Technology & Innovation Archives - Page 5 of 19

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

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

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.

The Effect of Luminance Distribution Patterns on Occupant Preference in a Daylit Office Environment

Van Den Wymelenberg, Kevin; Inanici, Mehlika; Johnson, Peter. (2010). The Effect of Luminance Distribution Patterns on Occupant Preference in a Daylit Office Environment. Leukos, 7(2), 103 – 122.

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Abstract

New research in daylighting metrics and developments in validated digital High Dynamic Range (HDR) photography techniques suggest that luminance based lighting controls have the potential to provide occupant satisfaction and energy saving improvements over traditional illuminance based lighting controls. This paper studies occupant preference and acceptance of patterns of luminance using HDR imaging and a repeated measures design methodology in a daylit office environment. Three existing luminance threshold analysis methods [method1: predetermined absolute luminance threshold (for example, 2000 cd/m(2)), method2: scene based mean luminance threshold, and method3: task based mean luminance threshold] were studied along with additional candidate metrics for their ability to explain luminance variability of 18 participant assessments of 'preferred' and 'just disturbing' scenes under daylighting conditions. Per-pixel luminance data from each scene were used to calculate Daylighting Glare Probability (DGP), Daylight Glare Index (DGI), and other candidate metrics using these three luminance threshold analysis methods. Of the established methods, the most consistent and effective metrics to explain variability in subjective responses were found to be; mean luminance of the task (using method3; (adj)r(2) = 0.59), mean luminance of the entire scene (using method2; (adj)r(2) = 0.44), and DGP using 2000 cd/m(2) as a glare source identifier (using method1; (adj)r(2) = 0.41). Of the 150 candidate metrics tested, the most effective was the 'mean luminance of the glare sources', where the glare sources were identified as 7* the mean luminance of the task position ((adj)r(2) = 0.64). Furthermore, DGP consistently performed better than DGI, confirming previous findings. 'Preferred' scenes never had more than similar to 10 percent of the field of view (FOV) that exceeded 2000 cd/m(2). Standard deviation of the entire scene luminance also proved to be a good predictor of satisfaction with general visual appearance.

Keywords

Glare; Daylight Metrics; Luminance Based Lighting Controls; Discomfort Glare; Occupant Preference; High Dynamic Range

Computerized Integrated Project Management System for a Material Pull Strategy

Kim, Sang-Chul; Kim, Yong-Woo. (2014). Computerized Integrated Project Management System for a Material Pull Strategy. Journal Of Civil Engineering And Management, 20(6), 849 – 863.

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Abstract

The purpose of this paper is to present a computerized integrated project management system and report results of a survey on the effectiveness of the system. The system consists of a scheduling system, material management system, labor/equipment system, and safety/quality control system. The backbone system is a scheduling system that adopts a production planning system and a project scheduling system. The lowest level in the scheduling system is a daily work management system, which is linked to each functional management system (i.e. material management system, labor/equipment system, and safety/quality control system). The paper focuses on the material management and scheduling systems to implement a material pull system to reduce material inventories on site. Details of material management and scheduling systems are discussed, and a sample application is presented to demonstrate the features of the proposed computer application system. The paper presents practitioners and researchers with a practical tool to integrate material management and scheduling systems for site personnel.

Keywords

Construction; Lean Construction; Material Management System; Integrated System; Daily Work Management

An Investigation of the Daylighting Simulation Techniques and Sky Modeling Practices for Occupant Centric Evaluations

Inanici, Mehlika; Hashemloo, Alireza. (2017). An Investigation of the Daylighting Simulation Techniques and Sky Modeling Practices for Occupant Centric Evaluations. Building And Environment, 113, 220 – 231.

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Abstract

Occupant centric performance approaches in daylighting studies promote design decisions that support human visual comfort, productivity, and visual preferences, along with more conventional energy efficiency criteria. Simulating per-pixel luminance values and luminance distribution patterns for the entire scene allows us to analyze the occupant centric metrics and performance criteria. However, there are a number of different sky models, complex fenestration models, and simulation techniques that produce either conventional point in time images or annual luminance maps. This paper discusses the similarities and differences between different techniques; and a comparison analyses provides insight about their impact on occupant centric lighting measures. The comparisons for sky modeling include the conventional CIE skies (Clear, Intermediate, and Overcast), measurement based CIE models, Perez all-weather skies, and high dynamic range image based skies. The comparison of simulation techniques include point in time simulations, image based lighting simulations, and annual luminance simulations (threephase and five-phase methods). Results demonstrate that measurement based sky models match real world conditions with reasonable proximity, and generic CIE skies consistently underestimate the indoor lighting conditions. Annual simulation methods provide a large database of temporal luminance variations, where individual instances are comparable to point in time simulations. Long term luminance simulations provide opportunities to evaluate the percentage of the year that a given luminance based criteria is met or violated. (C)2016 Elsevier Ltd. All rights reserved.

Keywords

Complex Fenestration Systems; Scattering Distribution-functions; Discomfort Glare; Visual Comfort; Daylit Spaces; Validation; Radiance; Performance; Offices; Design; Sky Models; Daylight Simulations; Point In Time Simulations; Image Based Lighting; Annual Lighting Simulations; Annual Luminance Maps

Six Fundamental Aspects for Conceptualizing Multidimensional Urban Form: A Spatial Mapping Perspective

Wentz, Elizabeth A.; York, Abigail M.; Alberti, Marina; Conrow, Lindsey; Fischer, Heather; Inostroza, Luis; Jantz, Claire; Pickett, Steward T. A.; Seto, Karen C.; Taubenboeck, Hannes. (2018). Six Fundamental Aspects for Conceptualizing Multidimensional Urban Form: A Spatial Mapping Perspective. Landscape And Urban Planning, 179, 55 – 62.

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Abstract

Urbanization is currently one of the most profound transformations taking place across the globe influencing the flows of people, energy, and matter. The urban form influences and is influenced by these flows and is therefore critical in understanding and how urban areas affect and are affected by form. Nevertheless, there is a lack of uniformity in how urban form is analyzed. Urban form analyzed from a continuum of a simple urban versus non-urban classification to highly detailed representations of land use and land cover. Either end of the representation spectrum limits the ability to analyze within-urban dynamics, to make cross-city comparisons, and to produce generalizable results. In the framework of remote sensing and geospatial analysis, we identify and define six fundamental aspects of urban form, which are organized within three overarching components. Materials, or the physical elements of the urban landscape, consists of three aspects (1) human constructed elements, (2) the soil-plant continuum, and (3) water elements. The second component is configuration, which includes the (4) two- and three-dimensional space and (5) spatial pattern of urban areas. Lastly, because of the dynamics of human activities and biophysical processes, an important final component is the change of urban form over (6) time. We discuss how a this urban form framework integrates into a broader discussion of urbanization.

Keywords

Ecosystem Services; Land-use; Reconceptualizing Land; Cellular-automata; Heterogeneity; Framework; Model; Emissions; Dynamics; Cities; Gis; Remote Sensing; Land Use; Land Cover; Urban Form; Urban Materials; Energy; Humans; Land Use And Land Cover Maps; Landscapes; Urban Areas; Urbanization

Evidence-Driven Sound Detection for Prenotification and Identification Of Construction Safety Hazards and Accidents

Lee, Yong-Cheol; Shariatfar, Moeid; Rashidi, Abbas; Lee, Hyun Woo. (2020). Evidence-Driven Sound Detection for Prenotification and Identification Of Construction Safety Hazards and Accidents. Automation In Construction, 113.

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Abstract

As the construction industry experiences a high rate of casualties and significant economic loss associated with accidents, safety has always been a primary concern. In response, several studies have attempted to develop new approaches and state-of-the-art technology for conducting autonomous safety surveillance of construction work zones such as vision-based monitoring. The current and proposed methods including human inspection, however, are limited to consistent and real-time monitoring and rapid event recognition of construction safety issues. In addition, the health and safety risks inherent in construction projects make it challenging for construction workers to be aware of possible safety risks and hazards according to daily planned work activities. To address the urgent demand of the industry to improve worker safety, this study involves the development of an audio-based event detection system to provide daily safety issues to laborers and through the rapid identification of construction accidents. As an evidence-driven approach, the proposed framework incorporates the occupational injury and illness manual data, consisting of historical construction accident data classified by types of sources and events, into an audio-based safety event detection framework. This evidence-driven framework integrated with a daily project schedule can automatically provide construction workers with prenotifications regarding safety hazards at a pertinent work zone as well as consistently contribute to enhanced construction safety monitoring by audio-based event detection. By using a machine learning algorithm, the framework can clearly categorize the narrowed-down sound training data according to a daily project schedule and dynamically restrict sound classification types in advance. The proposed framework is expected to contribute to an emerging knowledge base for integrating an automated safety surveillance system into occupational accident data, significantly improving the accuracy of audio-based event detection.

Keywords

Construction Projects; Occupational Hazards; Construction Workers; Construction; System Safety; Video Surveillance; Work-related Injuries; Audio-based Accident Recognition; Autonomous Safety Surveillance; Construction Safety; Evidence-driven Sound Event Detection; Accident Prevention; Accidents; Audio Acoustics; Classification (of Information); Construction Industry; Health Hazards; Health Risks; Knowledge Based Systems; Learning Algorithms; Losses; Machine Learning; Monitoring; Motion Compensation; Occupational Diseases; Steel Beams And Girders; Audio-based; Construction Accidents; Construction Work Zones; Historical Construction; Sound Event Detection; State-of-the-art Technology; Vision Based Monitoring; Algorithm; System

Exploring Partnership Between Transit Agency And Shared Mobility Company: An Incentive Program For App-based Carpooling

Shen, Qing; Wang, Yiyuan; Gifford, Casey. (2021). Exploring Partnership Between Transit Agency And Shared Mobility Company: An Incentive Program For App-based Carpooling. Transportation, 48(5), 2585 – 2603.

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Abstract

How should public transit agencies deliver mobility services in the era of shared mobility? Previous literature recommends that transit agencies actively build partnerships with mobility service companies from the private sector, yet public transit agencies are still in search of a solid empirical basis to help envision the consequences of doing so. This paper presents an effort to fill this gap by studying a recent experiment of shared mobility public-private partnership, the carpool incentive fund program launched by King County Metro in the Seattle region. This program offers monetary incentives for participants who commute using a dynamic app-based carpooling service. Through descriptive analysis and a series of logistic regression models, we find that the monetary incentive to encourage the use of app-based carpooling generates some promising outcomes while having distinctive limitations. In particular, it facilitates the growth of carpooling by making carpooling a competitive commuting option for long-distance commuters. Moreover, our evidence suggests that the newly generated carpooling trips mostly substitute single-occupancy vehicles, thus contributing to a reduction of regional VMT. The empirical results of this research will not only help King County Metro devise its future policies but also highlight an appealing alternative for other transit agencies in designing an integrated urban transportation system in the era of shared mobility.

Keywords

Shared Mobility; Public-Private Partnership; App-based Carpooling; Incentive Fund; Transit Agencies; Incentives; Commuting; Public Transportation; Mobility; Regression Analysis; Regression Models; Partnerships; Vehicles; Car Pools; Private Sector; Occupancy; Transportation Systems; Mass Transit; Transportation Planning; Empirical Analysis; Urban Transportation