Technology & Innovation Archives - Page 7 of 20

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.

A Probabilistic Portfolio-based Model For Financial Valuation Of Community Solar.

Shakouri, Mahmoud; Lee, Hyun Woo; Kim, Yong-woo. (2017). A Probabilistic Portfolio-Based Model for Financial Valuation of Community Solar. Applied Energy, 191, 709 – 726.

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Abstract

Community solar has emerged in recent years as an alternative to overcome the limitations of individual rooftop photovoltaic (PV) systems. However, there is no existing model available to support probabilistic valuation and design of community solar based on the uncertain nature of system performance over time. In response, the present study applies the Mean-Variance Portfolio Theory to develop a probabilistic model that can be used to increase electricity generation or reduce volatility in community solar. The study objectives include identifying the sources of uncertainties in PV valuation, developing a probabilistic model that incorporates the identified uncertainties into portfolios, and providing potential investors in community solar with realistic financial indicators. This study focuses on physical, environmental, and financial uncertainties to construct a set of optimized portfolios. Monte Carlo simulation is then performed to calculate the return on investment (ROI) and the payback period of each portfolio. Lastly, inclusion vs. exclusion of generation and export tariffs are compared for each financial indicator. The results show that the portfolio with the maximum output offers the highest ROI and shortest payback period while the portfolio with the minimum risk indicates the lowest ROI and longest payback period. This study also reveals that inclusion of tariffs can significantly influence the financial indicators, even more than the other identified uncertainties. (C) 2017 Elsevier Ltd. All rights reserved.

Keywords

Solar Energy; Photovoltaic Power Systems; Monte Carlo Method; Market Volatility; Energy Economics; Community Solar; Monte Carlo Simulation; Photovoltaic Systems; Portfolio Theory; Uncertainty; Environmental Uncertainties; Financial Indicator; Financial Uncertainties; Physical Uncertainties; Identified Uncertainties; Probabilistic Model; Mean-variance Portfolio Theory; Probabilistic Valuation; Individual Rooftop Photovoltaic Systems; Financial Valuation; Probabilistic Portfolio-based Model; Investment; Monte Carlo Methods; Photovoltaic Cells; Risk Analysis; Tariffs; Resolution Lidar Data; Electricity Consumption; Pv Systems; Autoregressive Models; Potential Assessment; Generation Systems; Neural-networks; Energy; Buildings; Economic Theory; Electricity; Exports; Probabilistic Models; Risk

A Mixed VR and Physical Framework to Evaluate Impacts of Virtual Legs and Elevated Narrow Working Space on Construction Workers Gait Pattern

Habibnezhad, M.; Puckett, J.; Fardhosseini, M.S.; Pratama, L.A. (2019). A Mixed VR and Physical Framework to Evaluate Impacts of Virtual Legs and Elevated Narrow Working Space on Construction Workers Gait Pattern. Arxiv, 7 pp.

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Abstract

It is difficult to conduct training and evaluate workers' postural performance by using the actual job site environment due to safety concerns. Virtual reality (VR) provides an alternative to create immersive working environments without significant safety concerns. Working on elevated surfaces is a dangerous scenario, which may lead to gait and postural instability and, consequently, a serious fall. Previous studies showed that VR is a promising tool for measuring the impact of height on the postural sway. However, most of these studies used the treadmill as the walking locomotion apparatus in a virtual environment (VE). This paper was focused on natural walking locomotion to reduce the inherent postural perturbations of VR devices. To investigate the impact of virtual height on gait characteristics and keep the level of realism and feeling of presence at their highest, we enhanced the first-person-character model with "virtual legs". Afterward, we investigated its effect on the gait parameters of the participants with and without the presence of height. To that end, twelve healthy adults were asked to walk on a virtual loop path once at the ground level and once at the 17th floor of an unfinished structure. By quantitatively comparing the participants' gait pattern results, we observed a decrease in the stride length and increase in the gait duration of the participants exposed to height. At the ground level, the use of the enhanced model reduced participants' average stride length and height. The results of this study help us understand users' behaviors when they were exposed to elevated surfaces and establish a firm ground for gait stability analysis for the future height-related VR studies. We expect this developed VR platform can generate reliable results of VR application in more construction safety studies.

Keywords

Civil Engineering Computing; Construction Industry; Gait Analysis; Medical Computing; Occupational Safety; Virtual Reality; Construction Safety Studies; Mixed Vr; Virtual Legs; Construction Workers Gait Pattern; Immersive Working Environments; Postural Instability; Serious Fall; Postural Sway; Walking Locomotion Apparatus; Natural Walking Locomotion; Inherent Postural Perturbations; Vr Devices; Virtual Height; First-person-character Model; Gait Parameters; Virtual Loop Path; Stride Length; Gait Duration; Gait Stability Analysis; Safety Concerns; Vr Platform; Height-related Vr Studies

Human-Centric Lighting Performance of Shading Panels in Architecture: A Benchmarking Study with Lab Scale Physical Models Under Real Skies

Parsaee, Mojtaba; Demers, Claude M. H.; Lalonde, Jean-francois; Potvin, Andre; Inanici, Mehlika; Hebert, Marc. (2020). Human-Centric Lighting Performance of Shading Panels in Architecture: A Benchmarking Study with Lab Scale Physical Models Under Real Skies. Solar Energy, 204, 354 – 368.

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Abstract

This study investigates shading panels' (SPs) impacts on daylighting features in a lab scale model in terms of parameters representing potential human eyes' biological responses identified as image forming (IF) and non-image forming (NIF). IF responses enable vision and NIF responses regulate internal body clocks known as circadian clocks. Human-centric lighting evaluates photopic units, representing IF responses, and melanopic units representing NIF responses, combined with correlated color temperature (CCT) of light for potential biological effects. SPs' impacts on such parameters of daylighting have not yet been studied. Previous research mostly studied panels' impacts on visual comfort and glare related to IF responses. This research explores the impact of SPs' color, reflectance, orientation, and openness on photopic and melanopic units and CCT of daylighting inside a 1:50 physical scale model of a space. Approximately 40 prototypes of SPs were evaluated. An experimental setup was designed under outdoor daylighting conditions to capture high dynamic range (HDR) images inside the model. HDR images were post processed to calculate and render the distribution of photopic and melanopic units, melanopic/photopic (M/P) ratios and CCTs in the captured viewpoint of the model. Results reveal the behavior of SPs' color, reflectance, orientation, and openness in modifying daylighting parameters related to biological responses. Bluish panels, in particular, increase daylighting melanopic units and CCTs whereas reddish panels increase photopic units and reduce CCTs. The research results were discussed to provide an outline for future developments of panels to adapt daylighting to occupants' IF and NIF responses.

Keywords

Models & Modelmaking; Shades & Shadows; Daylighting; Color Temperature; Benchmarking (management); Ecological Houses; Eye Tracking; Circadian Rhythms; Adaptive Design; Healthy Lighting; High Performance Fa‚àö√üade; Photobiology; Responsive Building; Design; Sensitivity; Illuminance; Systems; Spaces; Impact; Glare; High Performance Facade; Reflectance; Scale Models; Biological Effects; Human Performance; Prototypes; Parameter Modification; Lighting; Shading; Eye (anatomy); Color; Parameter Identification; Light Effects; Panels; Mathematical Models; Images; Biological Clocks; Orientation

A Framework for Estimating Commute Accessibility and Adoption of Ridehailing Services Under Functional Improvements from Vehicle Automation

Zou, Tianqi; Aemmer, Zack; Mackenzie, Don; Laberteaux, Ken. (2022). A Framework for Estimating Commute Accessibility and Adoption of Ridehailing Services Under Functional Improvements from Vehicle Automation. Journal Of Transport Geography, 102.

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Abstract

This paper develops an analytical framework to estimate commute accessibility and adoption of various ridehailing service concepts across the US by synthesizing individual commute trips using national Longitudinal Employer-Household Dynamics Origin-Destination Employment Statistics (LODES) data. Focusing on potential improvements in cost and time that could be enabled by vehicle automation, we use this modeling framework to simulate a lower-price autonomous service (e.g., 50% or 75% lower) with variable wait times and implementation levels (solo, pooled, and first/last mile transit connections services, alone or in combination) to determine how they might affect adoption rates. These results are compared across metrics of accessibility and trip density, as well as socioeconomic factors such as household income. We find - unsurprisingly - that major cities (e.g. New York, Los Angeles, and Chicago) support the highest adoption rates for ridehailing services. Decreases in price tend to increase market share and accessibility. The effect of a decrease in price is more drastic for lower income groups. The proposed method for synthesizing trips using the LODES contributes to current travel demand forecasting methods and the proposed analytic framework can be flexibly implemented with any other mode choice model, extended to non-commute trips, or applied to different levels of geographic aggregation.

Keywords

Choice Of Transportation; Demand Forecasting; Poor People; Adoption; Price Cutting; Metropolis; Employment Statistics; Los Angeles (calif.); New York (state); Chicago (ill.); Accessibility; Autonomous Vehicles; New Mobility Services; Ridehailing; Travel Demand; Preferences

A Suggested Color Scheme for Reducing Perception-Related Accidents on Construction Work Sites

Yi, June-Seong; Kim, Yong-Woo; Kim, Ki-Aeng; Koo, Bonsang. (2012). A Suggested Color Scheme for Reducing Perception-Related Accidents on Construction Work Sites. Accident Analysis And Prevention, 48, 185 – 192.

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Abstract

Changes in workforce demographics have led to the need for more sophisticated approaches to addressing the safety requirements of the construction industry. Despite extensive research in other industry domains, the construction industry has been passive in exploring the impact of a color scheme: perception-related accidents have been effectively diminished by its implementation. The research demonstrated that the use of appropriate color schemes could improve the actions and psychology of workers on site, thereby increasing their perceptions of potentially dangerous situations. As a preliminary study, the objects selected by rigorous analysis on accident reports were workwear, safety net, gondola, scaffolding, and safety passage. The colors modified on site for temporary facilities were adopted from existing theoretical and empirical research that suggests the use of certain colors and their combinations to improve visibility and conspicuity while minimizing work fatigue. The color schemes were also tested and confirmed through two workshops with workers and managers currently involved in actual projects. The impacts of color schemes suggested in this paper are summarized as follows. First, the color schemes improve the conspicuity of facilities with other on site components, enabling workers to quickly discern and orient themselves in their work environment. Secondly, the color schemes have been selected to minimize the visual work fatigue and monotony that can potentially increase accidents. (C) 2011 Elsevier Ltd. All rights reserved.

Keywords

Construction Industry Accidents; Industrial Hygiene; Industrial Safety; Empirical Research; Sensory Perception; Work Environment; Demographic Surveys; Job Performance; Color Scheme; Construction Industry; Labor Demography; Perception-related Accident; Accident Prevention; Accidents; Demography; Human Resource Management; Population Statistics; Color Schemes; Construction Works; Dangerous Situations; Rigorous Analysis; Safety Requirements; Temporary Facilities; Work Environments; Psychological Climate; Drivers; Emotion; Model