Technology & Innovation Archives - Page 13 of 19

Feasibility of Using QR Codes in Highway Construction Document Management

Lee, Hyun Woo; Harapanahalli, Bharat Anand; Nnaji, Chukwuma; Kim, Jonghyeob; Gambatese, John. (2018). Feasibility of Using QR Codes in Highway Construction Document Management. Transportation Research Record, 2672(26), 114 – 123.

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Abstract

Highway construction occasionally takes place in remote locations, making its document management challenging especially when frequent document revisions occur. With the recent advancement of smartphones and tablets, Quick Response (QR) codes can provide project teams rapid and reliable access to up-to-date documents required for field operations. As a result, the use of QR codes can lead to a reduced need for traveling or meeting for document revisions, and reduce the amount of hardcopy documents and storage space. Despite the potential for significant benefits, there have been few studies aimed at assessing the feasibility of using QR codes in highway construction. In response, the objective of the study was to investigate the benefits of and barriers to using QR codes in highway construction for document management. To conduct the study, first a multi-step process was used, involving an online survey and interviews, with a goal of determining the status quo of highway construction in terms of document management and mobile information technology (IT). The results indicate that hardcopy documentation is still the most prevalent form of document management in highway construction, and hence there is an opportunity for implementing QR codes in conjunction with mobile IT. In the second part of the study, a time study using a real-world infrastructure project was conducted based on three activities: detail look up, specification check, and version check. As a result, the study found statistical evidence that using QR codes can lead to significant time savings.

Keywords

Highway Planning; Information Services; Road Construction; Document Management; Field Operation; Highway Construction; Infrastructure Project; Online Surveys; Quick Response Code; Remote Location; Statistical Evidence

Curriculum To Prepare AEC Students for BIM-Enabled Globally Distributed Projects

Anderson, Anne; Dossick, Carrie Sturts; Osburn, Laura. (2020). Curriculum To Prepare AEC Students for BIM-Enabled Globally Distributed Projects. International Journal Of Construction Education & Research, 16(4), 270 – 289.

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Abstract

Globalization and the increasing adoption of BIM and other technologies in the AEC industry have changed the way we prepare graduates for the digital workplace. This paper presents curriculum design where students from five universities worked together to develop design and construction proposals. This paper describes a collaborative project executed in two parts. Part I included the University of Washington in the USA and IIT-Madras in India. Part II included Washington State University in the USA, and National Taiwan University and National Cheng Kung University in Taiwan. Students from these global universities worked on a multi-disciplinary, interdependent project where teams created 3D models and 4D construction simulations. This curriculum addresses ACCE and ABET accreditation requirements regarding multi-disciplinary teams, ethical and professional responsibilities in global, economic, environmental, and societal contexts, and effective teamwork. In this paper, we describe the course design, evaluative criteria, and lessons learned. We found that it was important to emphasize BIM Execution Planning for distributed teams given that communication and coordination can be challenging across time zones and cultural differences. Working through technical challenges of exchanging BIM data, the students learned coordination skills in a globally distributed team environment that simulated real work experiences. [ABSTRACT FROM AUTHOR]; Copyright of International Journal of Construction Education & Research is the property of Routledge 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

College Curriculum; Project Management; Digital Technology; Work Environment; Globalization; Bim; Building Information Modeling; Digital Literacy; Distributed Teams; Global Collaboration

A Global Horizon Scan of the Future Impacts of Robotics and Autonomous Systems on Urban Ecosystems

Goddard, Mark A.; Davies, Zoe G.; Guenat, Solene; Ferguson, Mark J.; Fisher, Jessica C.; Akanni, Adeniran; Ahjokoski, Teija; Anderson, Pippin M. L.; Angeoletto, Fabio; Antoniou, Constantinos; Bates, Adam J.; Barkwith, Andrew; Berland, Adam; Bouch, Christopher J.; Rega-brodsky, Christine C.; Byrne, Loren B.; Cameron, David; Canavan, Rory; Chapman, Tim; Connop, Stuart; Crossland, Steve; Dade, Marie C.; Dawson, David A.; Dobbs, Cynnamon; Downs, Colleen T.; Ellis, Erle C.; Escobedo, Francisco J.; Gobster, Paul; Gulsrud, Natalie Marie; Guneralp, Burak; Hahs, Amy K.; Hale, James D.; Hassall, Christopher; Hedblom, Marcus; Hochuli, Dieter F.; Inkinen, Tommi; Ioja, Ioan-cristian; Kendal, Dave; Knowland, Tom; Kowarik, Ingo; Langdale, Simon J.; Lerman, Susannah B.; Macgregor-fors, Ian; Manning, Peter; Massini, Peter; Mclean, Stacey; Mkwambisi, David D.; Ossola, Alessandro; Luque, Gabriel Perez; Perez-urrestarazu, Luis; Perini, Katia; Perry, Gad; Pett, Tristan J.; Plummer, Kate E.; Radji, Raoufou A.; Roll, Uri; Potts, Simon G.; Rumble, Heather; Sadler, Jon P.; De Saille, Stevienna; Sautter, Sebastian; Scott, Catherine E.; Shwartz, Assaf; Smith, Tracy; Snep, Robbert P. H.; Soulsbury, Carl D.; Stanley, Margaret C.; Van De Voorde, Tim; Venn, Stephen J.; Warren, Philip H.; Washbourne, Carla-leanne; Whitling, Mark; Williams, Nicholas S. G.; Yang, Jun; Yeshitela, Kumelachew; Yocom, Ken P.; Dallimer, Martin. (2021). A Global Horizon Scan of the Future Impacts of Robotics and Autonomous Systems on Urban Ecosystems. Nature Ecology & Evolution, 5(2), 219.

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Abstract

The future challenges and potential opportunities of robotics and autonomous systems in urban ecosystems, and how they may impact biodiversity, are explored and prioritized via a global horizon scan of 170 experts. Technology is transforming societies worldwide. A major innovation is the emergence of robotics and autonomous systems (RAS), which have the potential to revolutionize cities for both people and nature. Nonetheless, the opportunities and challenges associated with RAS for urban ecosystems have yet to be considered systematically. Here, we report the findings of an online horizon scan involving 170 expert participants from 35 countries. We conclude that RAS are likely to transform land use, transport systems and human-nature interactions. The prioritized opportunities were primarily centred on the deployment of RAS for the monitoring and management of biodiversity and ecosystems. Fewer challenges were prioritized. Those that were emphasized concerns surrounding waste from unrecovered RAS, and the quality and interpretation of RAS-collected data. Although the future impacts of RAS for urban ecosystems are difficult to predict, examining potentially important developments early is essential if we are to avoid detrimental consequences but fully realize the benefits.

Keywords

Smart City; Green Infrastructure; Automated Vehicles; Water-quality; Land-use; Cities; Opportunities; Biodiversity; Challenges; Services; Robotics; Horizon; Ecosystems; Land Use; Ecosystem Management; Transportation Systems; Strategic Management; Urban Areas

How Does Ride-Hailing Influence Individual Mode Choice? An Examination Using Longitudinal Trip Data from the Seattle Region

Wang, Yiyuan; Moudon, Anne Vernez; Shen, Qing. (2022). How Does Ride-Hailing Influence Individual Mode Choice? An Examination Using Longitudinal Trip Data from the Seattle Region. Transportation Research Record, 2676(3), 621 – 633.

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Abstract

This study investigates the impacts of ride-hailing, which we define as mobility services consisting of both conventional taxis and app-based services offered by transportation network companies, on individual mode choice. We examine whether ride-hailing substitutes for or complements travel by driving, public transit, or walking and biking. The study overcomes some of the limitations of convenience samples or cross-sectional surveys used in past research by employing a longitudinal dataset of individual travel behavior and socio-demographic information. The data include three waves of travel log data collected between 2012 and 2018 in transit-rich areas of the Seattle region. We conducted individual-level panel data modeling, estimating independently pooled models and fixed-effect models of average daily trip count and duration for each mode, while controlling for various factors that affect travel behavior. The results provide evidence of substitution effects of ride-hailing on driving. We found that cross-sectionally, participants who used more ride-hailing tended to drive less, and that longitudinally, an increase in ride-hailing usage was associated with fewer driving trips. No significant associations were found between ride-hailing and public transit usage or walking and biking. Based on detailed travel data of a large population in a major U.S. metropolitan area, the study highlights the value of collecting and analyzing longitudinal data to understand the impacts of new mobility services.

Keywords

Shared Mobility; Ride-hailing; Longitudinal Data; Substitution Between Travel Modes; Complementarity Between Travel Modes; Services; Uber

Guideline for Building Information Modeling in Construction Engineering and Management Education

Lee, Namhun; Dossick, Carrie S.; Foley, Sean P. (2013). Guideline for Building Information Modeling in Construction Engineering and Management Education. Journal Of Professional Issues In Engineering Education And Practice, 139(4), 266 – 274.

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Keywords

Buildings (structures); Computer Aided Instruction; Construction Industry; Educational Courses; Management Education; Structural Engineering Computing; Building Information Modeling; Construction Engineering And Management Education; Cem Education; Bim; Cem Curriculum

The Association between Park Visitation and Physical Activity Measured with Accelerometer, GPS, and Travel Diary

Stewart, Orion T.; Moudon, Anne Vernez; Fesinmeyer, Megan D.; Zhou, Chuan; Saelens, Brian E. (2016). The Association between Park Visitation and Physical Activity Measured with Accelerometer, GPS, and Travel Diary. Health & Place, 38, 82 – 88.

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Abstract

Public parks are promoted as places that support physical activity (PA), but evidence of how park visitation contributes to overall PA is limited. This study observed adults living in the Seattle metropolitan area (n=671) for one week using accelerometer, GPS, and travel diary. Park visits, measured both objectively (GPS) and subjectively (travel diary), were temporally linked to accelerometer-measured PA. Park visits occurred at 1.4 per person-week. Participants who visited parks at least once (n=308) had an adjusted average of 14.3 (95% Cl: 8.9, 19.6) min more daily PA than participants who did not visit a park. Even when park-related activity was excluded, park visitors still obtained more minutes of daily PA than non-visitors. Park visitation contributes to a more active lifestyle, but is not solely responsible for it. Parks may best serve to complement broader public health efforts to encourage PA. (C) 2016 Elsevier Ltd. All rights reserved.

Keywords

Physical Activity; Accelerometers; Geographic Information Systems; Park Use; Public Health; Built Environment; Gis; Leisure; Recreation; Substitution; Sedentary Behavior; Public-health; Accessibility; Prevention

Deep Learning in Design Workflows: The Elusive Design Pixel

Mahankali, Ranjeeth; Johnson, Brian R.; Anderson, Alex T. (2018). Deep Learning in Design Workflows: The Elusive Design Pixel. International Journal Of Architectural Computing, 16(4), 328 – 340.

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Abstract

The recent wave of developments and research in the field of deep learning and artificial intelligence is causing the border between the intuitive and deterministic domains to be redrawn, especially in computer vision and natural language processing. As designers frequently invoke vision and language in the context of design, this article takes a step back to ask if deep learning's capabilities might be applied to design workflows, especially in architecture. In addition to addressing this general question, the article discusses one of several prototypes, BIMToVec, developed to examine the use of deep learning in design. It employs techniques like those used in natural language processing to interpret building information models. The article also proposes a homogeneous data format, provisionally called a design pixel, which can store design information as spatial-semantic maps. This would make designers' intuitive thoughts more accessible to deep learning algorithms while also allowing designers to communicate abstractly with design software.

Keywords

Associative Logic; Creative Processes; Deep Learning; Embedding Vectors; Bimtovec; Homogeneous Design Data Format; Design Pixel; Idea Persistence

Participatory Infrastructures: The Politics of Mobility Platforms

Dunn, Peter T. (2020). Participatory Infrastructures: The Politics of Mobility Platforms. Urban Planning, 5(4), 335 – 346.

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Abstract

Much of everyday life in cities is now mediated by digital platforms, a mode of organization in which control is both distributed widely among participants and sharply delimited by the platform's constraints. This article uses examples of smartphone-based platforms for urban mobility to argue that platforms create new political arrangements of the city, intermediating the social processes of management and movement that characterize urban life. Its empirical basis is a study of user interfaces, data specifications, and algorithms used in the operation and regulation of ride-hailing services and bike-share systems. I focus on three aspects of urban politics affected by platforms: its location, its participants, and the types of conflict it addresses. First, the programming forums in which decisions are encoded in and distributed through platforms' core digital architecture are new sites of policy deliberation outside the more familiar arenas of city politics. Second, travelers have new opportunities to use platforms for travel on their own terms, but this expanded participation is circumscribed by interfaces that presuppose individual, transactional engagement rather than a participation attentive to a broader social and environmental context. Finally, digital systems show themselves to be well suited to enforcing quantifiable distributional goals, but struggle to resolve the more nuanced relational matters that constitute the politics of everyday city life. These illustrations suggest that digital tools for managing transportation are not only political products, but also reset the stage on which urban encounters play out.

Keywords

Construction; Users; Digital Geographies; Infrastructure; Participation; Platform Urbanism; Shared-use Mobility

Searching for Housing in the Digital Age: Neighborhood Representation on Internet Rental Housing Platforms across Space, Platform, and Metropolitan Segregation

Hess, Chris; Acolin, Arthur; Walter, Rebecca; Kennedy, Ian; Chasins, Sarah; Crowder, Kyle. (2021). Searching for Housing in the Digital Age: Neighborhood Representation on Internet Rental Housing Platforms across Space, Platform, and Metropolitan Segregation. Environment And Planning A-economy And Space, 53(8), 2012 – 2032.

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Abstract

Understanding residential mobility, housing affordability, and the geography of neighborhood advantage and disadvantage relies on robust information about housing search processes and housing markets. Existing data about housing markets, especially rental markets, suffer from accuracy issues and a lack of temporal and geographic flexibility. Data collected from online rental platforms that are commonly used can help address these issues and hold considerable promise for better understanding the full distribution of available rental homes. However, realizing this promise requires a careful assessment of potential sources of bias as online rental listing platforms may perpetuate inequalities similar to those found in physical spaces. This paper approaches the production of rental advertisements as a social process driven by both contextual and property level factors. We compare data from two online platforms for the 100 most populated metropolitan areas in the United States to explore inequality in digital rental listing spaces and understand what characteristics are associated with over and underrepresentation of advertisements in certain areas. We find similar associations for socioeconomic measures between platforms and across urban and suburban parts of these metropolitan areas. In contrast, the importance of racial and ethnic composition, as well as broader patterns of segregation, for online representation differs substantially across space and platform. This analysis informs our understanding of how online platforms affect housing search dynamics through their biases and segmentation, and highlights the potential and limits in using the data available on these platforms to produce small area rental estimates.

Keywords

Fair Market Rents; Cities; Opportunity; Residential Mobility; Online Rental Listings; Rental Housing Markets; Housing Search; Inequality

Reinforcement Learning Approach To Scheduling Of Precast Concrete Production

Kim, Taehoon; Kim, Yong-woo; Lee, Dongmin; Kim, Minju. (2022). Reinforcement Learning Approach To Scheduling Of Precast Concrete Production. Journal Of Cleaner Production, 336.

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Abstract

The production scheduling of precast concrete (PC) is essential for successfully completing PC construction projects. The dispatching rules, widely used in practice, have the limitation that the best rule differs according to the shop conditions. In addition, mathematical programming and the metaheuristic approach, which would improve performance, entail more computational time with increasing problem size, let alone its models being revised as the problem size changes. This study proposes a PC production scheduling model based on a reinforcement learning approach, which has the advantages of a general capacity to solve various problem conditions with fast computation time and good performance in real-time. The experimental study shows that the proposed model outperformed other methods by 4-12% of the total tardiness and showed an average winning rate of 77.0%. The proposed model could contribute to the successful completion of off-site construction projects by supporting the stable progress of PC construction.

Keywords

Precast Concrete; Reinforcement Learning; Deep Q -network; Production Scheduling; Minimize; Model