Journal of Information Technology in Construction最新文献

{"title":"ENERGYSIM: techniques for advancing building energy education through immersive virtual reality (VR) simulation","authors":"Hassan Anifowose, Kifah Alhazzaa, Manish Dixit","doi":"10.36680/j.itcon.2023.028","DOIUrl":"https://doi.org/10.36680/j.itcon.2023.028","url":null,"abstract":"An important practice for reducing the effects of global warming is the design and construction of energy-efficient buildings. In design education, the full comprehension of thermal behavior in buildings based on their geometry and material composition is required. The complexity of energy simulation principles, vis-a-vis the number of elements that impact the energy loads, their linkages, and their relationships to one another all combine to make this a challenging subject to absorb. Virtual Reality (VR) provides an immersive way to learn the concepts of building energy responses; however, the development of VR applications for education is difficult due to the knowledge, skill, and performance resource-related gaps. Unoptimized VR applications can adversely impact learning if user experiences are broken due to performance lags. This research, therefore, explores VR as a teaching tool for building energy education while showcasing the development process toward a visually accurate simulation and performant application. We developed EnergySIM; a multi-user VR building energy simulation prototype of the famous Farnsworth House. Using this prototype, we document rigorously tested development workflows for improved VR game performance, high visual fidelity, and user interaction, the three key factors which positively contribute to user knowledge retention. The study combines menu-driven interaction, virtual exploration, and miniature model manipulation approaches with the aim of testing user understanding and knowledge retention. Highlighted results provide reduced barriers of entry for educators towards developing higher quality educational VR applications. EnergySIM showcases pre-simulated building exterior surface heatmaps response from four seasons (winter, summer, fall, and spring) alongside an all-year-round sun-hour scenario. Four different material pre-simulated scenarios (single glazing, double glazing, concrete, and wood) for interior atmospheric temperature mapping are also explored. Preferred interaction methods are documented by allowing users’ visual appraisal of alternative building materials based on insulation capacity or resistance to heat flow (R-value). The significance of this work lies in its potential to revolutionize how students, designers, and instructors approach building energy education in today’s world. EnergySIM provides a hands-on and visually engaging learning experience towards the enhancement of knowledge retention and understanding. It pushes the boundaries of development for visual fidelity using geometry/mesh modeling input from various software into game engines and optimizing game performance using the HTC Vive Pro Eye and Meta Quest Pro headsets.","PeriodicalId":51624,"journal":{"name":"Journal of Information Technology in Construction","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136060774","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Operations, IT, and construction time orientations and the challenges of implementing IOT","authors":"Carrie Sturts Dossick, Madision Snider, Laura Osburn","doi":"10.36680/j.itcon.2023.031","DOIUrl":"https://doi.org/10.36680/j.itcon.2023.031","url":null,"abstract":"The adoption of Internet of Things has grown significantly in recent years both to address sustainability in campus operations and as part of digital twin systems. This study looks at in-depth cases of large university campus owners and the challenges that this IOT introduces for the maintenance and management of these systems and the data they collect. In this ethnography there are three main time orientations related to facilities management (Facilities), Information Technology (IT), and Capital Projects. First, a university campus is like a small city, with buildings, utilities, and transportation systems - taken together we call this campus infrastructure (buildings 50-100, roads and utilities 20-50 years). Second, IT employees think on 2–3-month scale, working through implementing software and hardware upgrades, configurations and patches, at times needing agile operations to deal with emerging cybersecurity threats. Third, in Capital Projects the design phase can last 9 months, and the construction from 1 - 2 years for a typical project, and this is where IOT technologies are often first introduced into campus. While the capital project teams reflect on the user experience, these teams are often removed from the realities of facilities management and do not understand the time scales or the scope of the work that is required to manage a portfolio of Facilities and IT systems. In this paper, we explore how these time orientations lead to tensions in the owners’ selection of IOT devices and systems, in the integration of new technologies into existing systems, and in the operations of keeping existing systems up and running for the longer time scales of campus infrastructure life spans. Furthermore, this paper presents a paradox: If they speed up, they lose things, if they slow down, they lose other things, and presents ways that owner organizations manage this paradox through temporal boundary spanners who understand the disciplinary requirements, cultures, and frameworks across the organization and helps to mitigate the tensions across these differences.","PeriodicalId":51624,"journal":{"name":"Journal of Information Technology in Construction","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136061089","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Sensing technologies in construction engineering education: industry experiences and expectations","authors":"O. Ogunseiju, Nihar J. Gonsalves, A. Akanmu, D. Bairaktarova, P. Agee, Kereshmeh Asfari","doi":"10.36680/j.itcon.2023.024","DOIUrl":"https://doi.org/10.36680/j.itcon.2023.024","url":null,"abstract":"As the construction industry continues to advance technologically, the adoption of sensing technologies is gradually gaining momentum. Sensing technologies (such as radio frequency identification systems, laser scanners, cameras, and global position systems) play a significant role in reducing costs, improving project productivity, and enhancing workers' health and safety. This has prompted the need for a workforce with the required skills and knowledge for deploying sensing technologies in the industry. Since construction-related education is aimed at preparing students for the future of the industry, it is important to investigate the industry’s expectations for equipping the future workforce with the required skills. This study adopts a mixed-method research approach. Data are collected from surveys, case studies, and a focus group discussion with industry practitioners. The data elucidate participants’ perceptions, attitudes, and beliefs regarding: the skills required, and level of knowledge transfer required to advance sensing technologies on construction projects, and the value and anticipated demand for these skills. The findings also revealed the extent to which sensing technologies are deployed in the industry and the benefits driving the adoption of these technologies. The results reveal a high rate of adoption of sensing technologies amongst industry practitioners and inform construction applications and skills to be taught in construction engineering education. This study contributes to the existing scarce literature on the knowledge and skill demands of the industry to implement sensing technologies. The findings provide critical feedback for expanding the construction education curriculum to meet up the industry’s demand and adequately prepare the future workforce.","PeriodicalId":51624,"journal":{"name":"Journal of Information Technology in Construction","volume":null,"pages":null},"PeriodicalIF":3.5,"publicationDate":"2023-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69721297","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Overview of BIM contributions in the construction phase: review and bibliometric analysis","authors":"James Olaonipekun Toyin, M. Mewomo","doi":"10.36680/j.itcon.2023.025","DOIUrl":"https://doi.org/10.36680/j.itcon.2023.025","url":null,"abstract":"Building Information Modelling (BIM) is a revolutionary invention within the construction industry that essentially aids the design, construction and management of construction projects throughout their lifespan. Globally, the Architecture, Engineering, and Construction (AEC) industry has for decades progressively adopted and implemented BIM. While there are several papers in this context, none have tried to extensively document BIM’s comprehensive contributions and uses in the construction phase. Therefore, this paper aims to identify BIM’s various contributions and uses in the construction phase and analyze publication trends, co-occurring keywords, contributing authors and countries. A systematic overview approach was used to review published articles on state-of-the-art of BIM in construction, supported by bibliometric network mapping analysis. A total of 409 documents were extracted and analyzed. The study’s findings document BIM’s various uses and contributions to the AEC industry, such as simulation of each stage of the construction process, virtual presentation of the building and site, visualization of progress, management of construction work, enhancement of safety, communication and collaboration, quick generation of reliable and accurate cost estimates, assistance in the fast realization of return on investment (ROI), and serving as a platform that hosts and documents various technological tools used during the construction phase. The bibliometric analysis reveals the most contributing scholars, countries, document sources, trend network mapping of co-occurring keywords, and publication trends. The primary practical implications of this study’s discoveries can be exploited as a basis for further research and to influence the future direction of BIM in the AEC industry. The findings will enhance the wider spread, application and understanding of BIM in the AEC industry, thereby increasing BIM awareness and knowledge globally.","PeriodicalId":51624,"journal":{"name":"Journal of Information Technology in Construction","volume":null,"pages":null},"PeriodicalIF":3.5,"publicationDate":"2023-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69721310","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Systematic Literature Review on 360° Panoramic Applications in Architecture, Engineering, and Construction (AEC) Industry","authors":"Y. Shinde, Kyeongsuk Lee, Beyza Kiper, Makayla Simpson, Sogand Hasanzadeh","doi":"10.36680/j.itcon.2023.021","DOIUrl":"https://doi.org/10.36680/j.itcon.2023.021","url":null,"abstract":"While the advancement of visualization technologies—virtual-reality, augmented-reality, mixed-reality, and extended reality—has long produced opportunities to create more realistic simulated environments to provoke and study natural human behavior, recent interest in applying 360° panoramic visualizations has been increasing across several disciplines due to these technologies’ lower costs, higher presence, and greater immersive-ness. However, the variety of applications of 360° panoramas (both images and videos) is limited in the architecture, engineering, and construction (AEC) domain compared to other domains. This paper systematically presents an in-depth understanding of 360° panorama research trends and reveals the challenges and opportunities for future research in the AEC area. In particular, this systematic review analyzed eighty studies across two decades (2000-2022) to consider 360° panoramas’ application areas, methodologies, potential benefits, challenges, best practices, and future research directions for both AEC and non-AEC domains. Several prevalent application domains in AEC—namely architectural studies, construction education and training, construction visualization and progress monitoring, and cognitive analysis and human behavior in the construction industry—were identified. This paper indicates that 360° panoramas provide a higher sense of presence than conventional simulation methods (e.g., virtual reality). Moreover, pairing 360° panorama technologies with a head-mounted display significantly increases immersion when compared with other display options. Lastly, limitations of 360° panoramas, such as cybersickness and technical properties, are discussed. This paper is expected to shed light on the potential of these state-of-the-art technologies in the AEC domain, which can serve both academia and industry.","PeriodicalId":51624,"journal":{"name":"Journal of Information Technology in Construction","volume":null,"pages":null},"PeriodicalIF":3.5,"publicationDate":"2023-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69721411","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Road modelling for infrastructure management - the efficient use of geographic information systems","authors":"A. Pavard, A. Dony, Patricia Bordin","doi":"10.36680/j.itcon.2023.022","DOIUrl":"https://doi.org/10.36680/j.itcon.2023.022","url":null,"abstract":"The construction sector is undergoing a digital transition. Local authorities have adopted geographic information systems (GISs) to plan their territories and structure their services, such as transport. Simultaneously, building information modelling (BIM) has demonstrated its advantages during the design and construction phases of structures. An infrastructure project can rely on these two technologies to plan its implementation (GIS), to complete its design and construction (BIM), or to manage associated services, such as mobility (GIS). However, road maintenance, an important part of the infrastructure’s life cycle, is not yet covered by these technologies. Road maintenance necessitates a comprehensive view of the infrastructure and its interactions with other real-world objects (e.g. vegetation, technical networks, or vehicles). Moreover, road managers are the local authorities that already use GISs. For these reasons, a GIS is suitable for fulfilling road maintenance requirements. This study presents a spatial framework (GIS) developed for road management. Applying it to a specific case study provides insights on the organisation of the spatial road framework which can be adapted to the infrastructure’s environment management. The spatial dimension must allow for the representation of the road and its components, including pavements and their dependencies. The structural dimension must be detailed to describe the layers, their formulations, and their thicknesses. The condition of the road must be described concisely so that the managers can plan maintenance.","PeriodicalId":51624,"journal":{"name":"Journal of Information Technology in Construction","volume":null,"pages":null},"PeriodicalIF":3.5,"publicationDate":"2023-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69721479","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Relevance of deep sequence models for recognising automated construction activities: a case study on a low-rise construction system","authors":"Aparna Harichandran, B. Raphael, Abhijit Mukherjee","doi":"10.36680/j.itcon.2023.023","DOIUrl":"https://doi.org/10.36680/j.itcon.2023.023","url":null,"abstract":"Recognising activities of construction equipment is essential for monitoring productivity, construction progress, safety, and environmental impacts. While there have been many studies on activity recognition of earth excavation and moving equipment, activity identification of Automated Construction Systems (ACS) has been rarely attempted. Especially for low-rise ACS that offers energy-efficient, cost-effective solutions for urgent housing needs, and provides more affordable living options for a broader population. Deep learning methods have gained a lot of attention because of their ability to perform classification without manually extracting relevant features. This study evaluates the feasibility of deep sequence models for developing an activity recognition framework for low-rise automated construction equipment. Time series acceleration data was collected from the structure to identify major operation classes of an ACS. Long Short Term Memory Networks (LSTM) were applied for identifying the activity classes and the performance was compared with that of traditional machine learning classifiers. Diverse augmentation methods were adopted for generating datasets for training the deep learning classifiers. Several recently published literature seem to establish the superiority of complex deep learning techniques over traditional machine learning algorithms regardless of the application context. However, the results of this study show that all the conventional machine learning classifiers perform equivalently or better than deep learning classifiers in identifying activities of the ACS. The performance of the deep learning classifiers is affected by the lack of diversity in the initial dataset. If the augmented dataset significantly alters the characteristics of the original dataset, it may not deliver good recognition results.","PeriodicalId":51624,"journal":{"name":"Journal of Information Technology in Construction","volume":null,"pages":null},"PeriodicalIF":3.5,"publicationDate":"2023-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69721755","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Digital transformation in construction - a review","authors":"Olle Samuelson, Lars Stehn","doi":"10.36680/j.itcon.2023.020","DOIUrl":"https://doi.org/10.36680/j.itcon.2023.020","url":null,"abstract":"Digital transformation (DT) is expected to contribute to the construction industry's ability to meet climate and sustainable challenges and increase companies' productivity. This study aims to explore requirements for, and factors affecting DT in the construction industry. This research goes beyond the technology perspective and focus on factors needed to transform the potential of digitalisation to benefits for organisations in the construction industry. A structured literature review is performed where knowledge gaps are identified, and a framework is developed that maps the required changes, as well as the associated challenges, constraints, and implications.\u0000The construction industry´s business-to-business logic, and the fragmented and project-based structure is found to have impact on the industry´s development within DT. Mainly regarding the DT aspects disruption, structural changes, organisational barriers, and the central aspect value creation. The understanding of DT by scholars and practitioners in the construction industry is found immature and this calls for further research. The research contributes to understanding of the concept DT and proposes, based on earlier DT literature, an adjusted framework for DT in construction, and points out key areas where research in construction has gaps to fill.","PeriodicalId":51624,"journal":{"name":"Journal of Information Technology in Construction","volume":null,"pages":null},"PeriodicalIF":3.5,"publicationDate":"2023-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69721397","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Automated translation from domain knowledge to software model: EXCEL2UML in the tunneling domain","authors":"G. Paskaleva, A. Mazak-Huemer, Marlène Villeneuve, Johannes Waldhart","doi":"10.36680/j.itcon.2023.019","DOIUrl":"https://doi.org/10.36680/j.itcon.2023.019","url":null,"abstract":"The development of software tools is a collaborative process involving both the domain experts and the software engineers. This requires efficient communication considering different expertise and perspectives. Additionally, the two groups utilize language and communication tools in disparate ways. This, in turn, may lead to hidden misunderstandings in the requirement analysis phase and potentially result in implementation problems later on, that is difficult and costly to correct. In this paper, we demonstrate the above mentioned challenge via a use case from the tunneling domain. In particular, during the requirement analysis phase for a software capable of handling the data model of the subsoil. The domain experts in the field can best express the complexity of their domain by describing its artifacts, which in most cases are incomprehensible to the software engineers. We outline a method that interleaves requirement analysis and software modeling to enable an iterative increase of the accuracy and completeness of the information extracted from those artifacts and integrated into a flexible software model, which can produce testable software code automatically. Furthermore, we present a prototypical implementation of our method and a preliminary evaluation of the approach.","PeriodicalId":51624,"journal":{"name":"Journal of Information Technology in Construction","volume":null,"pages":null},"PeriodicalIF":3.5,"publicationDate":"2023-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69721683","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Machine learning approaches to determining truck type from bridge loading response","authors":"Yueren Wang, I. Flood","doi":"10.36680/j.itcon.2023.018","DOIUrl":"https://doi.org/10.36680/j.itcon.2023.018","url":null,"abstract":"The paper is concerned with the development and comparison of alternative machine learning methods of determining the type of truck crossing a bridge from the dynamic response it induces within the bridge structure, the so-called weigh-in-motion problem. Weigh-in-motion is a rich engineering problem presenting many challenges for current machine learning technologies, and for this reason is proposed as a benchmark for guiding and assessing advances in the application of this field of artificial intelligence. A review is first provided of existing methods of determining truck types and loading attributes using both machine learning and heuristic search techniques. The most promising approach to date, that of artificial neural networks, is then compared to support vector machines in a comprehensive study considering a range of configurations of both modeling techniques. A local scatter point smoothing schema is adopted as a means of selecting an optimal set of design parameters for each model type. Three main model formats are considered: (i) a monolithic model structure with a one-versus-all truck type classification strategy; (ii) an array of sub-models each dedicated to one truck type with a one-versus-all classification strategy; and (iii) an array of sub-models each dedicated to selecting between pairs of trucks in a one-versus-one classification strategy. Overall, the formats that used an array of sub-models performed best at truck classification, with the support vector machines having a slight edge over the artificial neural networks. The paper concludes with some suggestions for extending the work to a broader scope of problems.","PeriodicalId":51624,"journal":{"name":"Journal of Information Technology in Construction","volume":null,"pages":null},"PeriodicalIF":3.5,"publicationDate":"2023-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69721637","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}