The Application of BIM Technology in Achieving a Balance between Greenness and Efficiency in H-Speed Rail Construction

Zhihao Lu

doi:10.54097/tnq9p264

Authors

Zhihao Lu SWJTU-Leeds Joint School, Southwest Jiaotong University, 611756 Chengdu, China

DOI:

https://doi.org/10.54097/tnq9p264

Keywords:

BIM; high-speed railway; integrated technology system; green construction; environmental monitoring.

Abstract

This research is centered on BIM technology. By analyzing the technical gaps of typical cases such as the Anjiu Railway project, and drawing on the experience of prefabricated buildings and water conservancy projects, three integrated technology systems have been constructed: BIM + GIS + IoT / NB-IoT is used for long-distance environmental monitoring; BIM + intelligent bridge erection machine + RFID + InSAR is used for bridge settlement control; BIM + intelligent TBM + TSP is used for safe tunnel excavation. The research shows that the integrated technology system can break through information barriers and achieve real-time environmental monitoring and dynamic optimization of construction, ensuring efficiency while reducing ecological disturbance. Regarding the limitations of standardization and cost in technology promotion, in the future, green efficiency evaluation indicators should be constructed and the application of technology modules should be promoted, providing theoretical and practical support for green construction of high-speed railways.

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References

[1] G.S. Guo, C. Zhu, R.C. Mao, X.D. Li, Y.K. Wu, J. Chen, decarbonizing high-speed rail infrastructure in China: An integrated assessment combining machine learning and scenario modeling to 2060, Energy. 341, 139478 (2025). https://doi.org/10.1016/j.energy.2025.139478

[2] A. M. Nagayo, R. Singh, A. Dhawan, T. C. Manjunath, A. Qasem, K.C. Sethi, K. Sharma. Integrating environmental sustainability in construction Time-Cost trade-off for decision-making using hybrid NSGA-III and MOPSO approach. Asian J Civ Eng. 26, 1527–1542 (2025). https: // doi.org/ 10.1007/ s42107- 025- 01265-3.

[3] R. Kaur, B. J. Mwambegele, A. G. Abraham, S. A. Basheer, S. Garia. A comprehensive review on building information modelling (BIM), its implementations and applications. Discov Civ Eng. 2, 177 (2025). https://doi.org/10.1007/s44290-025-00342-5

[4] L. Liu, Research on the Application of BIM + GIS + IOT Technologies in the Digital Construction Site of Anjiu Railway. Engineering Economics. 42(22), 147-149 (2023)

[5] M. Priyanka, P. Partheeban, V. P, K. S, A. C, Geospatial technology and IoT based soil and water conservation—A critical review. ICSCAN. 1–6 (2024). https: // doi.org/ 10.1109/ ICSCAN62807.2024. 10894644.

[6] X. Liu, M. F. Antwi-Afari, J. Li, YC. Zhang, P. Manu, BIM, IoT, and GIS integration in construction resource monitoring. Autom. Constr. 174, 106149 (2025). https://doi.org/10.1016/j.autcon.2025.106149

[7] D.X. Wang, Research on the whole process control of prefabricated building construction based on the integration of BIM model and RFID technology. Sichuan Cement. (11): 16-18 (2025). DOI:10.20198/ j.cnki.scsn. 2025.11.003

[8] W.M. Yu, Y.X. Yu, Y.H. Yu, Management of shield construction process for the Guangdong Water Resources Allocation Project in the Northern Bay of Hainan. Urban Construction Theory Research (Electronic Edition). (33), 19-22 (2024). DOI: 10.19569/j.cnki.cn119313/tu.202433007

[9] Y.K. Luo, Y.S. Hu, M.D. Yan, P.P. Yang, Design of a water and soil conservation monitoring system based on NB-IoT. Computer Measurement and Control. 30(02), 51-57+64 (2022). DOI: 10.16526/j.cnki.11-4762/tp.2022.02.008

[10] A. Hrysiewicz, X. W. Wang, E. P. Holohan, EZ-InSAR: An easy-to-use open-source toolbox for mapping ground surface deformation using satellite interferometric synthetic aperture radar. Earth Sci. Inform, 16, 1929–1945 (2023). https://doi.org/10.1007/s12145-023-00973-1

[11] P. Zhang, Z.H. Guo, S.F. Guo, J. Xia, Land subsidence monitoring method in regions of variable radar reflection characteristics by integrating PS-InSAR and SBAS-InSAR techniques. Remote Sens. 14(14), 3265 (2022). https://doi.org/10.3390/rs14143265

[12] X.L. Lu, W. Wang, C. Yang, X.Q. Hu, X. Liao, Z.H. Fu, Exploring the Influence of Seismic Source and Improvement Methods on Tunnel Seismic Prediction. LITHOSPHERE-US, 2024(2) (2024). https://doi.org/10.2113/2024/lithosphere_2023_334