Application of Intelligent Construction in Underground Space: Technical Integration and Field Overview

With the acceleration of urbanization, the development of underground space is evolving towards clustering. The high missed inspection rate and high operation and maintenance costs of traditional manual inspection highlight the urgency of intelligent transformation. This paper systematically organizes the existing technologies in the field of intelligent construction of underground space through literature analysis and case combing, covering technology chains and application scenarios, aiming to overview the development status of this field. The research finds that multi-modal perception networks can achieve multi-dimensional and accurate perception of the underground environment, and dynamic digital twin technology and AI modeling methods can break through the difficulties of modeling geological uncertainties. Intelligent control equipment can significantly improve construction efficiency. However, problems such as the lack of standardization of multi-source data, insufficient cross-scale modeling efficiency, and high costs of intelligent equipment restrict the large-scale application of technology. In the future, it is necessary to promote the transformation of underground engineering from experience-driven to data-intelligent-driven through paths such as interdisciplinary collaborative modeling, standard system construction, and data security guarantee. This research provides a reference for the current status of technologies for the intelligence of underground engineering, and has practical significance for optimizing the allocation of urban space resources and supporting the construction of new urbanization.