Application of Unmanned Aerial Vehicles in Construction Industry

: pp. 35 – 42
Received: March 27, 2023
Revised: May 14, 2024
Accepted: May 21, 2024

R. Baitsar, A. Telishevskyi. Application of unmanned aerial vehicles in construction industry. Energy Engineering and Control Systems, 2024, Vol. 10, No. 1, pp. 35 – 42.

Lviv Polytechnic National University
Lviv Polytechnic National University

Technological advances in the field of electronics, such as miniature electromechanical devices and small powerful electric motors, have made it possible to develop small and light devices, such as unmanned aerial vehicles (UAVs). Recently, civilian UAVs are rapidly gaining popularity. Undoubtedly, UAVs will be used for many services in the future. There is already a growing demand for such fields of application of unmanned aerial vehicles as agriculture, emergency services, energy, fuel, mining, construction, geodesy (cartography), transportation, etc. Thanks to modern technologies it possible to produce light and low-power but accurate sensors that can be used by controllers with high computing power and low energy consumption. This makes it possible to develop complex control systems for UAVs that can be implemented on board. Today’s quadcopters are used for design, surveillance, search, construction inspections, and a variety of other applications.

  1. Tealgroup. Available online: (accessed on 14 March 2022).
  2. Choi, H.-W.; Kim, H.-J.; Kim, S.-K.; Na, W.S. An Overview of Drone Applications in the Construction Industry. Drones 2023, 7, 515.
  3. Molina, A.A.; Huang, Y.; Jiang, Y. A Review of Unmanned Aerial Vehicle Applications in Construction Management: 2016–2021. Standards 2023, 3, 95-109.
  4. Szóstak, M., Nowobilski, T., Mahamadu, A.-M. and Pérez, D.C. (2023), "Unmanned aerial vehicles in the construction industry - Towards a protocol for safe preparation and flight of drones", International Journal of Intelligent Unmanned Systems, Vol. 11 No. 2, pp. 296-316.
  5. Application of drones in construction projects [Electronic resource]. – URL : stroitelnyh-proektah.html – in Ukrainian
  6. Drones. A revolution in construction technologies [Electronic resource]. – URL : stroitelstva – in Ukrainian
  7. Siebert, S.; Teizer, J. Mobile 3D mapping for surveying earthwork projects using Unmanned Aerial Vehicle (UAV) system. Autom. Constr. 2014, 41, 1–14.
  8. Goessens, S.; Muller, C.; Latteur, P. Feasibility study for drone-based masonry construction of real-scale structures. Autom. Constr. 2018, 94, 458–480.
  9. Hallermann, N.; Morgenthal, G. Unmanned aerial vehicles (UAV) for the assessment of existing structures. In Proceedings of the 36th IABSE Symposium, Kolkata, India, 24–27 September 2013.
  10. Rachmawati, T.S.N.; Kim, S. Unmanned Aerial Vehicles (UAV) Integration with Digital Technologies toward Construction 4.0: A Systematic Literature Review. Sustainability 2022, 14, 5708.
  11. Dallasega, P.; Rauch, E.; Linder, C. Industry 4.0 as an enabler of proximity for construction supply chains: A systematic literature review. Comput. Ind. 2018, 99, 205–225.
  12. Unmanned Aircraft Systems Roadmap 2005–2030 USA Office of the Secretary of Defense // roadmaplast.pdf , 2006 – 213 p.
  13. Kwon, S.; Park, J.-W.; Moon, D.; Jung, S.; Park, H. Smart Merging Method for Hybrid Point Cloud Data using UAV and LIDAR in Earthwork Construction. Procedia Eng. 2017, 196, 21–28.
  14. Jiang, W.; Zhou, Y.; Ding, L.; Zhou, C.; Ning, X. UAV-based 3D reconstruction for hoist site mapping and layout planning in petrochemical construction. Autom. Constr. 2020, 113.
  15. Asadi, K.; Suresh, A.K.; Ender, A.; Gotad, S.; Maniyar, S.; Anand, S.; Noghabaei, M.; Han, K.; Lobaton, E.; Wu, T. An integrated UGV-UAV system for construction site data collection. Autom. Constr. 2020, 112.
  16. Gheisari, M.; Rashidi, A.; Esmaeili, B. Using Unmanned Aerial Systems for Automated Fall Hazard Monitoring. In Construction Research Congress 2018; American Society of Civil Engineers: New Orleans, LA, USA, 2018; pp. 62–72.
  17. Vacanas, Y.; Themistocleous, K.; Agapiou, A.; Hadjimitsis, D. Building information modelling (BIM) and unmanned aerial vehicle (UAV) technologies in infrastructure construction project management and delay and disruption analysis. In Proceedings of the Third International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2015), Paphos, Cyprus, 22 June 2015.
  18. Kerle, N.; Nex, F.; Gerke, M.; Duarte, D.; Vetrivel, A. UAV-based structural damage mapping: A review. Int. J. Geo-Inf. 2020, 9, 14
  19. Melo, R.R.S.; Costa, D.B.; Álvares, J.S.; Irizarry, J. Applicability of unmanned aerial system (UAS) for safety inspection on construction sites. Saf. Sci. 2017, 98, 174–185.
  20. Albeaino, G.; Gheisari, M. Trends, benefits, and barriers of unmanned aerial systems in the construction industry: A survey study in the United States. J. Inf. Technol. Constr. 2021, 26, 84–111.
  21. Varbla, S.; Ellmann, A.; Puust, R. Centimetre-range deformations of built environment revealed by drone-based photogrammetry. Autom. Constr. 2021, 128.
  22. Tian, J.; Luo, S.; Wang, X.; Hu, J.; Yin, J. Crane lifting optimization and construction monitoring in steel bridge construction project based on BIM and UAV. Adv. Civil. Eng. 2021, 2021,
  23. Nex, F.; Remondino, F. UAV for 3D mapping applications: A review. Appl. Geomat. 2014, 6, 1–15.
  24. Bang, S.; Kim, H. Context-based information generation for managing UAV-acquired data using image captioning. Autom. Constr. 2020, 112,
  25. Martínez-Carricondo, P.; Carvajal-Ramírez, F.; Yero-Paneque, L.; Agüera-Vega, F. Combination of HBIM and UAV photogrammetry for modelling and documentation of forgotten heritage. Case study: Isabel II dan in Níjar (Almería, Spain). Herit. Sci. 2021, 9, 95.
  26. Irizarry, J.; Karan, E.P.; Jalaei, F. Integrating BIM and GIS to improve the visual monitoring of construction supply chin management. Autom. Constr. 2013, 31, 241–254.
  27. Pepe, M.; Constantino, D.; Alfio, V.S.; Restuccia, A.G.; Papalino, N.M. Scan to BIM for the digital management and representation in 3D GIS environment of cultural heritage site. J. Cult. Herit. 2021, 50, 115–125.
  28. Khan, M.S.; Park, J.; Seo, J. Geotechnical property modeling and construction safety zoning based on GIS and BIM integration. Appl. Sci. 2021, 11, 4004.
  29. Wen, M.-C.; Kang, S.-C. Augmented Reality and Unmanned Aerial Vehicle Assist in Construction Management. In Computing in Civil and Building Engineering; American Society of Civil Engineers: Orlando, FL, USA, 2014; pp. 1570–1577.
  30. Tomita, H.; Takabatake, T.; Sakamoto, S.; Arisumi, H.; Kato, S.; Ohgusu, Y. Development of UAV Indoor Flight Technology for Building Equipment Works. In Proceedings of the International Symposium on Automation and Robotics in Construction, Taipei, Taiwan, 28 June–1 July 2017; pp. 452–457.
  31. Patel, T.; Suthar, V.; Bhatt, N. Application of Remotely Piloted Unmanned Aerial Vehicle in Construction Management. In Recent Trends in Civil Engineering; Pathak, K.K., Bandara, J.M.S.J., Agrawal, R., Eds.; Lecture Notes in Civil Engineering; Springer: Singapore, 2021; Volume 77, pp. 319–329.
  32. Hugenholtz, C.; Brown, O.; Walker, J.; Barchyn, T.; Nesbit, P.; Kucharczyk, M.; Myshak, S. Spatial Accuracy of UAV-Derived Orthoimagery and Topography: Comparing Photogrammetric Models Processed with Direct Geo-Referencing and Ground Control Points. Geomatica 2016, 70, 21–30.
  33. Zhou, S.; Gheisari, M. Unmanned aerial system applications in construction: A systematic review. Constr. Innov. 2018, 18, 453–468.
  34. Hamledari, H.; Davari, S.; Azar, E.R.; McCabe, B.; Flager, F.; Fischer, M. UAV-Enabled Site-to-BIM Automation: Aerial Robotic- and Computer Vision-Based Development of As-Built/As-Is BIMs and Quality Control. In Construction Research Congress 2018; American Society of Civil Engineers: New Orleans, LA, USA, 2018; pp. 336–346.
  35. Kim, S.; Irizarry, J.; Kanfer, R. Multilevel Goal Model for Decision-Making in UAS Visual Inspections in Construction and Infrastructure Projects. J. Manag. Eng. 2020, 36.
  36. Leite, F.; Cho, Y.; Behzadan, A.H.; Lee, S.; Choe, S.; Fang, Y.; Akhavian, R.; Hwang, S. Visualization, Information Modeling, and Simulation: Grand Challenges in the Construction Industry. J. Comput. Civ. Eng.2016, 30.
  37. Nesbit, P.R.; Hugenholtz, C.H. Enhancing UAV–SfM 3D Model Accuracy in High-Relief Landscapes by Incorporating Oblique Images. Remote Sens. 2019, 11, 239.
  38. Fonstad, M.A.; Dietrich, J.T.; Courville, B.C.; Jensen, J.L.; Carbonneau, P.E. Topographic structure from motion: A new development in photogrammetric measurement: Topographic Structure from Motion. Earth Surf. Process. Landforms 2012, 38, 421–430.
  39. Agüera-Vega, F.; Carvajal-Ramírez, F.; Martínez-Carricondo, P. Assessment of photogrammetric mapping accuracy based on variation ground control points number using unmanned aerial vehicle. Measurement 2017, 98, 221–227.
  40. Niethammer, U.; James, M.R.; Rothmund, S.; Travelletti, J.; Joswig, M. UAV-based remote sensing of the Super-Sauze landslide: Evaluation. Eng. Geol. 2012, 128, 2–11.
  41. Smith, M.W.; Carrivick, J.L.; Quincey, D.J. Structure from motion photogrammetry in physical geography. Prog. Phys. Geogr. 2015, 40, 247–275.
  42. Nieminski, N.M.; Graham, S.A. Modeling Stratigraphic Architecture Using Small Unmanned Aerial Vehicles and Photogrammetry: Examples From the Miocene East Coast Basin, New Zealand. J. Sediment. Res. 2017, 87, 126–132.
  43. Wolf, P.R.; Dewitt, B.A.; Wilkinson, B.E. Elements of Photogrammetry with Application in GIS, 4th ed.; McGraw-Hill Education: Maidenhead, UK, 2014. ISBN-13: 978-0071761123
  44. Martin, R.; Rojas, I.; Franke, K.W.; Hedengren, J.D. Evolutionary View Planning for Optimized UAV Terrain Modeling in a Simulated Environment. Remote Sens. 2016, 8, 26.
  45. Pavlis, T.L.; Mason, K.A. The New World of 3D Geologic Mapping. GSA Today 2017, 4–10.
  46. Vacca, G.; Dessì, A.; Sacco, A. The Use of Nadir and Oblique UAV Images for Building Knowledge. ISPRS Int. J. Geo-Inf. 2017, 6, 393.
  47. Ostrowski, W. Accuracy of measurements in oblique aerial images for urban environment. Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci. ISPRS Arch. 2016, 42, 79–85.
  48. Rosenberg, A.S.; Waller, P.M. An Evaluation of a UAV Guidance System with Consumer Grade GPS Receivers; Proquest, Umi Dissertation Publishing: Ann Arbor, MI, USA, 2009; p. 175.
  49. Forlani, G.; Dall’Asta, E.; Diotri, F.; di Cella, U.M.; Roncella, R.; Santise, M. Quality assessment of DSMs produced from UAV flights georeferenced with on-board RTK positioning. Remote Sens. 2018, 10, 311.
  50. Moe, K.; Toschi, I.; Poli, D.; Lago, F.; Schreiner, C.; Legat, K.; Remondino, F. Changing the production pipeline – use of oblique aerial cameras for mapping purposes. Off. Publ. EuroSDR 2017, 2017, 44–61.