Available online at ScienceDirect. Procedia Engineering 161 (2016 ) Sepehr Alizadehsalehi a, *, Ibrahim Yitmen a

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1 Available online at ScienceDirect Procedia Engineering 161 (2016 ) World Multidisciplinary Civil Engineering-Architecture-Urban Planning Symposium 2016, WMCAUS 2016 The Impact of Field Data Capturing Technologies on Automated Construction Project Progress Monitoring Sepehr Alizadehsalehi a, *, Ibrahim Yitmen a a Civil Engineering Department, Eastern Mediterranean University, Famagusta, North Cyprus, via Mersin 10, Turkey Abstract Accurate and timely information of construction project progress in a regular repeated basis is one of the critical stages of construction management. The purpose of this study is to investigate the impact of field data capturing technologies (FDCT), in combination with building information modelling (BIM) on automated construction project progress monitoring (ACPPM). The research is based on a survey of contracting and engineering consulting firms operating in the Middle East, Mid-Asia, Europe, North America, and Far East. Based on an evaluation of the findings, 3D Laser Scanning (LS), Image-based, and Radio Frequency Identification (RFID) technologies in combination with BIM were found as the most used technologies for ACPPM. At the end, a conceptual framework is illustrated and managerial implications are highlighted with a sample statement focusing on requirements, processes and benefits. The study confirms the importance of using BIM-based FDCT in enhancing ACPPM factors performance. It also highlights the need for further exploration of the role of the BIM-based FDCT in improving ACPPM The Authors. Published by by Elsevier Ltd. Ltd. This is an open access article under the CC BY-NC-ND license ( Peer-review under responsibility of the organizing committee of WMCAUS Peer-review under responsibility of the organizing committee of WMCAUS 2016 Keywords: field data capturing technologies; automated construction project progress monitoring; BIM; 1. Introduction Construction industry realized the urgent need for providing the opportunity to understand the current project status easy, rapid, and accurate [1]. Rapid project assessment further identifies discrepancies between the as-built and asplanned progress, and facilitates decision making on the necessary remedial actions [2]. Currently, manual visual observations and traditional progress monitoring based on field personnel s interpretation are time-consuming, errorprone, and infrequent [3] [4]. Consequently, investigation on new methodologies that allow automatic recognition of as-built performance and visualization of construction progress is vital. In response to this need, significant progress towards automating detection and visualization of as-built status of a project has been achieved in recent years. The advancement in automatic field data acquisition systems will enable more accurate collection of data and knowledge The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license ( Peer-review under responsibility of the organizing committee of WMCAUS 2016 doi: /j.proeng

2 98 Sepehr Alizadehsalehi and Ibrahim Yitmen / Procedia Engineering 161 ( 2016 ) about processes and operations on site. These technologies include Image-based technologies, Laser Scanning (LS), Radio Frequency Identification (RFID), Ultra-Wideband (UWB), Global Positioning System (GPS) and wireless sensor networks (WSN). The purpose of this study is to investigate the impact of FDCT, in combination with BIM on ACPPM. 2. Literature Review 2.1. BIM in Project Progress Monitoring BIM is a rich source of information for performing ACPPM. It describes the as-planned project shape in terms of 3D geometry and combines it with the as-planned construction schedule. The resulting 4D model combines all relevant information for the complete construction process [2] [5]. Application of these models during the construction phase can be increased if further potential added values from integrating BIMs with as-built models [6]. Therefore, the planned state at any time can be derived and compared with the actual construction state. Consequently, BIM can serve as a powerful baseline for progress tracking and in the visualization of discrepancies Field Data Capturing Technologies for ACPPM In the last decade, the capabilities of FDCT for ACPPM have significantly increased. Early detection of performance deviations in field construction activities with minimum human input is critical as it provides an opportunity for project management to avoid them or minimize their impacts [7]. Integration of BIM-based models and real-time field data acquisition systems can increase the degree of automation in all parts of project progress monitoring and control such as architectural, structural and MEP. Furthermore, updates, analysis and reporting can be made more frequently, regularly, and accurately along the work progress. Table 1 shows the summary of the previous researches which used the integration of different FDCT and BIM for ACPPM. Table 1: Advanced Automated BIM-based Data Capturing Technologies. Operation Approach Technology Definition Resources Automated Construction Project Progress Monitoring Building Information Modelling (BIM) Image-based modelling 3D Laser Scanning(LS) Radio Frequency Identification (RFID) Barcodes Ultra-Wideband (UWB) Global Positioning System (GPS) Wireless Sensor Network (WSN) Registering site digital pictures and the project 3D Computer-Aided Design model in a common coordinate system- Comparing the site digital pictures to the project model Capturing data within three coordinates of longitude, latitude, and elevation of different objects Facilitating the control of various processes at different stages of a building lifecycle, especially for construction projects progress control monitoring Capturing and transmitting data from a tag embedded or attached to construction products, and such data can be used to capture construction progress The 3-D location of each tag can be recorded on a computer and the location and movement of each tag can be visually shown on a screen Space-based satellite navigation system providing location and time information in all conditions, anywhere that there is an unobstructed line of sight to GPS satellites and can use as a location tracking tool in construction industry. Spatially distributed autonomous sensors with a communications infrastructure to remote environmental and physical monitoring (temperature, humidity, sound, pressure, speed, direction, size, and etc. - Capable to collecting, storing, processing environmental information [3]; [8]; [9]; [10]; [11]; [6] [2]; [12]; [13]; [14]; [15]; [16]; [17]; [18]; [1] [19]; [20]; [21]; [17]; [1] [22]; [23]; [21] [24]; [17]; [1] [25]; [26]; [3]; [27] [28]; [29]; [30]; [31]

3 Sepehr Alizadehsalehi and Ibrahim Yitmen / Procedia Engineering 161 ( 2016 ) Research Method 3.1. Sampling The study focused on contracting and engineering consulting firms dealing with Civil Works, Infrastructure, Construction projects operating in the Middle East, Mid-Asia, Europe, North America, and Far East. The list consisted of a total of 326 contracting and engineering consulting firms. The sample includes only large firms Data Collection During the survey administration, a total of 500 firms were contacted to participate in the study and 326 completed questionnaires (one respondent from each firm) were received, giving a high response rate of 65 percent. The respondents were asked to rate the extent of agreement with each statement based on a five point Likert scale of 1 (strongly disagree) to 5 (strongly agree). Contact personnel in the firms for the questionnaire survey were either the top management or senior management. Table 2 shows the percentages of the respondents of the survey from different regions of the world having different professions. Table 2. Distribution of the stakeholders according to the type of regions and different professions. Regions/Countries Contracting Firm Stakeholders Profession Engineering Consulting Firm Project Manager (34.95%) Construction Manager (33%) Civil Engineer (32%) Middle East 4.60% 3.9% 3.6% UAE IRAN Mid-Asia 4.29% 4.% 3.9% AZERBAIJAN KAZAKHSTAN Europe 12.26% 11.6% 11.9% UK GERMANY FRANCE TURKEY North America 6.75% 6.4% 6.1% CANADA USA Far East 7.05% 6.7% 5.8% JAPAN S. KOREA Research Findings and Analysis 4.1. Determination of Relative Importance Indices The participating organizations provided numerical scoring expressing their opinions on the significance of each factor in determining the impact of the FDCT on ACPPM. The relative importance index method (RII) is used here to determine from perspective clients and contractors, factors affecting performance of consultants on development projects. RII is computed as [32]:

4 100 Sepehr Alizadehsalehi and Ibrahim Yitmen / Procedia Engineering 161 ( 2016 ) RII W (1) A N where: W is the weight given to each factor by the respondents and ranges from 1 to 5 A = the highest weight = 5 N = the total number of respondents Table 3. Matrix showing the variations in the level of Relative Importance Indices of the factors. Automated Construction Project Progress Monitoring (ACPPM) Environmental condition data collection Physical data collection Quality control Remote visual inspection Remote decision making Static/dynamic progress visualization Rapid/comprehensive emergency project assessment Item Field Data Capturing Technologies RII Rank 1 Image-based modelling D Laser Scanning (LS) Radio Frequency Identification (RFID) Barcodes Ultra-Wideband (UWB) Global Positioning System (GPS) Wireless Sensor Network (WSN) Site logistics visualization Static/dynamic safety analysis 4.2. Discussion of Survey The factor 3D Laser Scanning (LS) is ranked #1 and is perceived by respondents to have an influence on the ACPPM components Physical data collection and Static/dynamic progress visualization with values of RII 0.89, and 0.86 respectively. The interviews and observations highlighted that LS is a powerful tool for 3D field data collection during periodic inspections which generate 3D point cloud models to be transformed into the BIM. These models allow the project s stakeholders to understand the real-time status of projects with accurate 3D visualization. The factor Image-based modelling is ranked #2 and is perceived by respondents to have an influence on the ACPPM components Physical data collection and Static/dynamic progress visualization with values of RII 0.88, and 0.86 respectively. The interviews and observations emphasized that image-based is the most widespread and easy-to-use method of FDCT which can collect much information accurately and economically. In the construction site, the advanced image-based technology offers a unique capacity to construction by documenting and monitoring project progress and maintaining site condition controls. The factor Radio Frequency Identification (RFID) is ranked #3 and is perceived by the respondents to have an influence on the ACPPM components Site logistics visualizations and Remote decision making with values of RII 0.87, and 0.84 respectively. The interviews and observations pointed out that RFID is a strong and effective automatic identification technology, relying on storing and remotely retrieving data and providing a contact-less data accessing solution in progress monitoring. Participants concurred that RFID can generate positive impacts on real-time site logistics visualization and efficient-collaborative remote decision making.

5 Sepehr Alizadehsalehi and Ibrahim Yitmen / Procedia Engineering 161 ( 2016 ) Conceptual Model of Framework As mentioned in the literature review, there are various FDCT that are used for ACPPM. Each of these technologies according to their ability is able to collect the specific information (visual, logistics, quality etc.) about current status of projects under construction. Figure 1 presents the overall approach of Multi-Dimensional (n-d) Model for Integrated BIM- Based Data Acquisition Technologies and different combinations that make it up. The approach consists of integration of BIM with various data acquisition technologies (such as LS, Image-based, RFID, etc.) in order to increase the effectiveness of progress monitoring. Such a combination enables acquisition and update of the design and schedule information, involves modules that enable inspection planning and collection of as-built information based on that plan, and can be used to analyze the as-built information in different perspectives. Laser Scan (LS) Sensors Image- Based Building Information Model (BIM) As- Planned Model As- Built Model Global Position System (GPS) 3D 5D 4D 6D Ultra Wide Band (UWB) Barcodes Radio Frequency Identification (RFID) Fig. 1. Overall Approach: Multi-Dimensional (n-d) Model for Integrated BIM- Based Data Acquisition Technologies Managerial Implications This study has produced significant outcomes that can not only improve the knowledge of FDCT leveraging BIM Models (Architectural and Structural) for ACPPM but can also offer valuable guidelines for engineering management practice. Various real-time field data acquisition systems have been developed aimed at automating the progress of monitoring of construction projects. Some of those have demonstrated potential for ACPPM to a certain extent and most of the systems support a specific function of project control. It is envisioned that successful integration of realtime systems can provide the AEC industry with new opportunities in many aspects of project management. Progress monitoring on site in particular can be further advanced. Some real-time systems have been integrated individually with BIM. Visualization of construction progress helps construction project managers to study spatial aspects of asbuilt and as-planned performances, identify progress discrepancies, better utilize resources and equipment in different locations and make timely corrective decisions. Practicing engineering managers can develop a FDCT leveraging BIM models statement for ACPPM for their firm. Table 4 illustrates a sample of a FDCT BIM models for ACPPM. The FDCT BIM models clearly shows the relationships between the ACPPM, FDCT, BIM model, requirements, process and benefits. The creation of these FDCT BIM models can provide more opportunities for engineers and managers of construction projects to improve performance of projects through ACPPM leveraging BIM Models.

6 102 Sepehr Alizadehsalehi and Ibrahim Yitmen / Procedia Engineering 161 ( 2016 ) Table 4. A Sample of a FDCT leveraging BIM Models Statement for ACPPM. Automated Project Progress Monitoring Physical data collection Physical data collection Field Data Capturing Technologies 3D Laser Scanning (LS) Image-based Requirement Process Benefits -Identification of best possible position for Laser Scan in the construction site. -Integration different position scan data captured together in large scale constructıon sites -Camera selection -Camera location to be high enough to minimize line-of-sight interruptions to the view of the construction site -The camera to be programmable and equipped with a pan, tilt, and zoom movement function -Wired or wireless local area networks with internet connections for the transfer and saving of acquired site-image data to a main server - Scanning automatically of the desired points -Creation of 3D as- built point cloud model -Object detection along the X, Y and Z directions -Easily converting to 3D, 4D or n-d BIM- model (Scanto-BIM) -Improve the multidiscipline coordination of structural design documentation -Acquisition continuously records of high- resolution site images for representation of geometric attributes e.g., size, shape, faces, edges colour, location of objects etc. -Analysing the recorded images by applying computer vision technologies to obtain as-built 3D models automatically -Time saving/automatically making realtime state of project. -Automatically comparing for detecting progress deviations and using to update the schedule of the remaining process -Remote visual inspection -Cost effective operation -Quality assessment of existing infrastructure and construction sites -Remote decision making -Minimizing errors, and enhancing collaboration between engineering and architecture teams -Inexpensive operation -Can be used more flexible -Sharing of construction photographs on a truly massive scale to easily understandable -Integrating with other technologies and computer vision to make 2D, 3D and n-d for progress monitoring analysis -Detection of newly constructed elements and update of the construction schedule -Easy comparing different project status and describing progress deviations 4.5. Conclusions and Recommendations In recent years, significant progress towards automating field data capturing real-time information from real-life physical project processes and visualization of as-built status of a project using BIM has been achieved. This paper investigates the impact of FDCT, in combination with BIM on ACPPM within contracting firms and consulting firms operating in the construction sectors of different countries from the Middle East, Mid-Asia, Europe, North America, and Far East. Based on an evaluation of the findings, 3D Laser Scanning, Image-based, and Radio Frequency Identification (RFID) in combination with BIM were found as the most effective technologies for ACPPM. Finally, a conceptual framework and managerial implications are demonstrated with a sample statement focusing on requirements, processes and benefits. The study approves the significance of using BIM-based FDCT in enhancing ACPPM factors performance. It also highlights the need for further exploration of the role of the BIM-based FDCT in improving ACPPM. References [1] F. Bosché, M. Ahmed, Y. Turkan, C. T. Haas and R. Haas, The value of integrating Scan-to-BIM and Scan-vs-BIM techniques for construction monitoring using laser scanning and BIM: The case of cylindrical MEP components, Automation in Construction, vol. 49, p , [2] M. G. Fard, F. Peña-Mora and S. Savarese, Integrated Sequential As-Built and As-Planned Representation with D4ARD4AR Tools in Support of Decision-Making Tasks in the AEC/FM Industry, Journal of Construction Engineering and Management, vol. 137, no. 12, pp , 2011.

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