Journal of Information Technology in Construction最新文献

{"title":"A distributed collaborative platform for multi-stakeholder multi-level management of renovation projects","authors":"Omar Doukari, Mohamad Kassem, David Greenwood","doi":"10.36680/j.itcon.2024.011","DOIUrl":"https://doi.org/10.36680/j.itcon.2024.011","url":null,"abstract":"To meet European energy-saving and decarbonisation goals, the annual renovation rate of buildings requires to be at least twice its current level; an aspiration to which the use of innovative and automated solutions can contribute. This paper presents such a solution, the RINNO Retrofitting Manager (RRM) which is part of a large, ambitious research and development project (RINNO) that aims to provide an augmented intelligence-enabled framework for deep, energy-focused retrofitting of buildings. The RRM uses web-service technologies to rationalise the retrofitting process and optimise the delivery of renovation works, while making data readily accessible through an integrated set of role-based user interfaces. The RRM is designed and developed as an open distributed system, that is extensible and portable, by implementing a collaborative research and development approach. The RRM platform implements a multi-level, multi-stakeholder planning approach. It addresses the dearth, insufficiency, and isolation of existing renovation tools by enhancing collaboration, interoperability, and data security, and avoiding information loss and misunderstanding. Employing the Unified Theory of Acceptance and Use of Technology (UTAUT) model, tests conducted with users from independent construction organisations confirmed the RRM's satisfactory performance, ease of deployment, and overall suitability for the management of renovation projects. While this research provides a free collaborative platform for managing renovation projects that can be used by all building retrofit stakeholders in Europe, it also introduces a set of web-services that can be easily reused by third-party developers and integrated into their software tools.","PeriodicalId":51624,"journal":{"name":"Journal of Information Technology in Construction","volume":null,"pages":null},"PeriodicalIF":3.5,"publicationDate":"2024-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140368903","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 review of drivers and barriers of Digital Twin adoption in building project development processes","authors":"Muhammad Farhan Jahangir, Carl Schultz, A. Kamari","doi":"10.36680/j.itcon.2024.008","DOIUrl":"https://doi.org/10.36680/j.itcon.2024.008","url":null,"abstract":"Over the past few years, the AECO Industry has undergone a shift toward digital transformation, with a growing trend towards adopting innovative technologies such as Digital Twin (DT). DT offers a wide range of applications throughout the building development process. However, some specific factors impede its widespread adoption in the building industry. This study aims to systematically review the available literature on the building project development process from the perspective of DT, with a particular focus on predictive simulations, i.e., co-sims. The review provides a comprehensive overview of drivers and barriers to DT adoption through an analysis of 147 studies between 2013 and 2023. The research identifies seven external and 41 internal drivers, including efficient project management and monitoring, predictive maintenance, and the collection and visualization of real-time data, all of which contribute to improved decision-making processes and reduced operational expenses. Further, the study identifies nine external and 31 internal barriers that impede the adoption of DT in the building development process. These barriers encompass challenges such as a high initial investment cost, a scarcity of a skilled workforce, difficulties in data interoperability, and resistance to change within the organization. A key outcome of the literature review is having identified the opportunity to exploit technologies developed in the automotive sector that enable a seamless integration of specialized simulator models in building development processes, resulting in collaborative simulations. Thus, we propose the concept of a Building Simulation Identity Card (BSIC) to be pursued in future research that would enable stakeholders to address the challenges of collaboration, cooperation, coordination, and communication by creating a common vocabulary to effectively facilitate the adoption of DT in the building's development process.","PeriodicalId":51624,"journal":{"name":"Journal of Information Technology in Construction","volume":null,"pages":null},"PeriodicalIF":3.5,"publicationDate":"2024-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140372023","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":"Integration of BIM data and real-time game engine applications: Case studies in construction safety management","authors":"Ahmad Akib Uz Zaman, Ahmed Abdelaty, Md. Habibur Rahman Sobuz","doi":"10.36680/j.itcon.2024.007","DOIUrl":"https://doi.org/10.36680/j.itcon.2024.007","url":null,"abstract":"Building Information Modeling (BIM) has unique features that improve safety management in construction by visually identifying potential risks. Integrating BIM with a real-time game engine is a cutting-edge idea for more effective safety management. This study aims to conduct two case studies by integrating BIM data with game engines from two aspects: 1) Construction Safety Training and 2) Pre-construction Safety Management. A framework that covers techniques for extraction of safety ideas, managing the game engine, and character modeling tools and resources is used to carry out the case studies. In the first case study, a construction site was created by Revit, and a real-life scaffolding failure accident was simulated by Unity to warn workers to prevent similar future events. The second case study was conducted on the procedure of evacuation modeling in an emergency, integrating a BIM model and Unity following distinct pathways. This evacuation modeling can be used as a training platform for the occupants to acquaint themselves with the inside facility, show directions of the shortest evacuation path from specific points, and provide necessary information on emergency equipment. Finally, the study explains how the integration of the BIM model and game engine applications can be applied for effective, straightforward, and helpful safety management with the most efficient BIM data transition.","PeriodicalId":51624,"journal":{"name":"Journal of Information Technology in Construction","volume":null,"pages":null},"PeriodicalIF":3.5,"publicationDate":"2024-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140240148","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":"Influence of pre-processing methods on the automatic priority prediction of native-language end-users’ maintenance requests through machine learning methods","authors":"M. D’Orazio, G. Bernardini, E. Di Giuseppe","doi":"10.36680/j.itcon.2024.006","DOIUrl":"https://doi.org/10.36680/j.itcon.2024.006","url":null,"abstract":"Feedback and requests by occupants are relevant sources of data to improve building management, and building maintenance. Indeed, most predictable faults can be directly identified by occupants and communicated to facility managers through communications written in the end-users’ native language. In this sense, natural language processing methods can support the request identification and attribution process if they are robust enough to extract useful information from these unstructured textual sources. Machine learning (ML) can support assessing and managing these data, especially in the case of many simultaneous communications. In this field, the application of pre-processing and ML methods to English-written databases has been widely provided, while efforts in other native languages are still limited, impacting the real applicability. Moreover, the performance of combinations of methods for pre-processing, ML and classification classes attribution, has been limitedly investigated while comparing different languages. To fill this gap, this work hence explores the performance of automatic priority assignment of maintenance end-users’ requests depending on the combined influence of: (a) different natural language pre-processing methods, (b) several supervised ML algorithms, (c) two priority classification rules (2-class versus 4-class), (d) the database language (i.e. the original database written in Italian, the native end-users’ language; a translated database version in English, as standard reference). Analyses are performed on a database of about 12000 maintenance requests written in Italian concerning a stock of 23 buildings open to the public. A random sample of the sentences is supervised and labelled by 20 expert annotators following the best-worst method to attribute a priority score. Labelled sentences are then pre-processed using four different approaches to progressively reduce the number of unique words (potential predictors). Five different consolidated ML methods are applied, and comparisons involve accuracy, precision, recall and F1-score for each combination of pre-processing action, ML method and the number of priority classes. Results show that, within each ML algorithm, different pre-processing methods limitedly impact the final accuracy and average F1-score. In both Italian and English conditions, the best performance is obtained by NN, LR, SVM methods, while NB generally fails, and by considering the 2-class priority classification scale. In this sense, results confirm that facility managers can be effectively supported by ML methods for preliminary priority assessments in building maintenance processes, even when the requests database is written in end-users’ native language.","PeriodicalId":51624,"journal":{"name":"Journal of Information Technology in Construction","volume":null,"pages":null},"PeriodicalIF":3.5,"publicationDate":"2024-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140239979","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":"Probabilistic forecasting of construction labor productivity metrics","authors":"Emil L. Jacobsen, Jochen Teizer, Søren Wandahl, Ioannis Brilakis","doi":"10.36680/j.itcon.2024.004","DOIUrl":"https://doi.org/10.36680/j.itcon.2024.004","url":null,"abstract":"This study investigates the possibility of doing probabilistic forecasting of construction labor productivity metrics for both long-term and short-term estimates. The research aims to evaluate autoregressive forecasting models, which may help decision-makers with information currently unavailable in construction projects. Unlike point forecasts, the proposed method employs probabilistic forecasting, offering additional valuable insights for decision-makers. The distributional information is obtained by updating the moments of the distribution during training. Two datasets are used to evaluate the models: one collected from an entire construction site for long-term forecasting and one from an individual worker for short-term forecasting. The models aim to predict the state of direct work, indirect work, and waste. Several models are trained using different hyperparameters. The models are tuned on the number of trees and the regularization used. The presented method gives estimates of future levels of direct work, indirect work, and waste, which will add value to future processes.","PeriodicalId":51624,"journal":{"name":"Journal of Information Technology in Construction","volume":null,"pages":null},"PeriodicalIF":3.5,"publicationDate":"2024-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140445611","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":"Optimization and evaluation of a neural network based policy for real-time control of construction factory processes","authors":"Xiaoyan Zhou, Ian Flood","doi":"10.36680/j.itcon.2024.005","DOIUrl":"https://doi.org/10.36680/j.itcon.2024.005","url":null,"abstract":"This paper focuses on the development, optimization, and evaluation of an intelligent real-time control system for the fabrication of precast reinforced concrete components. The study addresses the unique challenges associated with real-time control in the construction manufacturing industry, including high customization, uncertain work demand, and limited stockpiling opportunities. A production system model is built based on a real construction manufacturing factory to simulate real-world precast reinforced concrete component fabrication, and acts as the basis for the development and validation of the control system. A review of alternative decision-making techniques is presented to identify the most suitable for the control of construction manufacturing factories. Ultimately, an artificial neural network approach trained using a reinforcement learning strategy is selected as a promising technique for effective real-time control. The controller is developed and validated, and its performance is optimized using sensitivity analysis, which takes into account both the structure of the artificial neural network and the parameters of the reinforcement learning algorithm. The ANN-based control policy is applied to the sequencing of precast reinforced concrete component production, while a rule-of-thumb policy is used as a benchmark for comparison. The study demonstrates that the optimized ANN-based control policy significantly outperforms the standard rule-of-thumb policy. The paper concludes by providing suggestions for further advancement of the ANN-based approach and potential avenues to increase the control policy's scope of application in construction manufacturing.","PeriodicalId":51624,"journal":{"name":"Journal of Information Technology in Construction","volume":null,"pages":null},"PeriodicalIF":3.5,"publicationDate":"2024-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140443212","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":"Novel framework for BIM interoperability for sustainability and green buildings - an application for concrete structures","authors":"Marina Muller, Filipe Esmanioto, Natan Huber, Eduardo F. R. Loures, Osisris Canciglieri Junior, Aaron Costin","doi":"10.36680/j.itcon.2024.003","DOIUrl":"https://doi.org/10.36680/j.itcon.2024.003","url":null,"abstract":"The construction industry has a great impact on the environment, therefore sustainable construction presents itself as a growing requirement of society. However, the concern with green buildings must not only be considered during the construction stage, but also during the entire life cycle of the building, integrating all stages from the design up until the demolition. Ensuring that the information permeates this lifecycle without data losses is vital. This way, efficient interoperability can support sustainability, allowing data to feed the process, and promoting the creation of more sustainable buildings. BIM (Building Information Modeling) arises as a means to support interoperability improvements in the AEC (Architecture, Engineering, and Construction) industry, by sharing models through open formats and enabling communication amongst actors. This paper presents a framework for BIM interoperability, with the goal to support knowledge organization and aid users in the decision-making processes. It will allow users to track sustainability concepts throughout the entire green BIM lifecycle and to improve processes in the construction industry toward more interoperable processes, minimizing data loss, and improving communication and efficiency. The framework is presented through process mapping techniques to analyze and integrate sustainability concepts using BIM throughout the lifecycle of a building. This framework considers not only data interoperability but also other aspects such as process, business, and service interoperability. Also, an application of the framework is described, using the case of cast-in-place concrete structures. Research findings identified the critical data points in the lifecycle of concrete structures which can influence sustainability.","PeriodicalId":51624,"journal":{"name":"Journal of Information Technology in Construction","volume":null,"pages":null},"PeriodicalIF":3.5,"publicationDate":"2024-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139798780","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":"Construction 4.0: A comparative analysis of research and practice","authors":"Nathalie Perrier, Aristide Bled First, Mario Bourgault, Nolwenn Cousin, Christophe Danjou, Robert Pellerin, Thibaut Roland","doi":"10.36680/j.itcon.2024.002","DOIUrl":"https://doi.org/10.36680/j.itcon.2024.002","url":null,"abstract":"This paper presents an overview of the existing literature on Construction 4.0 technologies over the past decade and their most common applications in both research and practice, aimed at achieving three objectives. First, the search for the most relevant articles on Construction 4.0, published in the scientific literature, and small firms that are developing and delivering 4.0 technologies in the construction industry allows to identify the numerous applications associated with Construction 4.0. Second, the applications found in the scientific literature and those identified in practice are classified and compared based on a framework consisting of three distinct axes. Third, the classification framework highlights current research trends and potential areas for future research, which can be summarized as follows: (i) development of hybrid digital solutions; (ii) alignment with effective collection of more structured data, smart interactive web technologies, robotics, autonomous systems, and intelligent built assets; and (iii) strengthen the capacities of artificial intelligence and machine learning.","PeriodicalId":51624,"journal":{"name":"Journal of Information Technology in Construction","volume":null,"pages":null},"PeriodicalIF":3.5,"publicationDate":"2024-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139859037","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":"Improving Learners’ Self-Efficacy in Performing Design Reviews with Virtual Reality","authors":"Fadi Castronovo, SeyedReza RazaviAlavi, Pablo Martinez Rodriguez","doi":"10.36680/j.itcon.2024.001","DOIUrl":"https://doi.org/10.36680/j.itcon.2024.001","url":null,"abstract":"Research on the use of innovative technology, such as virtual reality (VR), in Architecture, Engineering, and Construction (AEC) education, has been growing in the past twenty years. However, such research still requires robust investigation, as few studies have adopted educational psychology theories and rigorous methods. Furthermore, most of the research has focused on the cognitive effects of VR and additional research is also needed to investigate the affective effects, such as motivation, engagement, and self-efficacy. This study aims to evaluate the effects of technology decision-making between immersive virtual reality (IVR) and non-immersive virtual reality (nIVR) setups for a learning activity on AEC learners. For this, three hypotheses are formulated and tested on 165 UK students. Based on the results, both the designed IVR and nIVR learning activities had significant positive effects on learners’ self-efficacy and user experience with no significant difference between IVR and nIVR delivery. With this research, the authors contribute to the growing literature on VR implementation in AEC classrooms by showcasing a study founded on educational psychology theory and by using a rigorous research methodology. Furthermore, this study illustrates the effects that IVR and nIVR have on students’ affective learning and opens the possibility of new research in the field.","PeriodicalId":51624,"journal":{"name":"Journal of Information Technology in Construction","volume":null,"pages":null},"PeriodicalIF":3.5,"publicationDate":"2024-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139860046","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":"Novel framework for BIM interoperability for sustainability and green buildings - an application for concrete structures","authors":"Marina Muller, Filipe Esmanioto, Natan Huber, Eduardo F. R. Loures, Osisris Canciglieri Junior, Aaron Costin","doi":"10.36680/j.itcon.2024.003","DOIUrl":"https://doi.org/10.36680/j.itcon.2024.003","url":null,"abstract":"The construction industry has a great impact on the environment, therefore sustainable construction presents itself as a growing requirement of society. However, the concern with green buildings must not only be considered during the construction stage, but also during the entire life cycle of the building, integrating all stages from the design up until the demolition. Ensuring that the information permeates this lifecycle without data losses is vital. This way, efficient interoperability can support sustainability, allowing data to feed the process, and promoting the creation of more sustainable buildings. BIM (Building Information Modeling) arises as a means to support interoperability improvements in the AEC (Architecture, Engineering, and Construction) industry, by sharing models through open formats and enabling communication amongst actors. This paper presents a framework for BIM interoperability, with the goal to support knowledge organization and aid users in the decision-making processes. It will allow users to track sustainability concepts throughout the entire green BIM lifecycle and to improve processes in the construction industry toward more interoperable processes, minimizing data loss, and improving communication and efficiency. The framework is presented through process mapping techniques to analyze and integrate sustainability concepts using BIM throughout the lifecycle of a building. This framework considers not only data interoperability but also other aspects such as process, business, and service interoperability. Also, an application of the framework is described, using the case of cast-in-place concrete structures. Research findings identified the critical data points in the lifecycle of concrete structures which can influence sustainability.","PeriodicalId":51624,"journal":{"name":"Journal of Information Technology in Construction","volume":null,"pages":null},"PeriodicalIF":3.5,"publicationDate":"2024-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139858727","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}