Submitted Successfully!
To reward your contribution, here is a gift for you: A free trial for our video production service.
Thank you for your contribution! You can also upload a video entry or images related to this topic.
Version Summary Created by Modification Content Size Created at Operation
1 -- 1813 2024-02-08 01:39:18 |
2 update references and layout Meta information modification 1813 2024-02-08 03:01:59 |

Video Upload Options

Do you have a full video?

Confirm

Are you sure to Delete?
Cite
If you have any further questions, please contact Encyclopedia Editorial Office.
Kim, J.; Lee, D.; Kim, G. 3D Laser Scanner in a Structural Framework. Encyclopedia. Available online: https://encyclopedia.pub/entry/54882 (accessed on 09 October 2024).
Kim J, Lee D, Kim G. 3D Laser Scanner in a Structural Framework. Encyclopedia. Available at: https://encyclopedia.pub/entry/54882. Accessed October 09, 2024.
Kim, Ju-Yong, Donghoon Lee, Gwang-Hee Kim. "3D Laser Scanner in a Structural Framework" Encyclopedia, https://encyclopedia.pub/entry/54882 (accessed October 09, 2024).
Kim, J., Lee, D., & Kim, G. (2024, February 08). 3D Laser Scanner in a Structural Framework. In Encyclopedia. https://encyclopedia.pub/entry/54882
Kim, Ju-Yong, et al. "3D Laser Scanner in a Structural Framework." Encyclopedia. Web. 08 February, 2024.
3D Laser Scanner in a Structural Framework
Edit

As interest in smart construction technology increases, various smart construction technologies are being used for sustainable construction management. Among these technologies, 3D laser scanning technology receives data such as the speed, time, direction, and distance of light or laser beams reflected from the target object, allowing the representation of the object’s shape in a 3D-coordinate-based point cloud. Currently, a variety of equipment is used in 3D laser scanning, with the time-of-flight (TOF) method and phase-shift method commonly employed for laser scanning to detect the wavelength. This technology stands out for phenomena analysis and monitoring, with various applications being studied for construction engineering and management in construction industry.

3D laser scanning technology point cloud data smart construction technology

1. Introduction

With the recent activation of Fourth Industrial Revolution technologies, the construction industry is also very interested in various applicable smart construction technologies [1]. Representative smart construction technologies applicable to the construction field include Building Information Modeling (BIM), Internet of Things (IoT), 3D laser scanning technology, drone surveying technology, Augmented Reality (AR), Virtual Reality (VR), etc. [2]. By applying these smart construction technologies to construction work and management, various application methods such as energy saving and labor saving, as well as solving problems occurring in the construction industry, are being researched [3]. This research will ultimately lead to sustainable construction management. This is because the efficient use of construction resources and the creation and management of the environment on an ecological basis result in sustainable construction management and can achieve sustainability in the construction industry [4].
Among the smart construction technologies, 3D laser scanning technology is excellent at capturing real-world phenomena and is being utilized to analyze and monitor various existing conditions. Therefore, research is being conducted on how to measure and analyze the state of construction works using this 3D laser scanning technology [5]. This technology allows the collection of the current state of objects in the form of point cloud data (PCD) [6]. Recently, research on 3D laser scanning technology is being performed to monitor and analyze the current state of an object in various fields, including the construction industry, such as crop yield measurement in agriculture [7], railway environmental modeling [8], bridge monitoring [9], forest modeling and monitoring [10], cultural heritage monitoring, etc. [11].
The 3D model created from PCD obtained using devices like 3D laser scanners, LiDAR equipment, and 2D data conversion devices has been studied in conjunction with BIM as Scan to BIM [12]. The limitation of the PCD, unless integrated with other technologies, is that it is limited to analyzing existing conditions. Recent research has focused on utilizing PCD in the construction field by overlapping it with BIM to assess work progress through similarity measurements [13] and by employing algorithms to convert point clouds into shapes, thus using surface-based recognition metrics to monitor work progress compared to BIM [14]. Various studies are ongoing on BIM in conjunction with PCD for sustainable construction management.
The accurate and up-to-date measurements of work progress on a construction site are essential to sustainable project management functions such as scheduling and cost management but are currently performed using traditional building surveying techniques and visual inspection [15]. Traditional techniques for work progress management that manually collect and manage construction progress data contain inaccurate and missing information during the construction phase [16]. Traditional work progress measurements rely heavily on manual tasks and have been criticized by construction practitioners for their repeatability, inefficiency, and potential for error [17]. Automatic techniques for progress measurement studied until recently can be divided into two categories: the first is imaging techniques such as 3D laser scanning [17][18][19][20][21][22][23], 3D ranging cameras [17][23][24][25], and 2D-based modeling [26][27][28][29][30][31], and the second is geospatial techniques such as wireless fidelity (Wi-fi) [32], Global Positioning System (GPS) [33], barcodes [34][35], Radio-Frequency Identification (RFID) [36][37][38], and ultra-wideband (UWB) [39]. In particular, the three-dimensional model, which is known as PCD, obtained through 3D laser scanning technology, takes a form that is very similar to reality. PCD can be used in a variety of ways because it contains various types of information such as the location, color, and intensity of the object. Therefore, when analysis of the current status of an object is required, such as progress measurement, it is considered appropriate to apply 3D laser scanning technology to compare 3D information.

2. Data Collection Methods for Construction Progress Measurement

In construction projects, progress measurement is utilized as a metric to track the progress of construction [40]. To achieve accurate progress measurement, it is essential to first have a precise understanding of the construction project’s progress [41]. However, due to factors such as the increasing scale of construction projects and the concurrent progress of various facilities, obtaining reasonable and accurate information for progress rate measurement has limitations [13]. Research related to the automatic acquisition of information on construction progress on construction sites can be categorized into imaging techniques [17][18][19][20][21][22][23][24][25][26][27][28][29][30][31] and geospatial techniques [32][33][34][35][36][37][38][39]. The types and characteristics of these technologies are presented in Table 1.
Table 1. Data collection methods for progress measurement.
Imaging techniques include 3D laser scanning, 3D ranging cameras, and image-based modeling. Among these techniques, 3D laser scanning utilizes measurement techniques based on LiDAR or LaDAR to construct laser points received in a three-dimensional coordinate system in the form of a point cloud. This technique allows for the automatic collection of data that closely resemble reality, contributing to high accuracy and improved timeliness of data. However, it has disadvantages, including the need for experts to operate 3D laser scanners and the relatively high cost of hardware [17][18][19][20][21][22][23]. There are also 3D ranging cameras, which have the advantage of being compact and portable but have limited operating distances and limited in-field data that can be obtained [23][24][25]. Additionally, image-based modeling has user-friendly hardware, a relatively low price, and flexible hardware operation, and it allows the collection of a variety of data [26][27][28][29][30][31]. Geospatial technologies include wireless fidelity (Wi-Fi), Global Positioning System (GPS), barcodes, Radio-Frequency Identification (RFID), and ultra-wideband (UWB). Both Wi-Fi and UWB are technologies that use transceivers to collect data. Wi-Fi is cost-efficient in terms of hardware, but with increased installation and disassembly costs because its transmission range is limited [32]. However, although UWB offers long transmission distances and 3D data-collection capabilities, its application requires significant hardware investment [39]. GPS relies on satellite signals to locate specific objects but has limitations when used indoors [33]. Barcodes are widely used for material tracking and management due to their low cost and ease of use [34][35]. RFID uses chips to handle data and has the advantage of easily accessing stored data [36][37][38]. Utilizing these various data collection techniques has made it possible to collect and utilize construction site data with improved reliability, accuracy, and timeliness compared to collecting data manually.

3. Three-Dimensional Laser Scanning Technology and Its Application in Construction

PCD refers to data that can be acquired through 3D laser scanning technology, enabling the construction of a complete 3D model by combining PCD obtained from various scanning locations. This technology receives data such as the speed, time, direction, and distance of light or laser beams reflected from the target object, allowing the representation of the object’s shape in a 3D-coordinate-based point cloud [31]. Currently, a variety of equipment is used in 3D laser scanning, with the time-of-flight (TOF) method and phase-shift method commonly employed for laser scanning to detect the wavelength.
The PCD that consist of the point cloud includes several features such as three-dimensional coordinates (XYZ), color (RGB), and intensity information. Depending on the equipment’s characteristics, it may contain two or more of these features. Such features allow for robust predictions about the shape of the object based on the points collected by reflections. However, there are limitations in using these physical features for the direct classification of components that constitute the object within the PCD [13].
Several studies [5][42][43][44][45][46][47][48][49] have been conducted on the application of 3D laser scanning technology in the construction field, focusing on sustainability, maintenance, and civil engineering project management. In the study by Cheng and Jin [42], 3D laser scanning technology was applied to the reverse engineering of historical architecture. Their study showed that the historical architecture, which was reconstructed using a digital 3D model from a 3D laser scanner, could record shape, construction style, and structure richly like real architecture. It also supplied basic data for record data and repair protection. Bernet et al. [43] present the results of a study in which the data obtained from 3D laser scanning became a good material to implement an analysis concerning construction and surveying in the maintenance of buildings belonging to the cultural heritage. Moyano et al. [44] compared two scanners used in geodetic measurements for the purpose of BIM in historic buildings. The results of their study revealed that the differences in measurements from two laser scanners (Personal Laser Scanning and Terrestrial Laser Scanning) are not excessively large and admissible for a Scan-to-BIM procedure. Ding, Z. et al. [45] developed a digital framework integrating BIM and reverse engineering (RE) to reduce mistakes and reworks for renovation projects. Their study proposed a digital construction framework for improving information utilization, which integrated BIM, RE, and other advanced tools such as 3D laser scanning technology and prefabricated construction. A review study by Hosamo and Hosamo [46] presented a comprehensive and state-of-the-art review of digital twins using laser scanners in bridge maintenance and engineering. The study by Park and Kim [47] aimed to verify the feasibility of earthwork digitalization technology by applying 3D laser scanning technology to actual sites. The usefulness of its use in construction management was verified by numerically measuring changes in earthwork volume at actual earthwork sites. In a review study by Singh et al. [48], even though the lack of infrastructure in underground mines for data transfer, geodetic networking, and processing capacity remain limiting factors, the 3D laser scanning technology is becoming an integral part of mine automation because of its affordability, accuracy, and mobility, which should support its widespread usage in years to come. In a study by Wang J. et al. [49], the application of 3D laser scanning technology in the field of curtain wall design and installation, including scanning operations, point cloud data collection and processing, 3D BIM model reconstruction, and related BIM model exercises, was addressed. Kim and Kim [5] applied 3D laser scanning technology to check the quality of structural frame construction using a case study, in which it was possible to check the spacing, verticality, and thickness of wall rebars, and to check the dimensions of concrete walls, and the horizontality and thickness of concrete slabs during frame construction.

References

  1. Lee, G.P.; Choi, S.Y.; Son, T.H.; Choi, S.I. Current Status of Smart Technology Utilization and Revitalization Plan of Construction Companies in Korea; CERIK: Seoul, Republic of Korea, 2019; pp. 1–101.
  2. Ministry of Land, Infrastructure and Transport. Roadmap for Smart Construction Technology to Innovate Construction Productivity and Improve Safety; Ministry of Land, Infrastructure and Transport: Sejong, Republic of Korea, 2018.
  3. Chin, G.H. Smart construction technology to innovate construction productivity and enhance safety. Constr. Technol. Ssangyong 2019, 76, 9–15.
  4. Shi, L.; Ye, K.; Lu, W.; Hu, X. Improving the competence of construction management consultants to underpin sustainable construction in China. Habitat Int. 2014, 41, 236–242.
  5. Kim, J.Y.; Kim, G.H. Application of 3D laser scanning technology to the measurement of construction precision in building structural frame construction. J. Archit. Inst. Korea 2022, 38, 245–253.
  6. Hong, S.; Park, I.; Lee, J.; Lim, K.; Choi, Y.; Sohn, H.G. Utilization of a terrestrial laser scanner for the calibration of mobile mapping systems. Sensors 2017, 17, 474.
  7. Méndez, V.; Pérez-Romero, A.; Sola-Guirado, R.; Miranda-Fuentes, A.; Manzano-Agugliaro, F.; Zapata-Sierra, A.; Rodríguez-Lizana, A. In-Field Estimation of Orange Number and Size by 3D Laser Scanning. Agronomy 2019, 9, 885.
  8. Zhu, L.; Hyyppa, J. The use of airborne and mobile laser scanning for modeling railway environments in 3D. Remote Sens. 2014, 6, 3075–3100.
  9. Rashidi, M.; Mohammadi, M.; Sadeghlou Kivi, S.; Abdolvand, M.M.; Truong-Hong, L.; Samali, B. A decade of modern bridge monitoring using terrestrial laser scanning: Review and future directions. Remote Sens. 2020, 12, 3796.
  10. Li, J.; Yang, B.; Cong, Y.; Cao, L.; Fu, X.; Dong, Z. 3D forest mapping using a low-cost UAV laser scanning system: Investigation and comparison. Remote Sens. 2019, 11, 717.
  11. Ham, N.; Bae, B.I.; Yuh, O.K. Phased reverse engineering framework for sustainable cultural heritage archives using laser scanning and BIM: The case of the Hwanggungwoo (Seoul, Korea). Sustainability 2020, 12, 8108.
  12. Leśniak, A.; Górka, M.; Skrzypczak, I. Barriers to BIM implementation in architecture, construction, and engineering projects—The polish study. Energies 2021, 14, 2090.
  13. Kim, S.H. The Construction Project EV Tracking Process Based on the 3D Point Cloud and 4D BIM. Ph.D. Thesis, Yeungnam University, Gyeongsan, Republic of Korea, 2019.
  14. Turkan, Y.; Bosche, F.; Haas, C.T.; Haas, R. Automated progress tracking using 4D schedule and 3D sensing technologies. Autom. Constr. 2012, 22, 414–421.
  15. Zhang, X.; Bakis, N.; Lukins, T.C.; Ibrahim, Y.M.; Wu, S.; Kagioglou, M.; Aouad, G.; Kaka, A.P.; Trucco, E. Automating Progress Measurement of Construction Projects. Autom. Constr. 2009, 18, 294–301.
  16. Lee, H.-G.; Lee, H.-C.; Lee, D.-E. Developing IoT-based Construction Progress Measurement Prototype. J. Archit. Inst. Korea Struct. Constr. 2015, 31, 79–89.
  17. Xue, J.; Hou, X. High-Rise Building Construction Progress Measurement from Top View Based on Component Detection. Buildings 2022, 12, 106.
  18. Kim, J.Y.; Kim, G.H. Identifying Members of Common Structures Utilizing Three-Dimensional Detecting Information for 3D Scanning Model Application. Sustainability 2023, 15, 14073.
  19. Andriasyan, M.; Moyano, J.; Nieto-Julián, J.E.; Antón, D. From point cloud data to building information modelling: An automatic parametric workflow for heritage. Remote Sens. 2020, 12, 1094.
  20. Adan, A.; Quintana, B.; Prieto, S.A.; Bosche, F. An autonomous robotic platform for automatic extraction of detailed semantic models of buildings. Autom. Constr. 2020, 109, 102963.
  21. Liu, J.; Xu, D.; Hyyppa, J.; Liang, Y. A survey of applications with combined BIM and 3D laser scanning in the life cycle of buildings. IEEE J. Sel. Top. Appl. Earth Observ. Remote Sens. 2021, 14, 5627–5637.
  22. Zhang, C.; Arditi, D. Advanced progress control of infrastructure construction projects using terrestrial laser scanning technology. Infrastructures 2020, 5, 83.
  23. Pučko, Z.; Šuman, N.; Rebolj, D. Automated continuous construction progress monitoring using multiple workplace real time 3D scans. Adv. Eng. Inform. 2018, 38, 27–40.
  24. Wasenmüller, O.; Stricker, D. Comparison of kinect v1 and v2 depth images in terms of accuracy and precision. In Proceedings of the Asian Conference on Computer Vision (ACCV 2016), Taipei, Taiwan, 20–24 November 2016; pp. 34–45.
  25. Volk, R.; Luu, T.H.; Mueller-Roemer, J.S.; Sevilmis, N.; Schultmann, F. Deconstruction project planning of existing buildings based on automated acquisition and reconstruction of building information. Autom. Constr. 2018, 91, 226–245.
  26. Omar, H.; Mahdjoubi, L.; Kheder, G. Towards an automated photogrammetry-based approach for monitoring and controlling construction site activities. Comput. Ind. 2018, 98, 172–182.
  27. Yang, J.; Shi, Z.-K.; Wu, Z.-Y. Towards automatic generation of as-built BIM: 3D building facade modeling and material recognition from images. Int. J. Autom. Comput. 2016, 13, 338–349.
  28. Kropp, C.; Koch, C.; König, M. Interior construction state recognition with 4D BIM registered image sequences. Autom. Constr. 2018, 86, 11–32.
  29. Acharya, D.; Ramezani, M.; Khoshelham, K.; Winter, S. BIM-Tracker: A model-based visual tracking approach for indoor localisation using a 3D building model. ISPRS Ann. Photogramm. Remote Sens. Spat. Inf. Sci. 2019, 150, 157–171.
  30. Han, X.-F.; Laga, H.; Bennamoun, M. Image-based 3D object reconstruction: State-of-the-art and trends in the deeplearning era. IEEE T. Pattern Anal. 2019, 43, 1578–1604.
  31. Liu, Y.-P.; Yan, X.-P.; Wang, N.; Zhang, X.; Li, Z. A 3D reconstruction method of image sequence based on deep learning. J. Phys. Conf. Ser. 2020, 1550, 032051.
  32. Sabanci, K.; Yigit, E.; Ustun, D.; Toktas, A.; Aslan, M.F. WiFi Based Indoor Localization: Application and Comparison of Machine Learning Algorithms. In Proceedings of the 2018 XXIIIrd International Seminar/Workshop on Direct and Inverse Problems of Electromagnetic and Acoustic Wave Theory (DIPED), Tbilisi, Georgia, 24–27 September 2018; pp. 246–251.
  33. Song, J.; Haas, C.T.; Caldas, C.H. Tracking the location of materials on construction job sites. J. Constr. Eng. M. 2006, 132, 911–918.
  34. Navon, R.; Sacks, R. Assessing research issues in Automated Project Performance Control (APPC). Autom. Constr. 2007, 16, 474–484.
  35. Tserng, H.P.; Dzeng, R.J.; Lin, Y.C.; Lin, S.T. Mobile construction supply chain management using PDA and bar codes. Comput. Aided Civ. Infrastruct. Eng. 2005, 20, 242–264.
  36. Chen, Q.; Adey, B.T.; Haas, C.; Hall, D.M. Using look-ahead plans to improve material flow processes on construction projects when using BIM and RFID technologies. Constr. Innov. 2020, 20, 471–508.
  37. Oner, M.; Ustundag, A.; Budak, A. An RFID-based tracking system for denim production processes. Int. J. Adv. Manuf. Technol. 2017, 90, 591–604.
  38. Araújo, C.S.; de Siqueira, L.C.; Ferreira, E.D.; Costa, D.B. Conceptual framework for tracking metallic formworks on construction sites using IoT, RFID and BIM technologies. In Proceedings of the 18th International Conference on Computing in Civil and Building Engineering, São Paulo, Brazil, 18–20 August 2020; pp. 865–878.
  39. Cho, Y.K.; Youn, J.H.; Martinez, D. Error modeling for an untethered ultra-wideband system for construction indoor asset tracking. Autom. Constr. 2010, 19, 43–54.
  40. Land and Housing Institute. A Study on the Measurement Method of Progress and Payment in Apartment Building Construction; Land and Housing Institute: Seoul, Republic of Korea, 2002.
  41. Li, H.; Love, P.E.; Gunasekaran, A. A conceptual approach to modeling the procurement process of construction using petri-nets. J. Intell. Manuf. 1999, 10, 347–353.
  42. Cheng, X.J.; Jin, W. Study on reverse engineering of historical architecture based on 3D laser scanner. J. Phys. Conf. Ser. 2006, 48, 843–849.
  43. Bernat, M.; Janowski, A.; Rzepa, S.; Sobieraj, A.; Szulwic, J. Studies on the use of terrestrial laser scanning in the maintenance of buildings belonging to the cultural heritage. In Proceedings of the 14th Geoconference on Informatics, Geoinformatics and Remote Sensing 2014, SGEM.ORG, Albena, Bulgaria, 17–26 June 2014; pp. 307–318.
  44. Moyano, J.; Justo-Estebaranz, Á.; Nieto-Julián, J.E.; Barrera, A.O.; Fernández-Alconchel, M. Evaluation of records using terrestrial laser scanner in architectural heritage for information modeling in HBIM construction: The case study of the La Anunciación church (Seville). J. Build. Eng. 2022, 62, 105190.
  45. Ding, Z.; Liu, S.; Liao, L.; Zhang, L. A digital construction framework integrating building information modeling and reverse engineering technologies for renovation projects. Autom. Constr. 2019, 102, 45–58.
  46. Hosamo, H.H.; Hosamo, M.H. Digital twin technology for bridge maintenance using 3d laser scanning: A review. Adv. Civ. Eng. 2022, 2022, 2194949.
  47. Park, J.; Kim, S. Case Study Research in Earthwork Site Digitization for Smart Construction. J. Korean Soc. Ind. Converg. 2019, 22, 529–536.
  48. Singh, S.K.; Banerjee, B.P.; Raval, S. A review of laser scanning for geological and geotechnical applications in underground mining. Int. J. Min. Sci. Technol. 2022, 33, 133–154.
  49. Wang, J.; Yi, T.; Liang, X.; Ueda, T. Application of 3D Laser Scanning Technology Using Laser Radar System to Error Analysis in the Curtain Wall Construction. Remote Sens. 2023, 15, 64.
More
Information
Contributors MDPI registered users' name will be linked to their SciProfiles pages. To register with us, please refer to https://encyclopedia.pub/register : , ,
View Times: 206
Revisions: 2 times (View History)
Update Date: 08 Feb 2024
1000/1000
ScholarVision Creations