Русский
English
This study examines the transformative impact of digital technologies on construction site management in the Russian Federation. Using a multi-method research approach incorporating content analysis, comparative assessment, systems analysis, and SWOT evaluation, the research investigates how Building Information Modeling (BIM), Internet of Things (IoT) architecture, cloud computing, and artificial intelligence applications reconfigure traditional construction processes. Findings demonstrate that smart construction sites implement informatization across four critical dimensions: personnel management, machinery administration, material resource coordination, and construction target optimization. Comparative analysis reveals significant advantages of technology-enhanced approaches over conventional methods, particularly in multi-location collaborative workflows, simulation modeling, construction process visualization, and remote monitoring capabilities. The SWOT analysis identifies initial capital investment requirements, specialized workforce development, and systems integration complexities as primary implementation challenges. The research concludes that smart construction sites represent an evolutionary progression in the construction industry, with implementation effectiveness directly correlating to organizational digital maturity, ultimately establishing unprecedented levels of construction production efficiency and operational safety.
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22. Abioye S.O., Oyedele L.O., Akanbi L., Ajayi A., Delgado J.M.D., Bilal M. et al., Artificial intelligence in the construction industry: a review of present status, opportunities and future challenges. Journal of Building Engineering. 2021. 44. P. 103299. DOI: 10.1016/j.jobe.2021.103299
2. Safiullin M.R., Elshin L.A., Dinmukhametova A.A., Sharapov A.R., Blockchain transactions as a promising mechanism to ensure sustainable development of the construction complex under sanctions (by the example of the Russian economy). Vestnik MGSU. 2024.19 (6). P. 1016 – 1030. DOI: 10.22227/1997-0935.2024.6.1016-1030
3. Shishkina D.N., Assessment of economic efficiency of artificial intelligence application in construction: the choice of the optimal method. Vestnik MGSU. 2024. 19 (9). P. 1550 – 1561. DOI: 10.22227/1997-0935.2024.9.1550-1561
4. Karakozova I.V., Lisitsyn I.M., Boldyshev K.V., Methods of designing work operations in the conditions of digital technologies implementation in the construction industry. Vestnik MGSU.2024. 19 (8). P. 1373 – 1389. DOI: 10.22227/1997-0935.2024.8.1373-1389
5. Zhou J., Towards a New Generation of Intelligent Manufacturing. China Sci. Technol. Ind. 2018. 06. P. 20 – 23. DOI: 10.1016/j.eng.2018.01.002
6. Evdokimova T.S., Influence of Data Augmentation Methods on the Quality of Neural Network Models Training. Adaptive Approach to Data Augmentation. Eng. Bull. Don. 2024. 8. ivdon.ru/ru/magazine/archive/n9y2024/9461
7. Manyika J., Chui M., Brown B., et al., Big Data: The Next Frontier for Innovation, Competition, and Productivity. McKinsey Global Institute. 2011. DOI: 10.4236/ijis.2015.53013
8. Gareev I.F., Mukhametova N.N., The Introduction of Digital Technologies at the Stages of the Life Cycle of Residential Real Estate. Russian Journal of Housing Research. 2018. 5 (3). P. 305 – 322. DOI: 10.18334/zhs.5.3.39692
9. Jiang S., Yang B., Liu B., Precast components on-site construction planning and scheduling method based on a novel deep learning integrated multi-agent system. Journal of Building Engineering. 2025. 102. 111907. DOI: 10.1016/j.jobe.2025.111907
10. Al-Sehrawy R., Kumar B., Digital Twins in Architecture, Engineering, Construction and Operations. A Brief Review and Analysis. In: E. Toledo Santos, S. Scheer (eds), Proceedings of the 18th International Conference on Computing in Civil and Building Engineering. ICCCBE 2020. Lecture Notes in Civil Engineering, vol. 2021. 98. P. 924 – 939. Springer, Cham. DOI: 10.1007/978-3-030-51295-8_64
11. Ginzburg A.V., Ryzhkova A.I., Artificial Intelligence Capabilities for Increasing Organizational-Technological Reliability of Construction. Vestnik MGSU. 2018. 13 (1). P. 7 – 13. DOI: 10.22227/1997-0935.2018.1.7-13
12. Shishkina D.N. Assessment of economic efficiency of artificial intelligence application in construction: the choice of the optimal method. Vestnik MGSU. 2024. 19 (9). P. 1550 – 1561. DOI: 10.22227/1997-0935.2024.9.1550-1561
13. Fang W., Zhong B., Zhao N., Love P.E.D., Luo H., Xue J. et al., A deep learning-based approach for mitigating falls from height with computer vision: Convolutional neural network. Advanced Engineering Informatics. 2019. 39. P. 170 – 177. DOI: 10.1016/j.aei.2018.12.005
14. Zhang H., Wei J,. Jiao J., Gao Y., Comprehensive information management analysis of construction project based on BIM. Advances in Intelligent Systems and Computing. 2020. 1117. P. 1027 – 1033. DOI: 10.1007/978-981-15-2568-1_141
15. Tian H., Application of Information Technology in Construction Engineering Management. Management Science and Engineering. 2021. 10. P. 375 – 380. DOI: 10.12677/MSE.2021.104045
16. Salem T., Dragomir M., Chatelet E., Strategic Integration of Drone Technology and Digital Twins for Optimal Construction Project Management. Applied Sciences (Switzerland) 2024. 14 (11). 4787. DOI: 10.3390/app14114787
17. Torokhova K.E., Matveeva M.V., Economic efficiency and prospects for introducing information modelling technologies during the design stage in the building sector of a region. Proceedings of Universities. Investment. Construction. Real estate. 2023. 13 (2) (45). P. 192 – 201. DOI: 10.21285/2227-2917-2023-2-192-201
18. Liu G., Ma Z., Li S., Survey on lean construction and digital technology integration based on literature research. Tongji Daxue Xuebao/Journal of Tongji University. 2024. 52 (1). P. 145 – 156. DOI: 10.11908/j.issn.0253-374x.22147
19. Toyin J.O., Azhar S., Sattineni A., Fasoyinu A.A., Investigating the influence of ict application in construction jobsites: a systematic review and bibliometric analysis. Journal of information technology in construction. 2024. 29. P. 444 – 479. DOI: 10.36680/j.itcon.2024.021
20. Zaman M., Abdelwahed S., Zohrabi N., A Review of IoT-Based Smart City Development and Management. Journal of Smart Cities. 2024. 7. P. 1462 – 1500. DOI: 10.3390/smartcities7030061
21. Elshafey A., Saar C.C., Aminudin E.B., Gheisari M., Usmani A., Technology acceptance model for augmented reality and building information modeling integration in the construction industry. Journal of Information Technology in Construction. 2020. 25. P. 161 – 172. DOI: 10.36680/j.itcon.2020.010
22. Abioye S.O., Oyedele L.O., Akanbi L., Ajayi A., Delgado J.M.D., Bilal M. et al., Artificial intelligence in the construction industry: a review of present status, opportunities and future challenges. Journal of Building Engineering. 2021. 44. P. 103299. DOI: 10.1016/j.jobe.2021.103299
Lapidus A.A., Topchiy D.V., Baulin A.V., Yan J., Zhou B. Comprehensive analysis of digital technology applications in construction site management. Construction Materials and Products. 2025. 8 (2). 1. https://doi.org/10.58224/2618-7183-2025-8-2-1