Research on BIM-Based Intelligent Construction System Integration and Its Application in Civil Engineering

This paper introduces the core role of BIM technology in intelligent construction systems, and analyzes its information flow, collaborative work and data visualization functions in the project life cycle. Then, an integrated model based on the K-means clustering algorithm is proposed to optimize resource scheduling and task allocation during the construction process. By clustering data from different construction scenarios, the model can automatically identify and optimize resource allocation, improve construction efficiency and project progress. Again, this paper constructs a multi-dimensional algorithm framework, covering key steps such as data preprocessing, feature extraction, and cluster analysis. Through simulation experiments, the application effect of the integrated system in actual civil engineering is evaluated. The experimental results show that the K-means clustering algorithm can effectively improve the accuracy and real-time performance of resource allocation, significantly reduce resource waste during construction, optimize construction progress, and the model has good robustness and adaptability. The data analysis results also prove the wide applicability of the system in different construction site environments.