Lu, School of Housing, Building and Planning, Universiti Sains Malaysia, 11700 Gelugor, Pulau Pinang, Malaysia

luwas55555@gmail.com

Xiaolu Zhang, 33rd F, CSCEC Science and Industry Corporation Ltd., No. 3331 Zhongxin Road, Yuehai Street, Nanshan District, Shenzhen, Guangdong, China

971824580@qq.com

Downloads

Published

2025-01-09

How to Cite

Sun, J., Khoo, T. J., Osmadi, A., Bin, D., Lu, S., & Zhang, X. (2025). The Roles of Artificial Intelligence in Reducing Carbon Emissions in the Construction Industry: China, Heibei. Journal of Advanced Research in Applied Sciences and Engineering Technology, 54(2), 301–316. https://doi.org/10.37934/araset.54.2.301316

Issue

Section

Articles

Similar Articles

1 2 3 4 5 6 7 8 9 10 > >> 

You may also start an advanced similarity search for this article.