Research on the Application of BIM and Digital Twin-Based Artificial Intelligence Technologies in the Full Lifecycle of Building Construction

2Citations
Citations of this article
25Readers
Mendeley users who have this article in their library.
Get full text

Abstract

The emergence of new quality productive forces has served as robust impetus for the transformation and upgrading of the construction industry. To systematically investigate the synergistic effects arising from the integration of artificial intelligence (AI) with construction practices, this study categorizes AI applications into three phases: design, construction, and operation and maintenance (O&M). In the design phase, Building Information Modeling (BIM) and generative AI are synergistically employed to optimize architectural solutions. During the construction phase, intelligent construction robots, 5G-enabled tower cranes and other automated equipments are integrated with BIM and Augmented Reality (AR) platforms. This combination increases managerial and operational efficiency. For the O&M phase, a digital twin platform supported by Internet of Things (IoT) networks and AI-driven predictive analytics enables preventive equipment maintenance and energy consumption optimization. Taking Xiong’an New Area as a representative case study, this research demonstrates that the symbiotic integration of AI technologies with construction substantial improvements across project lifecycles, operational efficiency, and safety performance. These advancements provide both practical evidence and technical pathways to support future urban renewal initiatives.

Author supplied keywords

Cite

CITATION STYLE

APA

Xiao, B., Xu, F., Yan, Z., Zhang, J., & Zhu, S. (2025). Research on the Application of BIM and Digital Twin-Based Artificial Intelligence Technologies in the Full Lifecycle of Building Construction. In Proceedings of 2025 International Conference on Smart City and Sustainable Development, SCSD 2025 (pp. 118–122). Association for Computing Machinery, Inc. https://doi.org/10.1145/3747012.3747033

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free