Citation
Assessment of Three Building Technology Workflows

Material Information

Title:
Assessment of Three Building Technology Workflows Laser Scanning, Lidar Scanning and Photogrammetry and Their Usage
Creator:
Gosavi, Rutuja Narendra
Place of Publication:
[Gainesville, Fla.]
Florida
Publisher:
University of Florida
Publication Date:
Language:
english
Physical Description:
1 online resource (74 p.)

Thesis/Dissertation Information

Degree:
Master's ( M.S.C.M)
Degree Grantor:
University of Florida
Degree Disciplines:
Construction Management
Committee Chair:
ISSA,RAJA RAYMOND A
Committee Co-Chair:
FLOOD,IAN
Committee Members:
GHEISARI,MASOUD

Subjects

Subjects / Keywords:
building -- photogrammetry -- scanning -- technology
Construction Management -- Dissertations, Academic -- UF
Genre:
bibliography ( marcgt )
theses ( marcgt )
government publication (state, provincial, terriorial, dependent) ( marcgt )
born-digital ( sobekcm )
Electronic Thesis or Dissertation
Construction Management thesis, M.S.C.M

Notes

Abstract:
The construction industry has been incorporating building technologies in their daily activities to increase work efficiency. Progress monitoring and inspection are a few of the activities that are carried out every day. Mostly this is done manually, and reports are generated. Several researchers have put forth the importance and benefits of using technologies for such frequent activities. Reality computing is one such method which involves reality capture of activities going on around you. Reality computing includes capturing the reality, processing the data and analyzing the results. Several reality capturing technologies are available in the market such as laser scanners, cameras, Unmanned Aerial Vehicles (UAVs), etc. This thesis assesses three such reality capturing technology workflows: Laser scanning, Mobile Lidar Scanning and Photogrammetry using digital camera. An experiment was set up and scans and photos were obtained for a Virtual Design and Construction (VDC) lab at Rinker hall. The results were processed using industry standard software and the technologies were compared for workflows and affiliated parameters. By assessing the workflows, it was observed that the workflow for lidar scanning was the easiest to carry out however, data processing took up large portion of the time. Cost-wise scanners are on a very high end compared to cameras. The point cloud data obtained from a laser scan was very clean and easier to navigate through. Secondly, an industry survey was carried out using a questionnaire that was distributed amongst construction industry professionals. The intention of the survey was to assess to what extent is the construction industry was using these technologies and what the benefits and limitations of these technologies were from the industry perspective. According to the results, participants rated the benefits higher in comparison to the limitations. However, these technologies are not used very frequently for building inspection and manual inspection is still trusted over them. Yet, participants believe that technology based inspection could yield better results and efficiency over manual inspection. ( en )
General Note:
In the series University of Florida Digital Collections.
General Note:
Includes vita.
Bibliography:
Includes bibliographical references.
Source of Description:
Description based on online resource; title from PDF title page.
Source of Description:
This bibliographic record is available under the Creative Commons CC0 public domain dedication. The University of Florida Libraries, as creator of this bibliographic record, has waived all rights to it worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law.
Thesis:
Thesis (M.S.C.M)--University of Florida, 2018.
Local:
Adviser: ISSA,RAJA RAYMOND A.
Local:
Co-adviser: FLOOD,IAN.
Statement of Responsibility:
by Rutuja Narendra Gosavi.

Record Information

Source Institution:
UFRGP
Rights Management:
Applicable rights reserved.
Classification:
LD1780 2018 ( lcc )

Downloads

This item has the following downloads:


Full Text

PAGE 1

ASSESSMENT OF THREE BUILDING TECHNOLOGY WORKFLOWS: LASER SCANNING, LIDAR SCANNING AND PHOTOGRAMMETRY AND THEIR USAGE By RUTUJA NARENDRA GOSAVI A THESIS PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIA L FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE IN CONSTRUCTION MANAGEMENT UNIVERSITY OF FLORIDA 2018

PAGE 2

2018 Rutuja Gosavi

PAGE 3

To my father, Mr. Narendra Gosavi and mother, Mrs. Kalpana Gosavi

PAGE 4

4 ACKNOWLEDGMENTS I would like to express my sincere gratitude to my thesis advisor Dr. Raymond Issa, School of Construction Management, University of Florida He would always have a solution to my most complex problems. He would ensure that I was performing well and had everything that I needed to perform my thesis successfully. It was very convenient to perform my experiment for the thesis due to easy availability of resources such as laser scanner and digital camera which Dr. Issa readily made available. I would also like to thank CACIM lab assistants, Ralph Tayeh, Fope Bademosi, Nathan Blinn and Richard Kelly who helped me with gathering the data for the experiment, answered my smallest questions and were always there for me. I also really appreciate the help provided by Mr. Gannon Wilder for obtaining the Lidar Scans. I am much obliged to my committee members Dr. Masoud Gheisari and Dr. Ian F lood of A special thanks to Dr. Gheisari for helping me to prepare a quality survey questionnaire. I would like to express my gratitude to the construction indust ry professionals for taking the time to answer my questionnaire. Their valuable replies helped me in obtaining substantial results and deductions. Finally, I would like to thank my parents for their enormous support throughout this journey and the constan t encouragement to keep going. I could not have achieved this without you both. Thank you.

PAGE 5

5 TABLE OF CONTENTS page ACKNOWLEDGMENTS ................................ ................................ ................................ ............... 4 LIST OF TABLES ................................ ................................ ................................ ........................... 8 LIST OF FIGURES ................................ ................................ ................................ ......................... 9 LIST OF ABBREVIATIONS ................................ ................................ ................................ ........ 11 ABSTRACT ................................ ................................ ................................ ................................ ... 12 CHAPTER 1 INTRODUCTION ................................ ................................ ................................ .................. 14 1.1 Overview ................................ ................................ ................................ ........................ 14 1.2 What is the Construction Technology to be Deployed and What are the General Barriers ................................ ................................ ................................ .......................... 16 1.3 Problem Statement ................................ ................................ ................................ ......... 16 1.4 Objectives ................................ ................................ ................................ ...................... 17 1.5 Scope of Research ................................ ................................ ................................ .......... 17 1.6 Summary of Proposed Study ................................ ................................ ......................... 17 1.7 Importance of the Research ................................ ................................ ........................... 18 2 LITERATURE REV IEW ................................ ................................ ................................ ....... 19 2.1 Reality Computing ................................ ................................ ................................ ......... 19 2.2 Augmented Reality ................................ ................................ ................................ ........ 19 2.3 Laser Scanning ................................ ................................ ................................ ............... 20 2.4 Mobile Lidar Scanning ................................ ................................ ................................ .. 22 2.5 Photogrammetry ................................ ................................ ................................ ............ 23 2.6 Laser Scanning Applications ................................ ................................ ......................... 25 2.6.1 Laser Scanning for Geotechnical Works ................................ ........................... 25 2.6.2 Laser Scanning for Quality Ass essment in Construction ................................ .. 25 2.6.3 3D Scanning for Heritage Building Data Recording ................................ ......... 25 2.6.4 Automated Progress Control using La ser Scanning ................................ .......... 26 2.6.5 Acquiring Transportation Measurement Data using Laser Scanners ................ 26 2.6.6 Monitoring Construction Progress of Underground Structures like Tunnels using Laser Scanning Technology ................................ ................................ .... 27 2.6.7 Construction Renovation Documentation by Integrating Laser Scans to BIM ................................ ................................ ................................ ................... 27 2.6.8 Laser Scanners and Software Tools used for Applications Listed in the Literature Review ................................ ................................ .............................. 28 2.6.9 Benefits and Limitations of Laser Scanning from Literature Review. .............. 28 2.7 Lidar Scanning Applications ................................ ................................ ......................... 29 2.7.1 Earthwork Volume Estimation using Lidar Scanning ................................ ....... 29

PAGE 6

6 2.7.2 Health Monitoring of Structures using Lidar Scanning ................................ .... 29 2.7.3 Monitoring Geometry and Deformation of Tunnels ................................ ......... 30 2.7.4 Highway Planning using Lidar Technology ................................ ...................... 30 2.7.5 Development of Shop Drawings using Lidar Scanning ................................ .... 30 2.7.6 As Built Building Information Modelling using Mobile Lidar Technology .... 31 2.7.7 Lidar scanners and Software Tools used for Applications Listed in the Literature Review ................................ ................................ .............................. 31 2.7.8 Benefits and Limitations of Lidar scanning from Literature Review ............... 32 2.8 Photogrammetry applications ................................ ................................ ........................ 32 2.8.1 Dimension Verification using Photogrammetry ................................ ................ 32 2.8.2 Building Inspection using Photogrammetry ................................ ...................... 33 2.8.3 Pipework Progress Tracking using Photogrammetry ................................ ........ 33 2.8.4 3D Modelling of a Historical Building using Photogrammetry ........................ 34 2.8.5 Monitoring of Structural Deformation using Photogrammetry ......................... 35 2.8.6 Survey Mapping for Structural Geology using Photogrammetry ..................... 35 2.8.7 Monitoring of Bridge Load Testing using Photogrammetry ............................. 36 2.8.8 Excavation Volume Computation using Photogrammetry ................................ 36 2.8.9 Digital Photogrammetry for Trenchless Engineering ................................ ....... 37 2. 8.10 Cameras and Software tools used for Applications Listed in the Literature Review ................................ ................................ ................................ ............... 37 2.8.11 Benefits and Limitations of Photogrammetry from the Literature Review ....... 38 2.9 Common Applications for the Three Technologies ................................ ....................... 38 2.10 Research Gap ................................ ................................ ................................ ................. 39 3 RESEARCH METHODOLOGY ................................ ................................ ........................... 40 3.1 Purpose of the Study ................................ ................................ ................................ ...... 40 3.2 Experiment ................................ ................................ ................................ ..................... 41 3.2.1 Location of the Experiment ................................ ................................ ............... 41 3.2.2 Equipment Specifications ................................ ................................ .................. 41 3.2.2.1 Laser Scanner: ................................ ................................ .................... 41 3.2.2.2 Digital Camera: ................................ ................................ .................. 42 3.2.2.3 Lidar Scanner: ................................ ................................ .................... 42 3.2.2.4 Software for Data Processing: ................................ ............................ 42 3.2.2.5 Computer for Data Processing: ................................ .......................... 42 3.3 Description of the Experiment: ................................ ................................ ...................... 42 3.3.1 Data collection using Laser Scanner: ................................ ................................ 42 3.3.2 Data collection using Mobile Lidar Scanner: ................................ .................... 44 3.3.3 Data Collection using Digital Camera: ................................ ............................. 45 3.4 Workflows for the Three Technologies and their Comparison ................................ ..... 46 3.4.1 Laser Scanning ................................ ................................ ................................ .. 46 3.4.2 Lidar Scanning ................................ ................................ ................................ .. 47 3.4.3 Photogrammetry using Digital Camera ................................ ............................. 48 3.5 Comparison of the Three Technologies on the basi s of Various Parameters ................ 49 3.6 Survey Questionnaire ................................ ................................ ................................ ..... 49 3.6.1 Data Collection ................................ ................................ ................................ .. 49 3.6.2 Description of the Questionnaire and Analysis ................................ ................. 50

PAGE 7

7 4 RESULTS AND DISCUSSION ................................ ................................ ............................. 52 4.1 Analysis of the Exper iment ................................ ................................ ........................... 52 4.2 Analysis of the Survey Questionnaire Results ................................ ............................... 52 4.3 Likert scale questions analysis ................................ ................................ ....................... 57 5 CONCLUSION AND FUTURE RECOMMENDATIONS ................................ ................... 59 5.1 Conclusion ................................ ................................ ................................ ..................... 59 5.2 Limitations ................................ ................................ ................................ ..................... 59 5.3 Recommendations for Future Research ................................ ................................ ......... 60 APPENDIX A IRB APPROVAL ................................ ................................ ................................ .................... 61 B INFORMED CONSENT FORM ................................ ................................ ............................ 63 C ONLINE QUESTIONNAIRE ................................ ................................ ................................ 65 LIST OF REFERENCES ................................ ................................ ................................ ............... 69 BIOGRAPHICAL SKETCH ................................ ................................ ................................ ......... 74

PAGE 8

8 LIST OF TABLES Table page 2 1 List of laser scanners and software processing tools from literature review .................... 28 2 2 List of benefits of laser scanners from the literature review ................................ ............. 28 2 3 List of limitations of laser scanners from the literature r eview ................................ ........ 29 2 4 List of laser scanners and software processing tools from literature review .................... 31 2 5 List of benefits of lidar scanne rs from the literature review ................................ ............. 32 2 6 List of benefits of lidar scanners from the literature review ................................ ............. 32 2 7 List of cameras and so ftware processing tools from literature review ............................. 37 2 8 List of benefits of photogrammetry from the literature review ................................ ........ 38 2 9 List of benefits of photogrammetry from the literature review ................................ ........ 38 2 10 List of common applications for three technologies ................................ ......................... 39 3 1 Compa rison of technologies based on various parameters ................................ ............... 49

PAGE 9

9 LIST OF FIGURES Figure page 2 1 Laser Scanner ................................ ................................ ................................ ..................... 20 2 2 Pulse syst em laser scanner ................................ ................................ ................................ 21 2 3 Pulse shift laser scanner ................................ ................................ ................................ .... 21 2 4 Traditional Mobile Lidar Scanner ................................ ................................ ...................... 22 2 5 Ne w Mobile Lidar Scanner ................................ ................................ ................................ 23 2 6 Image of a UAV ................................ ................................ ................................ ................. 24 2 7 Image of a Digital Camera ................................ ................................ ................................ 24 3 1 Florida ................................ ................................ ................................ ................................ 41 3 2 Steps for initial setup of a LASER scanner ................................ ................................ ...... 43 3 3 Steps for initial setup of a mobile LIDAR scanner ................................ ........................... 44 3 4 Image of camera used for capturing photos ................................ ................................ ....... 45 3 5 Workflow for Laser Scanning. ................................ ................................ ........................... 46 3 6 Workflow for Lidar Scanning. ................................ ................................ ........................... 47 3 7 Workflow for Photogrammetry. ................................ ................................ ......................... 48 4 1 Venn diagram denoting educational backgrounds of participants where Sample N=75. ................................ ................................ ................................ ................................ 54 4 2 Bar chart diagram denoting number of years of exp erience of participants in the construction industry where Sample N=75. ................................ ................................ ....... 54 4 3 Bar chart diagram denoting the association of participants with several professional entities where Sample N=75 ................................ ................................ ............................. 55 4 4 Bar chart diagram denoting range for annual volume of work performed by the ................................ ................................ .. 55 4 5 Bar chart diagram denoting frequency of usage of different software for data processing where Sample N=133. ................................ ................................ ..................... 56 4 6 Bar chart diagram denoting technology usage for building inspection where Sample N=75 ................................ ................................ ................................ ................................ .. 56

PAGE 10

10 4 7 Bar chart diagram denoting building technology usage for activities other than building inspection where Sample N =75 ................................ ................................ .......... 57 4 8 Likert scale statistical calculations ................................ ................................ ..................... 57

PAGE 11

11 LIST OF ABBREVIATIONS AI Artificial Intelligence AR Augmented Reality BIM Buildin g Information Modelling GPS Global Positioning System IMU Inertial Measurement Unit IRB Institutional Review Board LASER Light Amplification by Stimulated Emission of Radiation QLASSIC Quality Assessment S ystem in construction RAM Random Access Memory SF Square Feet UAV Unmanned Aerial Vehicle

PAGE 12

12 Abstract of Thesis Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Master of Science in Construction Management ASSESSMENT OF THREE BUILDING TECHNOLOGY WORKFLOWS: LASER SCANNING, LIDAR SCANNING AND PHOTOGRAMMETRY AND THEIR USAGE By Rutuja Gosavi August 2018 Chair: Raymond Issa Major: Con struction Management The construction industry has been incorporating building technologies in their daily activities to increase work efficiency. Progress monitoring and inspection are a few of the activities that are carried out every day. Mostly this is done manually, and reports are generated. Several research ers have put forth the importance and benefits of using technologies for such frequent activities. Reality computing is one such method whi ch involves reality capture of activities going on aroun d you. Reality computing includes capturing the reality, processing the data and analyzing the results. Several reality capturing technologi es are available in the market such as laser scanners, cameras, Unmanned Aerial Vehicles (UA Vs), etc. This thesis assesses three such reality capturing technology workflows : Laser scanning Mobile Lidar Scann ing and Photogrammetry using digital camera. An experiment was set up and scans and photos were obtained for a Virtual Design and Construction (VDC) lab at Rin ker hall. The results were processed using industry standard software and the technologies were compared for workflows and affiliated parameters. By assessing the workflows it was observed that the workf low for lidar scanning was the easiest to carry out however, data processing took up large portion of the time. Cost wise scanners are on a very high end compared to cameras. The point cloud data obtained from a laser scan was very clean and easier to navigate through. Secondly, an industry

PAGE 13

13 survey was carr ied out using a questionnaire that was distributed amongst construction industry professionals. The intention of the survey was to assess to what extent is the construction industry was using these technologies and what the benefits and limitations of thes e technologies were rated the benefits higher in comparison to the limitations. However, these technologies are not used very frequently for building inspection and manual inspection is still trust ed over them. Yet, participants believe that technology based inspection could yield better results and efficiency over manual inspection.

PAGE 14

14 C HAPTER 1 INTRODUCTION 1.1 Overview The construction industry contributes to a large portion of a United States, the construction industry was a 900 billion dollar industry in 201 6 as reported by Statista ( https://www.statista.com/topics/974/construction/ ). The construction industry has been increasingly adopting technology i nnovations to resolve workforce issues. As per the annual construction report presented by JLL ( 2017 ) through the past two years, the construction industry has been adopting several technologies to increase work productivity and the three most promising t echnologies that were adopted to create higher quality of construction were Building Information Modelling (BIM); Prefab and Offsite Construction; Artificial Intelligence (AI) and Big Data. One of the most important facets where technology needs to be im plemented is for monitoring construction progress. Construction progress control is one of most critical activities under construction management. Typically progress monitoring is done by humans and reports are created based on their observations. This met hod is generally time consuming and the quality of data or reports obtained through manual inspection is generally low (Fard et al 2009). Through the years the data collection method is moving towards more automated means and is getting streamlined. Real time accurate data acquisition is the moto behind these technologies. Reality capturing is the process of scanning an object, building or structure and producing point clouds and then a 3D model out of it which can be used for several construction applic ations such as monitoring, renovation, etc (Dai et al. 2013). The development of reliable and time efficient techniques for reality capturing has gained increased importance because of the added project complexities that necessitates frequent updates for visualization, optimization and co ordination related applications (L im et al. 2014). Several technologies are utilized to

PAGE 15

15 capture this real time data on the site. The most common one is the total station equipment. Several high precision total stations with an error of 2 3mm are available. But depending on the size of the site, many readings have to be taken which is a time consuming process (Dai et al 2013). Even more advanced technologies have been used for reality capturing and monitoring which can be used for to develop 3D models with the required details. Some of these techniques are image based reconstruction using daily site photos, three dimensional laser scanning, mobile laser scanning and combination of photographs and laser scans. Several co mparison studies have been carried out between these technologies to understand their accuracy and efficiency in different circumstances. Researchers have compared photogrammetry against laser scanning where the accuracy of both the tools was less than 5mm however, processing time and quality of point clouds was better in laser scanning (Faltynova et al. 2016). Several use cases have been found for lidar technology where data was captured, and 3D models were generated (Zhang et al. 2005, Verma et al. 2006). There also several applications on automated real time monitoring that links activities, visual data and time and provides automated progress reports (Abeid et al. 2003). Computer vision technology was used to associate captured images to the quantity of work to show daily progress of the superstructure of the building (Zhang et al. 2005). These technologies come hand in hand with benefits as well as limitations however as long as there is a desire for greater project control, reality capturing technology should continue to develop. This research aims to compare three such reality capturing technologies for workflows, cost, quality of data and time parameters: Laser Scanning, Lidar Scanning and Photogrammetry. At the same time the research also intends to investigate the status or usage of these technologies in the construction industry for construction inspection.

PAGE 16

16 1.2 What is the Construction T echnology to be D eployed and W hat are the General B arriers The combination of construction methods, construction resources, work tasks and project influences that define the path of performing construction operations to accomplish the desired aim by utilizing efficient tools and improved methods is defined as construction technology ( Yu et al. 2008 ). Technology revo lution has helped to bring a higher level of advancement and efficiency in construction practices that traditional practices could not achieve. But, very few construction practitioners are ready to accept and involve technology in their daily work practice primarily because they are hesitant to trust the results obtained using technological tools and sometimes simply possess strong resistance to change. Despite being aware of the fact that technology would essentially aid in reducing human effort and increa se efficiency of work, not everyone is ready to adopt these new tools and want to stick to traditional methods due to reasons such as high cost, requirement of training, etc ( Zack 2016). 1.3 Problem Statement Several technologies and tools such as realit y computing are available in order to aid the building inspection activity. But not all construction companies prefer using them for various reasons or they prefer using one technology over the other. Hence, the question is, to what extent are reality comp uting tools used for building inspection? Which is the most widely used reality computing tool amongst the three tools: Laser Scanning, Lidar Scanning and Photogrammetry? What are the advantages and limitations of using these tools over manual inspection? Primarily how do cost, quality, time and workflow factors affect the acceptance of these tools for building inspection?

PAGE 17

17 1. 4 Objective s This study mainly focuses on assessing the usability, benefits and limitations of three Reality computing tools: Laser S canning, Lidar Scanning and Photogrammetry for purpose of efficient construction inspection. The specific objectives of the study are: 1. C ompare the 3 tools for the following parameters: workflow, cost, time and quality of data obtained by conducting an act ual experiment. 2. A nalyze the usability, benefits and limitations of the three reality computing tools in the real construction industry by conducting a survey and performing statistical analysis to draw results 1. 5 Scope of Research The primary focus of this research is to understand how the triple constraints: Time, Cost and Quality and Workflows vary for three different building inspection tools. At the same time, the research also concentrates on analyzing the level of acceptance these tools have recei ved for building inspection activity and what are their benefits and limitations in the construction industry. 1. 6 Summary of Proposed Study Several technologies can be used to obtain real time data on the state of construction site s One of the prime fac tors affecting the successful delivery of the project is accurate and timely capturing of information and construction technology tools can aid in acquiring this data with greater efficiency ( Dai et al. 2013). Despite their benefits, they are not always us ed as building inspection tools and many construction companies still prefer using manual method s of inspection ( Memon et al. 2015 ). Although companies are aware of the benefits of using these tools, they may not want to use them for several reasons and s till rely on human inspection to obtain site progress or inspection reports. Also, some companies may prefer one tool over the usability, benefits and limitations tow ards the 3 building inspection tools: Laser Scanning, Lidar

PAGE 18

18 Scanning and Photogrammetry by conducting an industry survey. The study shall also compare the three technologies for the following parameters: Workflow, Cost, Time, Quality based on an actual exp eriment. 1. 7 Importance of the Research This research will help in understanding the differences in parameters such a cost, time, quality and workflow for the three reality computing tools. This may help users in their selection of a particular technolo gy for future building inspections. The results of the industry survey questionnaire help in understanding the major factors that affect the utilization of these tools in construction inspection. In general, the research will help provide an overview of th e perception of reality computing tools in the real time construction industry. The results from the review may help reality computing tools manufacturers in taking these factors into consideration while selling their tool.

PAGE 19

19 CHAPTER 2 LITERATURE REVIEW 2. 1 R eality C omputing Reality computing is the use of reality capture in conjunction with computer aided simulation that enables faster design and solutions (Autodesk 2014) It intends to break down the barriers between physical and digital world for anyone engaged in the design, delivery and management of physical things. Reality computing technologies help to capture spatial information about the physical world which can then be integrated in construction processes to obtain accurate data. Realistic Augmen ted Reality (AR) representations are obtained by using reality computing technologies (Issa 2015). As built information is used for many applications in construction such as project documentation, quantity take off, quality control and progress monitoring. Hence, accurate and timely capturing of as built information plays an important role for a succ essful delivery of the project ( Dai et al. 2013). 2.2 Augmented Reality AR in simple terms can be defined as user interaction with the 3D environment. It give s a view of the real world environment where elements are superimposed in the form of sounds, digital information or videos. The AEC industry has embraced this technology for improving overall construction management productivity. As planned and as built s tatus can be monitored using the simulation and visualization of construction activities (Shin et al. 2008). Piekarski et al. (2003) listed several Realistic Augmented Reality capturing techniques and one of the methods suggested by them was a laser scanne r. AR for 3D modelling of a construction site application was discussed by Wang (2006). He put forth the issues that construction projects generally face such as time crunch, non availability of 3D model data for easier understanding and faster decision ma king. AR using photogrammetry to create 3D models was suggested by him as one of the ways that could address this concern. Realistic AR has had several applications in the AEC

PAGE 20

20 industry. To obtain these AR representations, reality capturing tools such as L aser scanner or cameras can be used for 3D modelling. 2.3 Laser Scanning A Light Amplification by Stimulated Emission of Radiation ( LASER) scanner is a device that operate s by emitting a laser beam to the required direction and waits for it to travel back and using the beam as means to measure distances from the sensor to the targeted object (P feif er et al. 2007). 3D location of the targeted surface can be determined using this technology. When light gets emitted in a regular pattern, a dense sampling of t he object surface is obtained. Thus, it is a non destructive and non contact technology used for capturing the digital shape of the targeted object. The level of details obtained from a laser scan depend on the scan and resolution settings that the equipm ent has been set to as well as the distance to the object. Figure 2 1 shows an image of a laser scanner mounted on a tripod stand. Figure 2 1. Laser Scanner ( Source: Reprinted with permission from C.R. Kennedy Survey Solutions website https://survey.crkennedy.com.au/categories/_products/3dlaserscanning ( June 18, 2018) ). Laser scanners based on various principles to measure distances are available in the market. Specifica lly, for building documentation, pulse systems or phase shift systems are used.

PAGE 21

21 In pulse systems as denoted in Figure 2 2 the distance between the scanner location and the surface of the object is measured by the time of flight needed by a single pulse of reflected shift system as denoted in F igure 2 3 the distance between the scanner and the object is calculated by measuring the phase shifts in the waves of infrared light. Pulse systems are suitab le for larger ranges (>100m) and phase shift systems are ideal for shorter distances but are generally faster in their operations. The output obtained from a laser scanner is a point cloud. A point cloud is a set of data points in a defined coordinate syst em that represents an external surface of the measured object (Vosselman et al 2010). The point cloud data can be processed in various software in order to obtain a 3D model. Several brands of 3D laser scanners are used in construction related applicati ons including Trimble, FARO Focus, Leica, CYRAX and many others. Figure 2 2. Pulse system laser scanner ( Source: Reprinted with permission from SurvTech Solutions website http://floridalaserscanning.com/3d laser scanning/how does laser scanning work/ ( June 22, 2018) ). Figure 2 3. Pulse shift laser scanner ( Source: Reprinted with permission from SurvTech Solutions website http://floridalaserscanning.com/3d laser scanning/how does laser scanning work/ (June 22,2018 ) ).

PAGE 22

22 2.4 Mobile Lidar Scanni ng Light Detection and Ranging (LIDAR ) is a laser imaging technology in tegrated with Geo positioning technology in order to obtain geo referenced spatial data. This technology is used to capture scenes with a higher level of accuracy. Faster, more accurate and comprehensive 3D data can be obtained from scans using Mobile Lida r Technology. Mobile lidar can be fixed on any mobile platform such as a van, boat or vehicle in case of ground based lidars. Since there are several obstructions like trees, buildings, etc on the ground, a more sophisticated navigation solution needs to b e used. Higher accuracy of sensors and processing solutions are employed to the equipment to maintain higher accuracy of data during periods of Global Positioning System ( GPS ) outages (Kiziltas et al. 2008) A mobile lidar system is an integration of subsy stems such as laser scanner, GPS technology and Inertial Measurement Unit (IMU) for orientation measurement of the moving platform and a software unit to process the recorded data (Ussyshkin 2009). Traditionally the mobile lidar units would be mounted on a vehicle as shown in F igure 2 4 or a mobile platform but now handheld mobile lidars as shown in F igure 2 5 are being used ( Lim et al. 2014). Figure 2 4. Traditional Mobile Lidar Scanner ( Source: Reprinted with permission from Earth Imaging journal websit e, https://eijournal.com/print/articles/consider the benefits of mobile lidar for transportation projects (June 19,2018)).

PAGE 23

23 Figure 2 5 New Mobile Lidar Scanner ( Source: Reprinted with permission from Paracosm website, https://paracosm.io/ (May 18, 2018) ). 2.5 Photogrammetry The term photogrammetry was first introduced by an architect Albrecht Meydenb auer who performed the first photogrammetric surveys in 1867 ( Grimm 2007) Photogrammetry includes performing indirect measurements of natural space by use of photography. Photogrammetry is the science that makes possible to obtain 3D measurements of objec ts from photographs taken from different perspectives (Blachut et al. 1988) The 2D photographs are extracted and mapped into a 3D space to create a 3D model. A photograph is recognized as a highly accurate mode of receiving information. Thus, photographs have been widely used as records of the site work particularly for construction control and inspection ( Kim et al 2008). Photogrammetric techniques can be applied to virtually any source of imagery, whether it comes from 35 mm digital cameras or an earth orbiting satellite. As long as the images are captured with stereoscopic overlap, one can derive accurate 3D data at a very wide range of scales ( Mathews 2008). Photogrammetry can be classified into two types; long range photogrammetry and short range pho togrammetry. Close range photogrammetry is used when the object to be measured is less than about a 300 met er s and the cameras are positioned close to it. Close range

PAGE 24

24 photogrammetry is usually done by using Digital cameras or mobile phone cameras. An image of a digital camera has been shown in Figure 2 7. 360 degree virtual reality (VR) cameras are also used for close range photogrammetry. Long range photogrammetry is generally done using Unmanned Aerial Vehicles (UAVs) as shown in F igure 2 6 and the height is mostly over 300m ( Mathews 2008). Figure 2 6. Image of a UAV ( Source: Photo courtesy of David Roca et al. (2013). cost (2013) 128 135. Figure 2 7 Image of a Digital Camera ( Source: Reprinted with permission website https://www.nikonusa.com/en/index.page ( June 12, 2018) )

PAGE 25

25 2.6 Laser S canning Applications 2.6.1 Laser Scanning for G eotechni cal W orks Laser scanning technology was used to create a 3D model of some critical locations of the Palace Bridge at St. Petersberg i n Russia The bridge was undergoing some renovations and the engineers required information related to certain piers and th e truss attachments. Since time restriction existed, the survey was conducted using a laser scanner. Also, the data had to be gathered without closing the traffic which was a significant challenge as the traffic would cause vibration in the piers leading t o inconsistent readings. Using a Riegl VZ 400 laser scanner for external survey and Z+F IMAGER 5006 scanner for internal survey of equipment and mechanisms, data was obtained. Point cloud processing was done using Leica Cloud and Worx XTools software. This method was time efficient and the data obtained was of higher quality and more complete (Kanashin et al. 2017). 2.6.2 Laser Scanning for Quality Assessment in Construction Muhammad et al. (2016) set up an experiment u sing a Leica ScanStationC10 laser sc anner and Leica cyclone point cloud processing software T wo precast concrete blocks of known dimensions were laser scanned and the point clouds were processed in the Leica cyclone software. The dimensions were then verified on the software. The (Quality A ssessment System in construction) QLASSIC was carried out and the accuracy results were high for the laser scanned data. When objects have a very small level of tolerance, laser scanner can be used to get accurate results within a short period of time. The 3d point cloud model can also help in identifying defects. However the cost of the equipment is high. 2.6.3 3D Scanning for Heritage B uilding Data R ecording Using 3 different laser scanners Cyrax 2500, MENSI S25 and LEICA HDS scanners, Boehler et al. (2004) scanned and the results were compared to photogrammetry results. It was found that the as built conditions can be

PAGE 26

26 recorded faster using photogrammetry. However, when it comes to complex shapes and i rregular structures which the heritage buildings possessed, 3D scanning would give better results. Compared to photogrammetry, laser scanning is more expensive primarily due to the initial cost that is invested in the apparatus. 2.6.4 Automated Progress C ontrol using Laser Scanning Zhang et al ( 2013) carried out an experiment for assessing how laser scanning can be used for monitoring progress on a construction project. He used Leica HDS 600 scanner and Leica Cloud point cloud processing software for the e xperiment. He carried out an experiment by loading four small paper material columns equally for four consecutive days and observed the shrinkage in the column height through these days using a laser scanner and associated it to a schedule ie. a 4D model The shrinkage of the column and the schedule were associated to each other. This method proved that it was cost effective and time saving compared to traditional methods. Automated progress control using laser scanner can be achieved but it has certain l imitations. The test in this experiment was conducted in convenient conditions but that may not be the condition on an actual site. Shape of the objects is not always definable as it was for the laboratory experiment. Laser scanning equipment are expensive however no human vs laser scanner cost analysis has been carried out. 2.6.5 Acquiring Transportation Measurement D ata using Laser Scanners Transportation projects are complex ones and require constant surveying and data acquisition. Laser scanning owin g to its benefits was used by Jaselskis et al. (2005) for carrying out a test experiment using CYRAX 2500 Scanner and CYCLONE software for point cloud processing. The laser scanner was set up at a highway intersection in Iowa and several scans were taken. The number of scans and time required for each scan was noted. Through this experiment it was noted that this method can be extremely useful where safety may be an issue.

PAGE 27

27 The time required to complete the entire set up was almost 2 times higher than antici pated. Cost factor was 30% higher compared to traditional methods but could be improved as the scanning crew would become more efficient users. 2.6.6 Monitoring Construction Progress of Underground S tructures like T unnels using Laser Scanning T echnology F or complex projects such a tunnel construction, survey engineering has significant impacts on the technical and economic aspects of the project. Laser scanning was considered as one of the potential technologies that could aid in simplifying the surveying process by Gikas (2012) Using the Leica Geosystems ScanStation Laser Scanner, two tunnels in Greece; The Tempi T1 tunnel and the N. Ikonio tunne l were scanned to obtain required data. They both were 1.9 km and 3.4 km long respectively. The data was process ed using the Leica Geosystems Cyclone software. Additional scans were taken using an older technology scanner, the Callidus CP 3200 scanner and processed using Mensi GS Series software. Area and volume computations for the tunnel were doing using laser sca nning. Also, the metal formwork liner location and progress monitoring of the construction of the tunnels was done with these laser scanners. It was observed that the computation values using traditional surveying method and both laser scanners had minor d ifferences. 2.6.7 Construction Renovation Documentation by I ntegrating Laser Scans to BIM A research was conducted by Falt i nova et al. (2016) which focused on finding out easier techniques to document building data. In the research he took an example of a 3 story building faade which is located in Prague, Czech Republic. The building facade needed to be renovated. Hence, laser scans were taken using Surphaser 25HSX laser scanner and the data processing was done using Geomagic Studio Software. Through hi s research he understood that higher point density can be achieved by using higher scanning resolution or by lowering the distance between the object and the scanner upto a certain point.

PAGE 28

28 2. 6.8 Laser S canners and Software T ools used for Applications L ist ed in the Literature R eview Table 2 1 provides a list of laser scanners and software tools obtained through the literature review Table 2 1. List of laser scanners and software processing tools from literature review Laser scanner Software Author Riegl VZ 400, Z+F IMAGER 5006 Leica Cloud, Worx Xtools Kanashin et al (2017) Leica ScanStation C10 Leica Cyclone Muhammad et al. (2016) Cyrax 2500, MENSI S25 and LEICA HDS Not mentioned Boehler et al. (2004) Leica HDS 6000 laser scanner Leica Cyclone Zhang et al (2013) CYRAX 2500 Cyclone software Jaselskis et al (2005) 2.6.9 Benefits and Limitations of Laser Scanning from Literature R eview. Table 2 2 and 2 3 list the benefits and limitations of laser scanners as observed from the literatur e review respectively. Table 2 2 List of benefits of laser scanners from the literature review Benefits Author Higher Time efficiency Kanashin et al. 2017, Zhang et al. 2003, Dai et al. 2013 Higher Quality of data Kanashin et al. 2017, Dai et al. 2013 Availability of accurate data for objects with smaller level of toler a nce Muhammad e t al. 2016 Easier mode of identifying defects Muhammad e t al. 2016 Easier method to capture objects with complex shapes Boehler et al. 2004 Cost effective Zhang et al. 2013 Easy access to hard to reach places Jaselskis et al. 2005

PAGE 29

29 Table 2 3 List of limitations of laser scanners from the literature review Limitations Author High cost of equipment Muhammad e t al. 20 16, Boehler et al. 2004, Zhang et al. 2013, Jaselsk is et al. 2005 Falt i nova et al. 2016, Dai et al. 2013 Irregular data obtained due to non ideal conditions Zhang et al. 2013 Minor differences in data obtained from traditional methods versus laser scanners Gikas 2012 Scanning quality can be improved by using scanners with higher resolution Falt i nova et al. 2016 Not feasible for low budget small projects Dai et al. 2013 Requirement of large number of scans El Hakim et al. 2004 For complex projects, photogrammetry should be combined with laser scanning Abdelhafiz 2009 2.7 Lidar Scanning Applications 2.7.1 Earthwork Volume E stimation using Lidar Scanning By integrating GPS technology to a traditional laser scanner, the author Du et al. (200 7 ) suggested a technique to estimate the cut and fill volume for a landslide earthwork. Since the area was a danger zone owing to the recent landslide, laser scanning was suggested as a suitable method compared to the traditional methods such as triangulation. Dibit Geoscanner was used for scanning purpose and a GPS was set to identify the location. The resultant volumes obtained were nearly accurate and the author suggested that the technology can mainly be used where safety is a concern and is also a time saving option compared to traditional methods. 2.7.2 Health Monitoring of S tructures using Lidar Scanning The actual behavior of structural elements may vary from the initial prediction through calculations due to several changes like environmental loads, fatigue due to live loads, etc. Hence, their periodic moni toring is required. The author s Park et al (2007) suggested that Lidar scanning be used to observe these slight movements of structures. An experiment was set up where a steel beam was loaded at known loads and the displacement was noted using Lidar scans. The displacements were also calculated using linear variable displacement transducers

PAGE 30

30 (LVDTs) and the results were compared. Traditional laser scanners would give a maximum error of upto 10mm but, with the use of Lidar scanning, the maximum error obtained was less than 1mm and equivalent to the LVDT values. However, Lidar scanners possess benefits over LVDTs and other sensors such as, Lidar scanners need not be attached to the building unlike LVDTs which is costly and sometimes impractical to reach the str ucture. Also, there is no wiring cost associated. However, the initial cost of the scanner is a concern. 2.7.3 Monitoring Geometry and Deformation of T unnels Tunnel monitoring can be done using Lidar scanning technique was first researched and documented in 2006. Wang et al. ( 2006) carried out a literature review on the usage of scanning for tunnel monitoring and found out that scanning has been used to receive information on as builts of tunnels such as deformation measurement and feature extraction like cross sections and construction monitoring. 2.7.4 Highway P lanning using Lidar Technology The Department of Transportation (DOT) is continuously seeking more and more convenient methods of obtaining accurate terrain information. Aerial photogrammetry has its own limitations such as narrow window during the year due to weather conditions. Hence, LIDAR was considered as an option. A project was undertaken by the Iowa DOT to acquire terrain data of a 46 mile corridor. By using conventional mapping methods the estimated time required for obtaining the details was 24 months but by using Lidar Technology, the same could be achieved within 13 months. In terms was cost, lidar was found to have achieved 50% more savings compared to photogrammetric mapping ( Vene ziano et al. 2002). 2.7.5 Development of Shop D rawings using Lidar Scanning A pilot study was conducted by Holley et. al (2014) to understand the feasibility of using Lidar technology for producing shop drawings for gypsum panels and measuring it against actual

PAGE 31

31 conditions. Since gypsum panels are used to a great extent in construction, their overall productivity needs to be improved and it would significantly impact the project. Leica C10 high definition scanner was used for scanning purpose and Cyclone s oftware was used for the analysis. On analysis it was found that further research could help in obtaining accurate shop drawing results. 2.7.6 As Built Building Information Modelling using Mobile Lidar Technology Using a mobile lidar scanner, a 4 storey building at the University of New South Wales was scanned by Lim et al. (2014) and one zone of the building was selected for data processing and the required dimensions were acquired. The lidar acquired dimensions were compared to the dimensions acquired b y traditional method where high level of accuracy was achieved compared to other methods. However, modelling the opening dimensions and decorative items was still found challenging. Yet, the mobile lidar still stood out in terms of its benefits such as red uction in time spent in acquiring the data and the elimination of tripod stands and extended time for each scan. Owing to the accuracy obtained through the results of the experiment, this method may still not provide very satisfactory results where pipes a nd electrical objects are involved as they require even higher level of accuracy. 2.7.7 L idar scan ners and Software T ools used for Applications L isted in the Literature R eview Table 2 4 provides a list of l idar scanners and software tools obtained through the literature review Table 2 4 List of laser scanners and software processing tools from literature review Lidar scanner Software Author Dibit Geoscanner Not mentioned Du et al. 2007 Leica C10 Cyclone Holley et al. 2014

PAGE 32

32 2.7.8 Benefits and Limit ations of Lidar scanning from Literature Review Table 2 5 and 2 6 list the benefits and limitations of lidar scanners as observed from the literature review respectively. Table 2 5 List of benefits of lidar scanners from the literature review Benefits Aut hor Higher time efficiency Du et al. 2007, Samsung et al. 2014 Accurate results Du et al. 2007, Paul Holley et al. 2014 Reduction in errors Park et al. 2007 Easier access to hard to reach places Park et al. 2007 Ability to use in all weather conditio ns Veneziano et al. 2002 Cost saving for big projects eg. Road mapping Veneziano et al. 2002 Elimination of tripods Lim et al. 2014 Table 2 6 List of benefits of lidar scanners from the literature review Limitations Author Higher initial cost Park et al. 2007 Difficulty with respect to modelling of decorative items Lim et al. 2014 Difficulty in obtaining data with very high level of accuracy eg. Pipes, electrical objects. Lim et al. 2014 2.8 Photogrammetry applications 2.8.1 Dimension Verificatio n using P hotogrammetry Dai et al ( 201 4 ) carried out an experiment of using photogrammetry technique to check the dimension quality of precast facades that were installed on high rise buildings in dense urban cities. Generally checking for such a huge quant ity of material is done simply by selecting random samples from a batch of items and the dimensions are verified manually. But with the proposed method, each faade panel was checked for their dimensions and quality. They used Canon Eos SLR 400D camera wit h a resolution of 10MP and shooting distance was set within 6

PAGE 33

33 m. Using this method, they were able to achieve 50% savings on manpower and 80% savings with respect to time invested in inspection. One of the prime benefits of this method is the ability to ca lculate measurements and check the quality for locations that are hazardous to reach. However, this method lacked accuracy mainly due to system errors caused by distortion of camera lens and random error due to human factors. 2.8.2 Building Inspection usi ng Photogrammetry Dai et al. ( 2014) in 2014 carried out another experiment to figure out how photogrammetric techniques can be improved to ensure that we get better results. Hence, three objects were considered; a side walk, a retaining wall and a storage building. The photogrammetry images were obtained using two different camera models: Canon EOS rebel T3i and Canon EOS 60D. Conditions such as relative position of reference lines, overlapping of images and location of camera parameters were changed and th e best scenario was determined to receive accurate results. However, the best scenario parameters are not valid for every situation and suffers difficulties while constructing texture less areas such as window glass and the inability to create point clouds of scenes requiring high densities. Also they were unable to define a quantitative relationship between data accuracy and affecting factors such as image resolution, camera type, etc. 2.8.3 Pipework Progress T racking using Photogrammetry Ahmed e t al. ( 2012) proposed that photogrammetry is a cheaper and more viable option compared to traditional methods like total station and laser scanning for monitoring project progress. Using Canon XSi 450D camera, images were captured for the building piping system a nd using a photo processing software, point clouds were created. Such images and point clouds were taken several times to create an as built 3D model and overlapping of point clouds was carried out to understand what progress has been done compared to the previous data. The

PAGE 34

34 author concluded that hand held camera for inspection compared to manual inspection is much more practical and economical solution. An affordable anti shake stabilization lens can be used and there are no health or safety associated wit h using cameras. It can also work in a wider range of temperatures compared to a laser scanner. 2.8.4 3D Modelling of a Historical Building using P hotogrammetry Liu ( 2014 ) created a 3D model using photogrammetry of a historical building. Using A Canon EO S Rebel T3i Digital Single Lens Reflex camera images were taken for the entire building for the interior and the exterior parts. The images were stitched using Autodesk Stitcher software and a 3D model was created using AutoDesk image M odel l er 2009. The 3D image based model and old CAD model was compared by means of interviews and the general notion was that 3D images based model portrayed a better as built condition and favorable decisions can be made using the model compared to the CAD model. The time req uired for creating the image based model would be equivalent to the time required by architects to generate an as built set of drawings. A similar research was carried out by Arias et al. (2015) to demonstrate photogrammetry as a means of data collection for architectural documentation. He carried out the photogrammetry of an old industry building using Kodak Dx3500 camera and Photomodeler Pro 4.0 for developing a 3D model. The author mainly intends to use this method for data preservation and for easier availability of metrics of the building since plans were either hand drawn in the old days or they may not be available. In such times this method proves useful. He suggests that this method is a cost friendly option but prior planning about photogrammetry could help in achieving time reduction and optimized results.

PAGE 35

35 2.8.5 Monitoring of Structural D eformation using Photogrammetry Wang et al. (2010) suggested that Photogrammetry can be an efficient means of monitoring structural members like membrane struc tures. Monitoring in civil engineering requires high level of precision and faster results so that immediate action can be taken to avoid any further damage if noticed. To analyze this issue an experiment was set up for monitoring the testing, construction and as built condition of a membrane structure using photogrammetry as he believed that it is a cost friendly and more accurate method. Two cameras, AVT Oscar F 810C/8 megapixel and Nikon 300 were used for capturing the images. PhotoModeler Pro and Vision Metrology System (VMS) were the software using for photogrammetric processing. One of the cameras was handheld while the other was fixed on a tripod. The one on the tripod gave out better results and hence stability carried high importance for acquiring a ccurate data. Target points need to be fixed on the area that is photographed especially if it is light colored for better identification. Also if large amount of data is acquired, significant time is spent in data sorting and filing. Overall the method w as found to be cheaper compared to traditional methods and more time efficient than measuring targets by other sensors. 2.8.6 Survey M apping for Structural Geology using P hotogrammetry Bemis et al. (2014) put forth a work flow to obtain photogrammetric d ata using DSLR camera and a camera installed on an Unmanned Aerial Vehicle (UAV). Images obtained from both a UAV and the camera were processed using Agisoft PhotoScan Software and the images were obtained using Go Pro camera. Through the experiment, the author found that open areas it is better to have certain amount of diffused lighting rather than strong reflective contrasts. Also obtaining images from poorly distributed locations can affect the model accuracy severely. Also UAVs could cover a larger a rea compared to digital cameras in a shorter span of time. Further this method is also a safer means of data acquisition.

PAGE 36

36 2.8.7 Monitoring of Bridge Load Testing using P hotogrammetry The author Velenca 2008 suggested that Photogrammetry could be an ef ficient method for structural deformation monitoring compared to traditional methods. In order to study this, he set up an experiment for a long span RC beam and steel beam to column connection. Two cameras were used : Nikon D70 and Olympus C8080 for obtai ning photographs. When the results were reliable in the laboratory, the same method was using for structural monitoring of a photogrammetry were proven to be of high ac curacy and faster results were obtained. Compared to the traditional methods of measuring displacement using Linear variable differential transducers (LVDTs) that have limitations such as number of points and devices and space occupied by each device, phot ogrammetry does not have these restrictions. However, well planned surveying and positioning of survey points can help in getting accurate results else hey may not be necessarily reliable. 2.8.8 Excavation Volume Computation using P hotogrammetry Yakar et al. (2008) suggested that photogrammetry technique could be used for volume computing as opposed to the traditional methods like trapezoidal method and geodetic surveying. A test field was created where all the dimensions were known so that they can be ve rified with photogrammetric results. Kodak DSC 4530 was used for obtaining images and Photomodeler 5.0 software was used to create a 3D model. The photogrammetric method required 2 people as opposed to 3 while using the conventional method and the accurac y level was higher for Photogrammetry. Also, the method was more than 20% cost effective compared to the conventional method. In general, the method was cost and time saving and can be used for hard to reach places.

PAGE 37

37 2.8.9 Digital Photogrammetry for Trenc hless E ngineering Trenchless engineering is being used vastly nowadays and efficient ways of monitoring and mapping need to be used in order to go through a hassle free process. (Lueke 2011) suggested that photogrammetry tool can be used to obtain 3D repre sentation of the jobsite. He used the Canon EOS Rebel Xsi DSLR camera for capturing photos and Photomodeler software for photo processing. The photogrammetry results for gathering surface profile data were compared to leveling techniques and it was found t hat photogrammetry required less manpower, and it could measure all target simultaneously hence, it was faster. Also, minimum training was required for using the camera and software. 2. 8.10 Cameras and S oftware tools used for Applications L isted in the L iterature R eview Table 2 7 provides a list of cameras and software tools obtained through the literature review Table 2 7 List of cameras and software processing tools from literature review Camera Software Author Canon Eos SLR 400D Not mentioned Dai e t al. 2013 Canon EOS rebel T3i and Canon EOS 60D Not mentioned Dai et al. 2014 Canon Xsi 450D Not mentioned Ahmed et al. 2012 Kodak Dx3500 Photomodeler pro Arias et al. 2015 AVT Oscar F 810C/8 Photomodeler pro Wang et al. 2010 Go Pro Agisoft Photosc an Bemis et al. 2014 N ikon D70 Not mentioned V alenca et al. 2008 Kodak DSC 4530 Photomodeler 5.0 Yakar et al. 2008 Canon EOS Rebel Xsi Digital SLR camera PhotoModeler Lueke et al. 2011

PAGE 38

38 2.8.11 Benefits and Limitations of P hotogrammetry from the Literat ure Review Table 2 8 and 2 9 list the benefits and limitations of photogrammetry as observed from the literature review respectively. Table 2 8 List of benefits of photogrammetry from the literature review Benefits Author Cost savings on manpower and tim e Dai et al. 2014, P. Arias 2015, Wang 2010, Yakar 2008, Lueke 2011 Easy access to hazardous areas Dai et al. 2014, Yakar 2008 Better mode of doucmentation compared to manual methods Ahmed et al. 2012 No health and safety issues Ahmed et al. 2012 Can be used in a wider range of temperatures Ahmed et al. 2012 Time saving due to less amount of data sorting and filling Wang 2010 High level of accuracy Wang 2010, Velenca 2008, Yakar 2008 Minimum training requirement for camera operation Lueke 2011 Ta ble 2 9 List of benefits of photogrammetry from the literature review Limitations Author Lack of accuracy due to distortion of camera lens and human factors Dai et al. 2014 Difficulty while capturing texture less areas Dai et al. 2014 Inability to crea te dense point clouds Dai et al. 2014 Prior planning of data acquisition required to obtain optimized results Arias 2015, Bemis 2014 Velenca 2008 Using tripod can give better results due to increased stabilization Wang 2010 2.9 Common Applications for the Three T echnologies Table 2 10 lists the common applications of the three technologies as observed from the literature review.

PAGE 39

39 Table 2 10 List of common applications for three technologies Common applications Laser Scanning Lidar Scanning Photogramm etry Dimension Verification Building Inspection Progress monitoring Historical building documentation Monitoring of structural deformation Survey Mapping (Roads) Bridge Load testing Computation of quantities (Vol ume of excavation) Trenchless Engineering (Tunnels) Development of shop drawings Quality Assessment Geotehnical Works 2.10 Research Gap Several applications of the three technologies have been found through the literature but literature related specifically to building inspection is limited. These technologies come along their advantages and disadvantages some of which were noted through the literature review. The question is to what extent are these technologies used for the purpose of building inspection and what are their benefits and limitations from a construction industry perspective? What is the workflow for these technologies? What parameters differentiate them from one another?

PAGE 40

40 CHAPTER 3 RESEARCH METHODOLOGY 3.1 Purp ose of the Study The purpose of the research is to determine the differences in workflows, cost, quality and time factors for three building technologies: Laser Scanning, Lidar Scanning and Photogrammetry using Digital Camera. The second purpose is to dete rmine the perception of the construction industry towards using building technology tools especially towards the building inspection activity. To investigate the proposed study, two experiments were conducted. The first experiment was conducted in the Univ ersity building. A room in the building which is the computer laboratory was selected for the experiment. Laser Scans, Lidar Scans and Photographs were obtained for the room. The workflow for the three techniques was framed and the overall experiment will be compared for quality of data, cost and time factors. Two equipment Laser Scanner and Digital Camera required for the experiment were available with the university. In order to obtain the Lidar Scans, a third party personnel from a local company in Gaine sville was contacted for obtaining the laser scans and additional information about the equipment. The point cloud data obtained was processed in an Autodesk software. Being a student at the University of Florida, free access to the software was available. The second experiment was based on an industry survey. The questionnaire for the study was evaluated and approved by the University In order to submit the stud y, the researcher had to take up two trainings IRB 02 and NIH Extramural Training. The questionnaire on approval was distributed to subjects who are construction industry professionals. LinkedIn messenger and emails were used as a medium of communication. Survey links were distributed along with an Informed Consent Form as an

PAGE 41

41 agreement to participate in the study. The responses provided by the subjects were statistically analyzed. 3.2 Experiment The proposed method using the following equipment for obtaini ng scans and images: 3.2.1 Location of the E xperiment The experiment was conducted in the Rinker hall building at the University of Florida as shown in Figure 3 1 A computer laboratory room was selected for obtaining the scans. The size of the laborator y was approximately 700 Square Feet (SF) Figure 3 Florida ( Source: Photo courtesy of author (June 12,2018 ) ) 3.2.2 Equipment Specifications 3.2.2.1 Laser Scanner: The lase r scanner used for obtaining the point cloud data was the FARO Focus 3 D 120 which is a phase based laser scanner The scan settings were set to 1/5 Resolution. Quality of 3X and the color capture was turned on. This scanner has an accuracy up to 1mm and th e range is

PAGE 42

42 from 0.6 up to 120 m. The scanner has been classified as Class 54 for environmental protection. The scanner comes with 2 batteries and 32GB SD card. The battery life for the equipment is 4.5 hours per charge The scanner was available at the Univ Construction Management 3.2.2.2 Digital Camera: The camera used for obtaining photographs was Canon EOS Rebel T3. The camera resolution is 12 megapixels with 32 GB SD Card. The camera was also available at the 3.2.2.3 Lidar Scanner: The mobile Lidar scanner used for the experiment was PX 80 by Paracosm. Since this equipment was not available with the school, a local company personnel of the Lidar Scanning company offered to help for obtaining the scanned data. 3.2.2.4 Software for Data P rocessing: The scans and images obtained from all the three software were processed for creating 3D models using Autodesk Re cap for laser and lidar sc ans and Autodesk Recap Photo for photogrammetry. 3.2.2.5 Computer for Data P rocessing: The data processing was performed on Dell Inspiron 13 7000 laptop with 1800MHz processing speed, 8 GB Random Access Memory (RAM) and Intel(R) UHD Graphics 620 processo r and 64 bit Windows 10. 3.3 Description of the E xperiment: 3.3.1 Data collection using Laser Scanner: The FARO scanner was set up on a tripod in one corner of the room. Initial settings were done for the scanner such as creating a folder as denoted in Figure 3 2A changing the resolution

PAGE 43

43 and quality Figur e 3 2B enabling sensors Figure 3 2C and Color settings Figure 3 2D Then a scan was taken. Similarly, the tripod was set up at three other corners of the room and scans were obtained. The four scans that were saved on the SD card in the .fls format were then copied to the computer for processing. A) Step 1: Folder Creation B) Step 2: Resolution and Quality settings C) Step 3: Sensor Settings D) Step 4: Scan Parameter settings Figure 3 2. Steps for initial setup of a LASER scanner ( Source: Photo c ourtesy of author (May 28, 2018) ).

PAGE 44

44 3.3.2 Data colle ction using Mobile Lidar Scanner: The Paracosm scanner and tablet attached to it were set up for the experiment. Set up as denoted in Figure 3 3A and 3 3B included mounting the scanner and tablet on the hand held stick and creating a folder for the new s can. The scanner was held in hand at an angle such that the camera view is not obstructed, and maximum area is covered. Holding the scanner, a walk was taken through the entire room. Due to the small size of the room, only one scan was required to obtain s ubstantial data. The scanned data was extracted by the scanning operator at his office and raw data files in .ply, .las and .jobsight format were obtained. The scanned point cloud file was uploaded on Autodesk Recap and a 3D point cloud model was created u sing Autodesk Recap. A) Step 1: Scanner and tablet set up B) Step 2: Folder Creation Figure 3 3 Steps for initial setup of a mobile LIDAR scanner ( Source: Photo c ourtes y of author (Jun 10,2018) )

PAGE 45

45 3.3.3 Data C ollection using Digital Camera: Canon Digital camera as shown in Figure 3 4 was used to capture photos in the computer laboratory. --photos were captured and were extracted from the SD card in the .CR2 format. They were later converted to .JPEG format using an online raw file converter. The .JPEG format photos were extracted in Autodesk Recap and stitched to create a 3D model. Figure 3 4. Image of camera used for capturing photos ( Source: Photo c ourtesy of author (June 22,2018) )

PAGE 46

46 3. 4 Workflows fo r the Three T echnologies and their Compariso n 3.4.1 Laser Scanning Figure 3 5. Workflow for Laser Scanning (Source: Diagram courtesy of author (June 8,2018 ) ).

PAGE 47

47 3.4.2 Lidar Scanning Figure 3 6. Workflow for Lidar Scanning ( Source: Diagram courtesy of author (June 8, 2018)).

PAGE 48

48 3.4.3 Photogrammetry using Digital Camera Figure 3 7. Workflow for Photogrammetry ( Source: Diagram courtesy of author (June 8, 2018)).

PAGE 49

49 3.5 Comparison of the Three Technologies on the basis of Various P arameters Table 3 1 denot es the comparison of the three building technologies on the basis of several param e ters Table 3 1. Comparison of technologies based on various parameters Sr. No. Parameters Laser Scanner Lidar Scanner Photogrammetry 1 Cost $25,000 $28,000 $800 2 Time Initial Device Setup (Time is inclusive of starting and setting up the equipment and fixing the initial settings) 8 7 2 Total Scan Time (min) 30 5 7 Data Processing Time (min) 35 60 55 Total Time (min) 73 72 64 3 Weight (lbs) 9.25 7 1.1 4 Batter y Life 4.5 hrs 1.5 hrs 8hrs 5 Dimensions 230x183x103mm Height 280mm Diameter 170mm 129.9x99.7x77.9m m 6 Sensors GPS, Compass, Height Sensor, Inclinometer Simaltanous Localization and Mapping (SLAM) CMOS (Complementary Metal Oxide Semiconductor) 7 Touchsc reen Facility Yes Yes No 8 Range 120m 100m 9 Accuracy 1mm 20 30mm 10 Extracted data format .FLS .LAS, .PLY, .JOBSIGHT .CR2 12 Camera Resolution 13.2 MP 3.2 MP 12 MP 3.6 Survey Questionnaire 3.6.1 Data Collection The data for understanding the st atus of the three technologies: Laser Scanning, Lidar Scanning and Photogrammetry was sent out to construction industry professionals via Emails

PAGE 50

50 and Linkedin Messenger. 700 contacts of construction professionals were obtained through by on LinkedIn. Some of the details that are available by using this function are: Name, Email id, Profession, etc. Since a direct filter could not be applied for identifying construc tion out of 2000 contacts, 650 contacts were selected for sending out the survey. These 650 contacts were emailed the survey on their respective email ids. However, not everyone listed their professional email ids and there was unsurety about the survey having reached everyone. Hence, the same survey link was sent over Linked I n messenger to each person separately. The rest of the 50 contacts were obtained from the bus iness cards obtained during the career fair held by the questionnaire. A total of 96 responses were obtained out of which 75 were complete and could be considered for fur ther analysis. Eight people informed over emails and LinkedIn messenger that they were unaware of the technologies or did not work in that area of construction and hence would not be the right people to answer the questionnaire. Seven emails bounced and he nce could not reach the sampled participants. From the obtained results, the response rate was 11%. 3.6.2 Description of the Q uestionnaire and A nalysis The survey questionnaire consisted of 13 questions. Two of the 13 questions were fill in the blank ques tions. Five of them were multiple choice questions with additional options to fill data other than the given options. The rest of the five questions were based on the Likert scale. The aim of the first four questions was to understand the educational and p rofessional background of the participants. The next nine questions aimed at understanding the extent to which construction industry professionals are familiar with the reality capturing techniques, at what frequency do they utilize these tools and what ar e the potential benefits and limitations of

PAGE 51

51 these tools. For some of the questions, participants were asked to select on a scale of 1 5 or the Likert scale responses. Each of the responses for the questions were analyzed graphically and the Likert scale qu estions were statistically analyzed. Mean and Standard Deviations were calculat ed for the Liker t Scale questions.

PAGE 52

52 CHAPTER 4 RESULTS AND DISCUSSION 4.1 Analysis of the E xperiment The workflows for the three processes were similar in some ways. The most c onvenient mode of gathering the data was found to be with the lidar scanner. It had the least number of setup processes and it took least amount of time for the actual scanning process. However, extracting the scan from the lidar scanner took significant a mount of time. With respect to photogrammetry, it is highly dependent on the way the images are taken. It is important to have maximum number of overlaps else desired output will not be received. Also, movements or distortions while taking images can also lead to undesirable output. The cost of a digital camera is far lower than the scanners but the quality of data obtained is of a much higher quality. Time taken to process the data and convert it to a 3D model is the highest for photogrammetry as maximum time is spent in gathering the correct data. Also more number of captures need to be taken. 4.2 Analysis of the Survey Questionnaire R esults On analyzing the responses for the first four questions, the overall background and profession of 75 industry prof essionals was understood. Fr om Figure 4 2 it can be observed that out of a sample of 75, about 41% of the participants possess about 1 3 years of experience, 25 % possess between 3 6 years of AEC industry experience. One third of the total sample possesse s more than 6 years of experience. With respect to the education experience from Figure 4 1 93% of the total participants belongs to the AEC background. They belonged to either one of the backgrounds or a combination of two. Almost half of the participan ts possessed two professional backgrounds. The other 7% were

PAGE 53

53 from education backgrounds and professions such as Architectural Engineering, Human Resources, Urban Planning, Business Management and Mechanical Engineering. About the professional entities tha t one is associated with, almost 55% of the population was associated with General contractors. This can be observed in Figure 4 3. The rest were associated with BIM consultancy, Software development and vendors, consultancies subcontractors, owners and ar chitect. Figure 4 4 denotes t h at the annual volume of work performed by the participants mostly ranged between 0 0.5 billion and 1 5 billion. More than 50% of the population were associated with companies that have a turnover between zero to five billion dollars. From the graph in Figure 4 5 it can be observed that maximum participants use Revit as a means of modelling medium followed by Autodesk Recap. 15 participants do not use any modelling medium and the rest use several other software. From the graph in Figure 4 6, it is seen that one third of the sample does not use any technology for building inspection and rely on human inspection. Whereas seven out of 75 participants use all three technologies Laser scanning is the most used method for building i nspection. Lastly from Figure 4 7, it was observed that two third of the population did not use any technology for activities other than building inspection but one third of the population did for activities such as survey mapping, quality control, site lo gistics and planning, building layout and as built documentation.

PAGE 54

54 Figure 4 1. Venn diagram denoting educational backgrounds of participants where Sample N=75 (Source: Courtesy of author (June 25, 2018) Figure 4 2. Bar chart diagram denoting number of years of experience of participants in the construction industry where Sample N=75 (Source: Courtesy of author (June 25, 2018) 0 5 10 15 20 25 30 35 25
PAGE 55

55 Figure 4 3. Bar chart diagram denoting the association of participants with several professional entities where Sample N =75 (Source: Courtesy of author (June 25, 2018) Figure 4 4. Bar chart diagram denoting range for annual volume of work performed by the (Source: Courtesy of author (June 25, 2018) 0 10 20 30 40 50 ARCHITECT 2 OR MORE ROLES OWNER SUB CONTRACTOR OTHER GENERAL CONTRACTOR 1 5 7 7 12 46 Count Role PROFESSIONAL ROLES VS COUNT 0 5 10 15 20 25 30 10
PAGE 56

56 Figure 4 5. Bar chart dia gram denoting frequency of usage of different software for data processing where Sample N=133 (Source: Courtesy of author (June 25, 2018) Figure 4 6. Bar chart diagram denoting technology usage for building inspection where Sample N =75 (Source: Court esy of author (June 25, 2018) 1 1 18 46 1 1 8 1 2 6 1 9 15 6 7 1 1 3 1 1 1 1 1 0 5 10 15 20 25 30 35 40 45 50 SOFTWARE USAGE FOR DATA PROCESSING 0 5 10 15 20 25 30 17 0 5 4 1 9 7 27 10 TECHNOLOGY USAGE FOR BUILDING INSPECTION

PAGE 57

57 Figure 4 7 Bar chart diagram denoting building technology usage for activities other than building inspection where Sample N =75 (Source: Courtesy of author (June 25, 2018) 4.3 Likert scale questions analysis Figure 4 8. Likert scale statistical calculations (Source: Courtesy of author (June 25, 2018) 23 52 0 10 20 30 40 50 60 Yes No BUILDING TECHNOLOGY USAGE FOR ACTIVITIES OTHER THAN BUILDING INSPECTION

PAGE 58

58 From the Likert scale results, it was found that more than half of the participants were familiar with the concept of Reality computing. Participants were neutral in their opinion when they were asked to rate the quality of Human inspection. In general, participants rated technology based inspection on a higher end compared to human inspection. With respect to how effective the three techniques were for building inspec tion. Laser scanning was found to be more effective compared to the other two methods followed by Lidar scanning and then photogrammetry. Participants used Laser scanning and photogrammetry to an equal extent and Lidar scanning was the used least frequentl y owing to it being a newer technology compared to the other two. The ratings received for all advantageous were comparatively high. The cost and requirement of training however were the biggest disadvantages.

PAGE 59

59 CHAPTER 5 CONCLUSION AND FUTURE RECOMMENDATI ONS 5.1 Conclusion Reality capturing is a growing technology. It does have several civil engineering and construction applications but it is scantily documented for building inspection purpose. Hence, it was essential to understand the limitations by perf orming an experiment and also by conducting a survey with construction professionals to understand the limitations of these technologies. Through the literature review, higher cost is one of the major concerns why these technologies are not used. Still peo ple prefer to use manual mode of inspection. The experiment helped to understand the workflow of each of these technologies and the differences of various parameters in each of them. The survey results led to the conclusion that people are aware about real ity capturing and its benefits yet they are hesitant to use them on projects for inspection and progress monitoring purpose. The most important reason is the cost of the equipment and requirement of training. 5.2 Limitations With respect to the limitatio ns, for capturing images from a camera, the camera was hand held which meant lower stability while capturing. Dimension cross verification of 3D model versus actual site dimension was not carried out to judge the accuracy of data. With respect to the surve y, the participants were considered who belonged to the construction backgrounds but did not necessarily have experience in using building technologies. The results of the questionnaire may have been different had the participants been the ones who work sp ecifically in the building technology sector.

PAGE 60

60 5. 3 Recommendations for Future Research While performing the experiment with the three technologies the accuracy of the data obtained has not been taken into consideration. Accuracy of the instrument is known however cross verification with manual measurements could have helped to achieve more standard conclusions. Also, for photogrammetry, if images were captured by fixing the camera on the tripod stand, the results may have been different and more accurate d ue to increase in stability of promoting these technologies because they are typically being used for surveying and documentation purpose. If their feasibility i n building inspection is known, they frequency of usage of these techniques may increase.

PAGE 61

61 APPENDIX A IRB APPROVAL

PAGE 62

62

PAGE 63

63 APPENDIX B INFORMED CONSENT FORM Informed Consent Protocol Title Assessing 3 building technology workflows: La ser Scanning, Lidar Scanning and Photogrammetry and performing an industry survey to evaluate their usage status and feasibility in the construction industry Purpose of the research study The purpose of this research is to study the usage and feasibilit y of 3 technologies for building inspection: Laser Scanning, Lidar Scanning and Photogrammetry. What you will be asked to do in the study You will be asked to fill a questionnaire inclusive of 13 multi choice and fill in the blank questions. Time requi red 8 10 minutes. Risks and Benefits There are no anticipated risks or benefits involved with participating in this survey. Compensation There is no compensation for participating in this research. Confidentiality Your participation will be anony mous. Your identity will not be revealed. Voluntary participation Your participation in this study is completely voluntary. There is no penalty for not participating. Right to withdraw from the study You have the right to withdraw from the study at a ny time without consequence. Who to contact if you have questions about the study Rutuja Gosavi, Graduate Student, Rinker School of Construction Management, Rinker Hall, University of Florida, phone (352) 284 7434. Dr. Raymond Issa, Thesis Committe e Chair, Rinker School of Construction Management, Rinker Hall, University of Florida, phone (352) 273 1152. Who to contact about your rights as a research participant in the study IRB02 Office Box 112250 University of Florida Gainesville, FL 32611 2250 Phone 392 0433.

PAGE 64

64 Agreement I have read the procedure described above. I voluntarily agree to participate in the procedure and I have received a copy of this description. If I have responded to the survey, I have voluntarily agreed to participate howeve r, my response shall be withdrawn if I request to do so. Request for withdrawal can either be emailed to Rutuja Gosavi or messaged over LinkedIn messenger.

PAGE 65

65 APPENDIX C ONLINE QUESTIONNAIRE

PAGE 66

66

PAGE 67

67

PAGE 68

68

PAGE 69

69 LIST OF REFERENCES Abdelhafiz A. based monitoring system applied to project manageme 603 616. 055. hods for Close Range Photogrammetry Surveying July 2015 Vol 14, No.6, 1371 1381. Bemis S., Micklethwaithe S., Turner D., James M., Akciz S., Thiele S., Bangash H. (2014). based and UAV based photogrammetry: A multi scale, high resolution Geology 69 (2014) DOI: 10.10.14 163 178f. photogrammetric methods and l Information Research: Bridging the Pacific and Atlantic University of Gvle, Sweden, 7 9 June 2004. C.R. Kennedy Survey Solutions (2018). 3D laser scanning. Retrieved from https://survey.crkennedy.com.au/categories/_products/3dlaserscanning (Access date: June 18, 2018) aterials ISSN: 1662 7482 Vols.353 356, pp 2795 2798 DOI: 2013 08 08. Engineering 2014, 2:2 http://www.viejournal.com/content/2/1/2. 663. El Detailed 3D reconstruction of large scale 24(3), 21 29.

PAGE 70

70 Using Laser Scanning and International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XLI B3, 2016. A 4 Dimensional augmented re ality model for automating construction progress monitoring data collection, processing Dimensional Laser Scanning for Geometry Documentation and Construction Management of Highway Tunnels during Exca 11249 11270; doi:10.3390/s120811249. 53 49. Qualitative P 248. DOI: 10.1061 /(ASCE)0733 9464(2005)131:3(377). geotechnical works on reconstruction of drawing spans of the Palace Bridge reconstruction of draw spans of the Palace Bridge in Sa Geotechnics and Geoecology, TGG 2017, 17 19 May 2017, Saint Petersburg, Russia. 143. process implications of field data capture technologies for construction and facility/ ion, Special issue Sensors in Construction and Infrastructure Management (13) (2008) 134 154. https://www .statista.com/topics/974/construction/ (Access date: June 8, 2018) built Building (2014) 209 218. Liu 228.

PAGE 71

71 1 ASCE 2183 2192. https:/ /img04.en25.com/Web/JLLAmericas/%7Bdc55efb8 8a3c 4554 8808 4b11ea27d402%7D_JLL Construction Outlook Q3 2017.pdf (Access date: May 10, 2018). Rane Photogrammetric Technology: Providing Resource documentation, Interpre o/perations Center Denver, Colorado, 800225 Technical Note 428 September 2008. the construction project 15 Universiti Teknologi Malaysia. Retrieved from https://www.autodesk.com/redshift/reality computing/ (Access date: May 11, 2018). Muhammad A., Khairulnizam M., Zulkepli M., Mohd Farid M., Lau C., Mohd Azwan A., Albert of precast Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XLII 4/W1, 2016. https://www.nikonusa.com/en/index.page (Access date: June 12 2018) https://paracosm.io/ (Access date: May 18,2018) Park H., Lee H Aided Civil and Infrastructure Engineering 22 (2007) 19 30. Institute of Photogrammetry and Remote Sensing, Austria 681.7.055:621.375.826. E nvironments Conference 23 May 2003. cost Aerial unit for outdoor 135.

PAGE 72

72 Journal of Information Technology in Construction (ITcon), Special issue: 9th AiC BIM Academic Symposium and Job Task Analysis Review Conference, Vol. 21, pg. 204 217. tion of application areas for Augmented Reality in Construction, Elsevier, 17, 882 894. http://floridalaserscanning.com/3d laser scanning/how does laser scanning work/ (Access date: June 22,2018) ructure. Retrieved from https://www.autodesk.com/redshift/what is reality capture/ (Access date: May 8, 2018) plication: From Data Collection to End Eilat, Israel, 3 8 May 2009. Technical University of Lisbon Januar y 2018. I/FIEOS 2002 Conference Proceedings. Verma, V., Kumar, R., Hsu, S., (2006) "3D building detection and modeling from aerial lidar data." 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06). Vol. 2. IEEE, 2006. unbeath, Scotland, UK: Whittles Publishing, 2010. p.318, ISBN 978 1904445 87 6. construction and as built condition of membrane structures by Close Range Photogrammetr Spatial Information Sciences, Vol. XXXVIII, Part 5 592 296. al of Traffic and Transportation Engineering 2014, 1(5):325 337. International Journal of Advanced Robotic Systems, Vol 4, No. 4 (2007). Williams K., Olsen M., Roe G., Glennie

PAGE 73

73 https://eijournal.com/print/artic les/consider the benefits of mobile lidar for transportation projects (Access date: June 19, 2018) volume Computing of Digital close Range and Spatial Information Sciences. Vol. XXXVII. Part B3b. Beijing 2008 Yu W., Wu C., Lein W. (200 th International Symposium on Automation and Robotics in Construction, June 26 29, 2008. The potential impact on project Construction Forum DOI: December 2016. Automation in Construction Volum e 36, December 2013, Pages 108 116. Zhang, Y., Zhang, Z., Zhang, J., Wu, J.(2005). "3D building modelling with digital map, lidar data and video image sequences." The Photogrammetric Record 20.111 (2005): 285 302.

PAGE 74

74 BIOGRAPHICAL SKETCH Rutuja Gosavi is a researcher who possesses interest in the building technology sector and its implementations for various construction related applications. She received her MS in construction management from the University of Florida She possesses a b achelor s degree in the field of c ivil e ngineering from Veermata Jijabai Technological Institute, Mumbai, India. Rutuja aims to work in the construction industry as a construction management professional in the long run.