Technology & Innovation Archives - Page 5 of 19

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).

View Publication

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.

View Publication

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.

View Publication

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.

Where to Focus for Successful Adoption of Building Information Modeling within Organization

Won, Jongsung; Lee, Ghang; Dossick, Carrie; Messner, John. (2013). Where to Focus for Successful Adoption of Building Information Modeling within Organization. Journal Of Construction Engineering And Management, 139(11).

View Publication

Abstract

Suggestions abound for successful adoption of building information modeling (BIM); however, a company with limited resources cannot adopt them all. The factors that have top management priority for successful accomplishment of a task are termed critical success factors (CSFs). This paper aims to derive the CSFs for four questions commonly asked by companies in the first wave of BIM adoption: (1)What are the CSFs for adopting BIM in a company? (2)What are the CSFs for selecting projects to deploy BIM? (3)What are the CSFs for selecting BIM services? (4)What are the CSFs for selecting company-appropriate BIM software applications? A list of consideration factors was collected for each question, based on a literature review, and then refined through face-to-face interviews based on experiences of BIM experts. An international survey was conducted with leading BIM experts. From the 206 distributed surveys, 52 responses from four continents were collected. This study used quantitative data analysis to derive a manageable number (4-10) of CSFs for each category from dozens of anecdotal consideration factors. The derived CSFs are expected to be used as efficient metrics for evaluating and managing the level of BIM adoption and as a basis for developing BIM evaluation models in the future.

Keywords

Architectural Cad; Building Information Modeling; Bim; Critical Success Factors; Csf; Management; Building Information Models; Organizations; Computer Software; Building Information Modeling (bim); Critical Success Factor (csf); Organizational Strategy; Bim Software Application; Bim Service; Bim-assisted Project; Information Technologies

Evaluating a New Suite of Luminance-Based Design Metrics for Predicting Human Visual Comfort in Offices with Daylight

Van Den Wymelenberg, Kevin; Inanici, Mehlika. (2016). Evaluating a New Suite of Luminance-Based Design Metrics for Predicting Human Visual Comfort in Offices with Daylight. Leukos, 12(3), 113 – 138.

View Publication

Abstract

A new suite of visual comfort metrics is proposed and evaluated for their ability to explain the variability in subjective human responses in a mock private office environment with daylight. Participants (n = 48) rated visual comfort and preference factors, including 1488 discreet appraisals, and these subjective results were correlated against more than 2000 unique luminance-based metrics that were captured using high dynamic range photography techniques. Importantly, luminance-based metrics were more capable than illuminance-based metrics for fitting the range of human subjective responses to data from visual preference questionnaire items. No metrics based upon the entire scene ranked in the top 20 squared correlation coefficients, nor did any based upon illuminance or irradiance data, nor did any of the studied glare indices, luminance ratios, or contrast ratios. The standard deviation of window luminance was the metric that best fit human subjective responses to visual preference on seven of 12 questionnaire items (with r(2) = 0.43). Luminance metrics calculated using the horizontal 40. band (a scene-independent mask) and the window area (a scene-dependent mask) represented the majority of the top 20 squared correlation coefficients for almost all subjective visual preference questionnaire items. The strongest multiple regression model was for the semantic differential rating (too dim-too bright) of the window wall (R-adj(2) = 0.49) and was built upon three variables; standard deviation of window luminance, the 50th percentile luminance value from the lower view window, and mean luminance of the 40. horizontal band.

Keywords

Discomfort Glare; Controls; Daylighting; Visual Perception

Work Zone Intrusion: Technology To Reduce Injuries & Fatalities

Nnaji, Chukwuma; Gambatese, John; Lee, Hyun Woo. (2018). Work Zone Intrusion: Technology to Reduce Injuries & Fatalities. Professional Safety, 63(4), 36 – 41.

View Publication

Abstract

WZIAT was first introduced to work zones in 1995 following a Strategic Highway Research Program (SHRP)-sponsored study (Agent & Hibbs, 1996). Since the SHRP program, several WZIATs have been developed, evaluated by departments of transportation (DOTs) and implemented in work zones on many highway projects. [...]the researchers investigated the potential usefulness of WZIATs on reported fatal work zone intrusion cases. [...]the researchers identified and evaluated work zone fatality cases captured in the NIOSH Fatality Assessment and Control Evaluation (FACE) program to determine whether WZIATs could have prevented the reported fatalities. [...]construction and maintenance workers are provided additional reaction time if an intrusion occurs before the activity zone.

Keywords

Research; Fatalities; Highway Construction; Injury Prevention; Traffic Accidents & Safety; Automobile Safety; Roads & Highways; Transportation Planning; Electronic Mail Systems; Researchers; Intrusion; General Contractors; Occupational Health; Vehicles; Studies; Workers; Employees; Construction Industry; Traffic Control; United States--us; Canada; Kansas; Oregon

Dynamic Modal Accessibility Gap: Measurement and Application Using Travel Routes Data.

Guan, Jinping; Zhang, Kai; Shen, Qing; He, Ying. (2020). Dynamic Modal Accessibility Gap: Measurement and Application Using Travel Routes Data. Transportation Research: Part D, 81.

View Publication

Abstract

Accessibility is a key concept in transportation research and an important indicator of people's quality of life. With the development of big data analytics, dynamic accessibility that captures the temporal variations of accessibility becomes an important research focus. Few prior studies focus on comparative measures of dynamic accessibility to Points of Interest (POIs) by alternative travel modes. To fill this research gap, we propose a new index called dynamic modal accessibility gap (DMAG), which draws upon available data on residents' real travel routes using different travel modes, as well as the data on POIs. We study the DMAG in the real-travel covered area, assuming POIs are only useful if it is within someone's real-travel covered area. We then apply this DMAG methodology to Shanghai's central city and peripheral area. In both cases, we measure the accessibility for public and private travel modes. As an example, one-week taxi GPS and metro smart card data, and POIs data are used to generate the DMAG index for 30-minute and 60-minute trip durations for weekdays and holidays. Results show that DMAG can reflect the pattern of temporal variations. The proposed DMAG analytical framework, which can be applied at both the user and the system levels, can support urban and transportation planning, and promote social equity and livability.

Keywords

Air Travel; Choice Of Transportation; Urban Transportation; Transportation Planning; Urban Planning; Smart Cards; Inner Cities; Route Choice; Shanghai (china); Dynamic Accessibility; Modal Accessibility Gap (mag); Points Of Interest (pois); Public And Private Travel Modes; Temporal Variations; Scale Residential Areas; Transport; Time; Dimensions; Employment; Indicator; Choice; Boston; Car

Three Pathways to Highly Energy Efficient Buildings: Assessing Combinations of Teaming and Technology

Homayouni, Hoda; Dossick, Carrie Sturts; Neff, Gina. (2021). Three Pathways to Highly Energy Efficient Buildings: Assessing Combinations of Teaming and Technology. Journal Of Management In Engineering, 37(2).

View Publication

Abstract

Highly energy efficient (HEE) buildings require a whole-system approach to building design. Scholars have suggested many tools, techniques, and processes to address the cross-disciplinary complexities of such an approach, but how these elements might be best combined to lead to better project outcomes is yet unknown. To address this, we surveyed architects associated with 33 AIA-COTE award-winning projects on the social, organizational, and technological elements of whole-system design (WSD) practices. We then used fuzzy sets-qualitative comparative analysis (fsQCA) to analyze the interdependencies among those elements. We found three distinct pathways for the design and construction of HEE buildings: information-driven, process-driven, or organization-driven. We also found that HEE buildings share some conditions for success, including having shared goals, owners engagement in the design process, and frequent and participatory interorganizational meetings. Our findings can help practitioners strategize and make decisions on incorporating WSD elements associated with their project types. Moreover, these results provide a launchpad for scholars to investigate complementarities among elements facilitating the design and construction process of HEE projects.

Keywords

Buildings (structures); Construction; Design Engineering; Energy Conservation; Fuzzy Set Theory; Innovation Management; Organisational Aspects; Project Management; Team Working; Whole-system Approach; Building Design; Cross-disciplinary Complexities; Social Elements; Organizational Elements; Technological Elements; Whole-system Design Practices; Fuzzy Set; Distinct Pathways; Hee Buildings; Project Types; Construction Process; Hee Projects; Highly Energy Efficient Buildings; Whole-system Design; Energy Efficient Buildings; Building Information Modeling; Integrated Project Teams; Fuzzy Sets-qualitative Comparative Analysis