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Immersive VR Versus BIM for AEC Team Collaboration in Remote 3D Coordination Processes

Asl, Bita Astaneh; Dossick, Carrie Sturts. (2022). Immersive VR Versus BIM for AEC Team Collaboration in Remote 3D Coordination Processes. Buildings, 12(10).

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Abstract

Building Information Modeling (BIM) and Virtual Reality (VR) are both tools for collaboration and communication, yet questions still exist as to how and in what ways these tools support technical communication and team decision-making. This paper presents the results of an experimental research study that examined multidisciplinary Architecture, Engineering, and Construction (AEC) team collaboration efficiency in remote asynchronous and synchronous communication methods for 3D coordination processes by comparing BIM and immersive VR both with markup tools. Team collaboration efficiency was measured by Shared Understanding, a psychological method based on Mental Models. The findings revealed that the immersive experience in VR and its markup tool capabilities, which enabled users to draw in a 360-degree environment, supported team communication more than the BIM markup tool features, which allowed only one user to draw on a shared 2D screenshot of the model. However, efficient team collaboration in VR required the members to properly guide each other in the 360-degree environment; otherwise, some members were not able to follow the conversations.

Keywords

Mental Models; Virtual-reality; Performance; Virtual Reality (vr); Building Information Modeling (bim); 3d Coordination; Clash Resolution; Remote Collaboration; Multidisciplinary Aec Team

Selection of Wearable Sensor Measurements for Monitoring and Managing Entry-level Construction Worker Fatigue: A Logistic Regression Approach

Lee, Wonil; Lin, Ken-yu; Johnson, Peter W.; Seto, Edmund Y.w. (2022). Selection of Wearable Sensor Measurements for Monitoring and Managing Entry-level Construction Worker Fatigue: A Logistic Regression Approach. Engineering Construction & Architectural Management (09699988), 29(8), 2905-2923.

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Abstract

Purpose: The identification of fatigue status and early intervention to mitigate fatigue can reduce the risk of workplace injuries. Off-the-shelf wearable sensors capable of assessing multiple parameters are available. However, using numerous variables in the fatigue prediction model can elicit data issues. This study aimed at identifying the most relevant variables for measuring occupational fatigue among entry-level construction workers by using common wearable sensor technologies, such as electrocardiogram and actigraphy sensors. Design/methodology/approach: Twenty-two individuals were assigned different task workloads in repeated sessions. Stepwise logistic regression was used to identify the most parsimonious fatigue prediction model. Heart rate variability measurements, standard deviation of NN intervals and power in the low-frequency range (LF) were considered for fatigue prediction. Fast Fourier transform and autoregressive (AR) analysis were employed as frequency domain analysis methods. Findings: The log-transformed LF obtained using AR analysis is preferred for daily fatigue management, whereas the standard deviation of normal-to-normal NN is useful in weekly fatigue management. Research limitations/implications: This study was conducted with entry-level construction workers who are involved in manual material handling activities. The findings of this study are applicable to this group. Originality/value: This is the first study to investigate all major measures obtainable through electrocardiogram and actigraphy among current mainstream wearables for monitoring occupational fatigue in the construction industry. It contributes knowledge on the use of wearable technology for managing occupational fatigue among entry-level construction workers engaged in material handling activities. [ABSTRACT FROM AUTHOR]; Copyright of Engineering Construction & Architectural Management (09699988) is the property of Emerald Publishing Limited and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Keywords

Construction Workers; Wearable Technology; Logistic Regression Analysis; Fatigue (physiology); Frequency-domain Analysis; Heart Beat; Lifting & Carrying (human Mechanics); Construction Safety; Information And Communication Technology (ict) Applications; Management; Technology

Using Open Data and Open-source Software to Develop Spatial Indicators of Urban Design and Transport Features for Achieving Healthy and Sustainable Cities

Boeing, Geoff; Higgs, Carl; Liu, Shiqin; Giles-corti, Billie; Sallis, James F.; Cerin, Ester; Lowe, Melanie; Adlakha, Deepti; Hinckson, Erica; Moudon, Anne Vernez; Salvo, Deborah; Adams, Marc A.; Barrozo, Ligia, V; Bozovic, Tamara; Delclos-alio, Xavier; Dygryn, Jan; Ferguson, Sara; Gebel, Klaus; Thanh Phuong Ho; Lai, Poh-chin; Martori, Joan C.; Nitvimol, Kornsupha; Queralt, Ana; Roberts, Jennifer D.; Sambo, Garba H.; Schipperijn, Jasper; Vale, David; Van De Weghe, Nico; Vich, Guillem; Arundel, Jonathan. (2022). Using Open Data and Open-source Software to Develop Spatial Indicators of Urban Design and Transport Features for Achieving Healthy and Sustainable Cities. Lancet Global Health, 10(6), E907-E918.

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Abstract

Benchmarking and monitoring of urban design and transport features is crucial to achieving local and international health and sustainability goals. However, most urban indicator frameworks use coarse spatial scales that either only allow between-city comparisons, or require expensive, technical, local spatial analyses for within-city comparisons. This study developed a reusable, open-source urban indicator computational framework using open data to enable consistent local and global comparative analyses. We show this framework by calculating spatial indicators-for 25 diverse cities in 19 countries-of urban design and transport features that support health and sustainability. We link these indicators to cities' policy contexts, and identify populations living above and below critical thresholds for physical activity through walking. Efforts to broaden participation in crowdsourcing data and to calculate globally consistent indicators are essential for planning evidence-informed urban interventions, monitoring policy effects, and learning lessons from peer cities to achieve health, equity, and sustainability goals.

Keywords

Systems; Access; Care

Lingzi Wu

Lingzi Wu is an Assistant Professor with the Department of Construction Management (CM) at the University of Washington (UW). Prior to joining UW in September 2022, Dr. Wu served as a postdoctoral fellow in the Department of Civil and Environmental Engineering at University of Alberta, where she received her MSc and PhD in Construction Engineering and Management in 2013 and 2020 respectively. Prior to her PhD, Dr. Wu worked in the industrial construction sector as a project coordinator with PCL Industrial Management from 2013 to 2017.

An interdisciplinary scholar focused on advancing digital transformation in construction, Dr. Wu’s current research interests include (1) integration of advanced data analytics and complex system modeling to enhance construction practices and (2) development of human-in-the-loop decision support systems to improve construction performance (e.g., sustainability and safety). Dr. Wu has published 10 papers in top journals and conference proceedings, including the Journal of Construction Engineering and Management, Journal of Computing in Civil Engineering, and Automation in Construction. Her research and academic excellence has received notable recognition, including a “Best Paper Award” at the 17th International Conference on Modeling and Applied Simulation, and the outstanding reviewer award from the Journal of Construction Engineering and Management.

As an educator and mentor, Dr. Wu aims to create an inclusive, innovative, and interactive learning environment where students develop personal, technical, and transferable skills to grow today, tomorrow, and into the future.

Narjes Abbasabadi

Narjes Abbasabadi, Ph.D., is an Assistant Professor in the Department of Architecture at the University of Washington. Dr. Abbasabadi also leads the Sustainable Intelligence Lab. Abbasabadi’s research centers on sustainability and computation in the built environment. Much of her work focuses on advancing design research efforts through developing data-driven methods, workflows, and tools that leverage the advances in digital technologies to enable augmented intelligence in performance-based and human-centered design. With an emphasis on multi-scale exploration, her research investigates urban building energy flows, human systems, and environmental and health impacts across scales—from the scale of building to the scale of neighborhood and city.

Abbasabadi’s research has been published in premier journals, including Applied Energy, Building and Environment, Energy and Buildings, Environmental Research, and Sustainable Cities and Society. She received honors and awards, including “ARCC Dissertation Award Honorable Mention” (Architectural Research Centers Consortium (ARCC), 2020), “Best Ph.D. Program Dissertation Award” (IIT CoA, 2019), and 2nd place in the U.S. Department of Energy (DOE)’s Race to Zero Design Competition (DOE, 2018). In 2018, she organized the 3rd IIT International Symposium on Buildings, Cities, and Performance. She served as editor of the third issue of Prometheus Journal, which received the 2020 Haskell Award from AIA New York, Center for Architecture.

Prior to joining the University of Washington, she taught at the University of Texas at Arlington and the Illinois Institute of Technology. She also has practiced with several firms and institutions and led design research projects such as developing design codes and prototypes for low-carbon buildings. Most recently, she practiced as an architect with Adrian Smith + Gordon Gill Architecture (AS+GG), where she has been involved in major projects, including the 2020 World Expo. Abbasabadi holds a Ph.D. in Architecture from the Illinois Institute of Technology and Master’s and Bachelor’s degrees in Architecture from Tehran Azad University.

Maximizing the Computational Efficiency of Temporary Housing Decision Support Following Disasters

El-Anwar, Omar; Chen, Lei. (2014). Maximizing the Computational Efficiency of Temporary Housing Decision Support Following Disasters. Journal Of Computing In Civil Engineering, 28(1), 113 – 123.

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Abstract

Postdisaster temporary housing has long been a challenging problem because of its interlinked socioeconomic, political, and financial dimensions. A significant need for automated decision support was obvious to address this problem. Previous research achieved considerable advancements in developing optimization models that can quantify and optimize the impacts of temporary housing decisions on the socioeconomic welfare of displaced families and total public expenditures on temporary housing as well as other objectives. However, the computational complexity of these models hindered its practical use and adoption by emergency planners. This article analyzes the computational efficiency of the current implementation of the most advanced socioeconomic formulation of the temporary housing problem, which uses integer programming. Moreover, it presents the development of a customized variant of the Hungarian algorithm that has a superior computational performance while maintaining the highest quality of solutions. An application example is presented to demonstrate the unique capabilities of the new algorithm in solving large-scale problems.

Keywords

Decision Support Systems; Emergency Management; Integer Programming; Computational Efficiency; Temporary Housing Decision Support Following Disasters; Financial Dimensions; Political Dimensions; Socioeconomic Dimensions; Socioeconomic Welfare; Emergency Planners; Socioeconomic Formulation; Hungarian Algorithm; Multiobjective Optimization; Maeviz-hazturk; Housing; Computation; Disasters; Temporary Structures; Temporary Housing; Optimization; Disaster Management

The Impact of Avatars, Social Norms and Copresence on the Collaboration Effectiveness of AEC Virtual Teams

Anderson, Anne; Dossick, Carrie Sturts; Iorio, Josh; Taylor, John E. (2017). The Impact of Avatars, Social Norms and Copresence on the Collaboration Effectiveness of AEC Virtual Teams. Journal Of Information Technology In Construction, 22, 287 – 304.

Abstract

A growing number of architecture, engineering, and construction (AEC) firms are outsourcing complex design and construction work to international vendors. Due to the significant geographic distances that can separate project team members in global design networks, much of this work is executed in virtual teams, defined as teams composed of geographically separated members who collaborate to accomplish organizational tasks mediated by technology. The challenges of working in geographically distributed networks have prompted the development of alternative, virtual workspaces. Questions remain on how these virtual workspaces support or hinder collaborative work. People are social beings that rely on body language and other non-verbal cues to communicate. What happens to team formation and collaborative effectiveness when non-verbal cues are mediated through avatar actions? In this paper, qualitative ethnographic data collected over four years from studies conducted in a 3D virtual world are used to examine collaboration effectiveness of global virtual engineering project teams. We found that avatar movement and position was effective at communicating nonverbal information, even when done so unintentionally. Avatar actions that map to established social norms in the physical world results in more efficient communication. Collaboration was also enhanced when gesture bubbles were used for backchannel communication and when text chat was used to avoid interrupting voice communication. We found collaboration was hindered when the learning curve was too steep for participants to adapt to tool use or avatar actions in the environment. These findings have important implications for the future of collaboration in virtual environments, particularly in the AEC industry where 3D models can be imported into the virtual environment and explored synchronously by a project team.

Keywords

Architectural Design; Human Resource Management; International Trade; Bim Coordination; Collaboration Technology; Distributed Teams; Social Norm; Virtual Worlds; Communication; Design; Technology; Dimensions; Teamwork; Behavior; Collaboration Technologies; Social Norms

Cybergrid: A Virtual Workspace for Architecture, Engineering, and Construction

Taylor, John E.; Alin, Pauli; Anderson, Anne; Çomu, Semra; Dossick, Carrie Sturts; Hartmann, Timo; Iorio, Josh; Mahalingam, Ashwin; Mohammadi, Neda. (2018). Cybergrid: A Virtual Workspace for Architecture, Engineering, and Construction. Transforming Engineering Education: Innovative, Computer-mediated Learning Technologies, 291-321.

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Abstract

Projects in the architecture, engineering and construction (AEC) industry frequently involve a large number of firms that increasingly span national boundaries. National boundary spanning by AEC firms engaged in complex, interdependent work introduces coordination challenges because stakeholders may not share the same language, culture or work practices. These types of firms have begun to explore the use of technologies that can meaningfully create productive work connections between the distributed participants 47 and help improve work coordination and execution. In this chapter, we describe the CyberGRID (Cyber-enabled Global Research Infrastructure for Design); a virtual workspace designed to support geographically distributed AEC work coordination and execution. The CyberGRID was created as a research tool to both enable and study virtual AEC teamwork. We summarize findings from multiple experiments over the jive year history of CyberGRID research and development. These findings help to improve our understanding of interactional dynamics among virtual teams in complex sociotechnical systems like the CyberGRID. We then discuss the challenges faced in developing the CyberGRID and in achieving widespread adoption of such tools in the industry. We close the chapter with a discussion of future research opportunities to develop improved sociotechnical systems to better support the execution of AEC projects. Our goal with this chapter is to argue that sociotechnical systems like the CyberGRID can fundamentally and positively transform the interactional dynamics of AEC project stakeholders to create more efficient global virtual work practices.

Keywords

Civil Engineering Computing; Construction Industry; Data Visualisation; Groupware; Project Management; Team Working; Virtual Reality; Cybergrid; Virtual Workspace; Construction; Engineering; National Boundaries; National Boundary Spanning; Aec Firms; Complex Work; Interdependent Work; Coordination Challenges; Culture; Productive Work Connections; Chapter; Global Research Infrastructure; Geographically Distributed Aec Work Coordination; Research Tool; Virtual Aec Teamwork; Virtual Teams; Complex Sociotechnical Systems; Future Research Opportunities; Improved Sociotechnical Systems; Aec Projects; Aec Project Stakeholders; Efficient Global Virtual Work Practices

Dynamic Production Scheduling Model Under Due Date Uncertainty in Precast Concrete Construction

Kim, Taehoon; Kim, Yong-Woo; Cho, Hunhee. (2020). Dynamic Production Scheduling Model Under Due Date Uncertainty in Precast Concrete Construction. Journal Of Cleaner Production, 257.

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Abstract

Precast concrete structures (PCs) are widely used in the construction industry to reduce project delivery times and improve quality. On-time delivery of PCs is critical for successful project completion because the processes involving precast concrete are the critical paths in most cases. However, existing models for scheduling PC production are not adequate for use in dynamic environments where construction projects have uncertain construction schedules because of various reasons such as poor labor productivity, inadequate equipment, and poor weather. This research proposes a dynamic model for PC production scheduling by adopting a discrete-time simulation method to respond to due date changes in real time and by using a new dispatching rule that considers the uncertainty of the due dates to minimize tardiness. The model is validated by simulation experiments based on various scenarios with different levels of tightness and due date uncertainty. The results of this research will contribute to construction project productivity with a reliable and economic precast concrete supply chain. (C) 2020 Elsevier Ltd. All rights reserved.

Keywords

Multiple Production; Demand Variability; Supply Chain; Shop; Management; Minimize; Lines; Precast Concrete Production; Dynamic Simulation; Uncertainty; Production Scheduling; Dispatching Rule