Automated Construction Monitoring Using Drone Technology And Digital Twins
Abstract
The construction industry faces significant challenges in terms of project tracking, quality assurance, and making real-time decisions. The study examines the transformations that are possible when considering the use of drone technology in combination with digital twinning structures to automate construction site monitoring. This paper demonstrates that integrating uncrewed aerial vehicles (UAVs) and digital twin models enables the transformation of construction supervision. Key results indicate an increase in monitoring efficiency, with a potential decrease in inspection time of up to 75%, improved accuracy in tracking progress, and cost savings resulting from early identification of problems. The embedding enables real-time data synchronisation between the actual construction site and a virtual digital twin model, supporting predictive capabilities and active project management. This study contributes to a strategy guide on industry adoption, technical difficulty, regulatory, and organisational issues, emphasising the importance of this technology convergence to innovative construction practices.
Keywords
Full Text:
PDFReferences
1. Salem, T., Dragomir, M., & Chatelet, E. (2024). Strategic integration of drone technology and digital twins for optimal construction project management. Applied Sciences, 14(11), 4787. doi: 10.3390/app14114787
2. Alhammadi, S. A., Tayeh, B. A., Alaloul, W. S., & Salem, T. J. (2021). Risk Management Strategies in Construction Organisations. The Open Civil Engineering Journal, 15(1), 406–413. doi: 10.2174/1874149502115010406
3. Boje, C., Guerriero, A., Kubicki, S., & Rezgui, Y. (2020). Towards a semantic Construction Digital Twin: Directions for future research. Automation in Construction, 114, 103179. doi: 10.1016/j.autcon.2020.103179
4. Omrany, H., Al-Obaidi, K. M., Husain, A., & Ghaffarianhoseini, A. (2023). Digital Twins in the Construction industry: A comprehensive review of current implementations, enabling technologies, and future directions. Sustainability, 15(14), 10908. doi: 10.3390/su151410908
5. Rao, A. S., Radanovic, M., Liu, Y., Hu, S., Fang, Y., Khoshelham, K., Palaniswami, M., & Ngo, T. (2022). Real-Time Monitoring of Construction Sites: Sensors, Methods, and Applications. Automation in Construction, 136, 104099. doi: 10.1016/j.autcon.2021.104099
6. Ullo, S. L., & Sinha, G. R. (2020). Advances in Smart Environment Monitoring Systems Using IoT and Sensors. Sensors, 20(11), 3113. doi: 10.3390/s20113113
7. Anwar, N., Izhar, M. A., & Najam, F. A. (2018). Construction Monitoring and Reporting using Drones and Unmanned Aerial Vehicles (UAVs). The Tenth International Conference on Construction in the 21st Century (CITC-10)
8. Fan, J., & Saadeghvaziri, M. A. (2019). Applications of Drones in Infrastructure: Challenges and Opportunities. Zenodo (CERN European Organisation for Nuclear Research). doi: 10.5281/zenodo.3566281
9. Berie, H. T., & Burud, I. (2018). Application of Unmanned Aerial Vehicles in Earth Resources Monitoring: A Focus on Evaluating Potentials for Forest Monitoring in Ethiopia. European Journal of Remote Sensing, 51(1), 326–335. doi: 10.1080/22797254.2018.1432993
10. Feng, H., Chen, Q., & De Soto, B. G. (2021). Application of Digital Twin Technologies in Construction: An Overview of Opportunities and Challenges. Proceedings of the ISARC. doi: 10.22260/isarc2021/0132
11. Hou, L., Wu, S., Zhang, G., Tan, Y., & Wang, X. (2020). Literature Review of Digital Twins Applications in Construction Workforce Safety. Applied Sciences, 11(1), 339. doi: 10.3390/app11010339
12. Piras, G., Agostinelli, S., & Muzi, F. (2024). Digital Twin Framework for Built Environment: A review of Key Enablers. Energies, 17(2), 436. doi: 10.3390/en17020436
13. Salem, T., & Dragomir, M. (2022). Options for and Challenges of Employing Digital Twins in Construction Management. Applied Sciences, 12(6), 2928. doi: 10.3390/app12062928
14. Pal, A., Lin, J. J., Hsieh, S., & Golparvar-Fard, M. (2023). Automated vision-based construction progress monitoring in the built environment through a digital twin. Developments in the Built Environment, 16, 100247. doi: 10.1016/j.dibe.2023.100247
15. Jarahizadeh, S., & Salehi, B. (2024). A Comparative analysis of UAV photogrammetric software performance for forest 3D modelling: a case study using AGISoft Photoscan, PIX4DMapper, and DJI Terra. Sensors, 24(1), 286. doi: 10.3390/s24010286
16. Gabara, G., & Sawicki, P. (2019). Multi-Variant Accuracy Evaluation of UAV Imaging Surveys: A case study on an investment area. Sensors, 19(23), 5229. doi: 10.3390/s19235229
17. Ahmed, F., Mohanta, J. C., Keshari, A., & Yadav, P. S. (2022). Recent Advances in Unmanned Aerial Vehicles: A Review. Arabian Journal for Science and Engineering, 47(7), 7963–7984. doi: 10.1007/s13369-022-06738-0
18. Qi, Q., Zhao, D., Liao, T. W., & Tao, F. (2018). Modelling of Cyber-Physical Systems and Digital Twin Based on Edge Computing, Fog Computing and Cloud Computing Towards Smart Manufacturing. International Manufacturing Science and Engineering Conference. doi: 10.1115/msec2018-6435
19. Moeini, S., Oudjehane, A., Baker, T., & Hawkins, W. (2017). Application of an interrelated UAS-BIM system for construction progress monitoring, inspection and project management. PM World Journal, 6(9), 1-13.
20. Dupont, Q. F., Chua, D. K., Tashrif, A., & Abbott, E. L. (2017). Potential Applications of UAVs along the Construction Value Chain. Procedia Engineering, 182, 165–173. doi: 10.1016/j.proeng.2017.03.155
21. Rui, Y., Yaik-Wah, L., & Siang, T. C. (2021). Construction Project Management based on Building Information Modelling (BIM). Civil Engineering and Architecture, 9(6), 2055–2061. doi: 10.13189/cea.2021.090633
22. Koon, M. (2016). Construction of Sacramento Kings Arena Using Award-Winning Drone Monitoring System Developed at Illinois. Retrieved from https://cee.illinois.edu/news/construction-sacramento-kings-arena-using-award-winning-drone-monitoring-system-developed
23. Hirose, M., Xiao, Y., Zuo, Z., Kamat, V. R., Zekkos, D., & Lynch, J. (2015). Implementation of UAV localisation methods for a mobile post-earthquake monitoring system. IEEE Workshop on Environmental, Energy, and Structural Monitoring Systems (EESMS) Proceedings, 66–71. doi: 10.1109/eesms.2015.7175854
24. Zhang, P., Li, N., Jiang, Z., Fang, D., & Anumba, C. J. (2018). An agent-based modelling approach for understanding the effect of worker-management interactions on construction workers' safety-related behaviours. Automation in Construction, 97, 29–43. doi: 10.1016/j.autcon.2018.10.015
25. Behzadi, A. (2016). Using Augmented and Virtual Reality Technology in the Construction Industry. American Journal of Engineering Research, 5(12), 350-353.
26. Tayeh, B. A., Salem, T. J., Aisheh, Y. I. A., & Alaloul, W. S. (2020). Risk Factors Affecting the Performance of Construction Projects in the Gaza Strip. The Open Civil Engineering Journal, 14(1), 94–104. doi: 10.2174/1874149502014010094
27. Draghici, A., Dursun, S., Bașol, O., Boatca, M. E., & Gaureanu, A. (2022). The Mediating Role of Safety Climate in the Relationship between Transformational Safety Leadership and Safe Behaviour – The Case of Two Companies in Turkey and Romania. Sustainability, 14(14), 8464. doi: 10.3390/su14148464
28. Noghabaei, M., Heydarian, A., Balali, V., & Han, K. (2020). Trend analysis on the adoption of virtual and augmented reality in the architecture, engineering, and construction industry. Data, 5(1), 26. doi: 10.3390/data5010026
29. Elshafey, A., Saar, C. C., Aminudin, E. B., Gheisari, M., & Usmani, A. (2020). Technology Acceptance Model for Augmented Reality and Building Information Modelling Integration in the Construction Industry. Journal of Information Technology in Construction, 25, 161–172. doi: 10.36680/j.itcon.2020.010
Article Metrics
Metrics powered by PLOS ALM
Refbacks
- There are currently no refbacks.
Copyright (c) 2025 Aleke Christiana Ukamaka, Christopher Mayowa Adeniji, Kofi Yeboah Adjei, Olatunji Olamide Segun, Idris Usman Aliyu, Peter Sanctus Ejiofor

This work is licensed under a Creative Commons Attribution 4.0 International License.



