Tetteh, M. O., Darko, A., Boateng, E. B., & Chan, A. P. C. (2024). Energy Efficiency Retrofitting of Existing Building Stock for Net Zero. In Rethinking Pathways to a Sustainable Built Environment (pp. 142–158). Routledge. https://doi.org/10.1201/9781003317890-9
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Abstract
Existing buildings’ retrofits improve energy efficiency and are a crucial part of global decarbonization plan. There is a need for a better understanding of public sentiment toward energy efficiency retrofitting of existing buildings (EEREB) to effectively promote its widespread adoption through policy interventions. Currently, there is a lack of comprehensive studies that assess the general public's sentiments toward EEREB. This chapter utilizes social media data to assess the overall public's sentiments of EEREB. Sentiment analysis was used to analyze a total of 3,306 comments from the social media platform YouTube. The concerns and perceptions of the public were analyzed using a Latent Dirichlet Allocation model, which identified nine main themes. These themes include ventilation, energy efficiency, indoor environment quality, comfort and occupant behavior, cost considerations, community engagement, technology usage, implementation knowledge, and social impact. The public expressed stronger positive sentiments, with about 64% reporting favorable views of EEREB and acknowledging its benefits. In addition, interesting patterns of perceptions shaped by a combination of generic and local-specific factors were identified. This chapter enhances the understanding of the general public's needs, concerns, and views on EEREB. Additionally, it could provide valuable insights for policymakers to refine or develop more effective actions in support of EEREB.
Debrah, C., Chan, A. P. C., Darko, A., Owusu-Manu, D.-G., & Ohene, E. (2024). Green Finance. In Rethinking Pathways to a Sustainable Built Environment (pp. 277–302). Routledge. https://doi.org/10.1201/9781003317890-18
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Abstract
Green building is an “unheralded hero” in the global emissions fight. Its business case has raised demand from several stakeholders. It is seen as a multitrillion-dollar business opportunity of the next decade, leading to increased green finance (GF) investment for green building. GF is accepted as a tool to finance climate change mitigation and adaptation actions, including buildings and construction. To promote GF for green building, collaboration efforts between governments, businesses, investors, and the public are key. This chapter presents the evolution of GF for green building, an overview of the implementation and its potentials, with a focus on the role of stakeholders, policies, regulations, and incentives. Typologies of GF for green building and some examples of success stories are discussed. Other related issues such as green standards, green certifications, and green indices are examined. This chapter facilitates a systematic and comprehensive understanding of the subject. Overall, it summarises the development of GF in this field and the consequent impact on climate action.
Xiao, B., Wang, Y., Zhang, Y., Chen, C., & Darko, A. (2024). Automated daily report generation from construction videos using ChatGPT and computer vision. Automation in Construction, 168, 105874-. https://doi.org/10.1016/j.autcon.2024.105874
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Abstract
Daily reports are important in construction management, informing project teams about status, enabling timely resolutions of delays and budget issues, and serving as official records for disputes and litigation. However, current practices are manual and time-consuming, requiring engineers to physically visit sites for observations. To fill this gap, this paper proposes an automated framework to generate daily construction reports from on-site videos by integrating ChatGPT and computer vision (CV)-based methods. The framework utilizes CV methods to analyze video footage and extract relevant productivity and activity information, which is then fed into ChatGPT using proper prompts to generate daily reports. A web application is developed to implement and validate the framework on a real construction site in Hong Kong, generating daily reports over a month. This research enhances construction management by significantly reducing documentation efforts through generative artificial intelligence, with potential applications in jobsite safety management, quality reporting, and stakeholder communication.
Keywords
Construction daily report generation; Computer vision; ChatGPT; Construction management; Project documentation
The American Institute of Architects is hosting a webinar on their online learning platform AIAU, about the Building Owners Assessment Tool (BOAT) developed by Carrie Sturts Dossick along with her project team members. Other course instructors are Markku Allison, AIA; Greg Gidez, AIA, FDBIA; and Laura F. Stagner, FAIA, DBIA, PMP. The course was recorded live in October 2024 and is available as a resource on the AIAU website until 2027. View the course on the AIAU website here.
Professor Carrie Sturts Dossick, Associate Dean for Research, and Assistant Professor Lingzi Wu both from the department of Construction Management, presented at the 2024 Northwest Construction Consumer Council (NWCCC) Conference, “AI and Digital Technology in Construction” and Distinguished Project Awards. Their presentations are linked below. Assistant Professor Wu gave a presentation entitled “AI-Powered Solutions for Next-Generation Construction Management.” Professor Sturts Dossick presented on Cybersecurity Planning.
Mousavinezhad, S., Toledo, W. K., Newtson, C. M., & Aguayo, F. (2024). Rapid Assessment of Sulfate Resistance in Mortar and Concrete. Materials, 17(19), 4678-. https://doi.org/10.3390/ma17194678
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Abstract
Extensive research has been conducted on the sulfate attack of concrete structures; however, the need to adopt the use of more sustainable materials is driving a need for a quicker test method to assess sulfate resistance. This work presents accelerated methods that can reduce the time required for assessing the sulfate resistance of mixtures by 70%. Class F fly ash has historically been used in concrete mixtures to improve sulfate resistance. However, environmental considerations and the evolving energy industry have decreased its availability, requiring the identification of economically viable and environmentally friendly alternatives to fly ash. Another challenge in addressing sulfate attack durability issues in concrete is that the standard sulfate attack test (ASTM C1012) is time-consuming and designed for only standard mortars (not concrete mixtures). To expedite the testing process, accelerated testing methods for both mortar and concrete mixtures were adopted from previous work to further the development of the accelerated tests and to assess the feasibility of testing the sulfate resistance of mortar and concrete mixtures rapidly. This study also established criteria for interpreting sulfate resistance for each of the test methods used in this work. A total of 14 mortar mixtures and four concrete mixtures using two types of Portland cement (Type I and Type I/II) and various supplementary cementitious materials (SCMs) were evaluated in this study. The accelerated testing methods significantly reduced the evaluation time from 12 months to 21 days for mortar mixtures and from 6 months to 56 days for concrete mixtures. The proposed interpretation method for mortar accelerated test results showed acceptable consistency with the ACI 318-19 interpretations for ASTM C1012 results. The interpretation methods proposed for the two concrete sulfate attack tests demonstrated excellent consistency with the ASTM C1012 results from mortar mixtures with the same cementitious materials combinations. Metakaolin was shown to improve sulfate resistance for both mortar and concrete mixtures, while silica fume and natural pozzolan had a limited impact. Using 15% metakaolin in mortar or concrete mixtures with Type I/II cement provided the best sulfate resistance.
Keywords
accelerated test method; concrete; metakaolin; mortar; natural pozzolan; sulfate attack
In FY24, CBE researchers have been awarded a number of grants and contracts for projects that include a community engagement component, defined as “collaboration between institutions of higher education and their larger communities (local, regional/state, national, global) for the mutually beneficial creation and exchange of knowledge and resources in a context of partnership and reciprocity,” by The Carnegie Foundation for the Advancement of Teaching. In FY24 (July 2023 – June 2024), CBE researchers were awarded 17 grant and contract awards,…
Dr. Carrie Sturts Dossick, Associate Dean for Research, and Professor in the department of Construction Management has been featured on the Building Innovation: The Podcast. The podcast episode is Season 2, Episode 1, and is part one of the NBIMS-US™ Series, and discusses the new module for Project BIM Requirements. Listen to the Podcast here: https://www.nibs.org/building-innovation-podcast
Adabre, M. A., Chan, A. P. C., Darko, A., Edwards, D. J., Yang, Y., & Issahaque, S. (2024). No Stakeholder Is an Island in the Drive to This Transition: Circular Economy in the Built Environment. Sustainability, 16(15), 6422-. https://doi.org/10.3390/su16156422
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Abstract
Ensuring optimum utilisation of the Earth’s finite resources engenders the circular economy (CE) concept which has attracted the attention of policymakers and practitioners worldwide. As a bifurcated strategy which involves both scientific knowledge, advanced technologies and behavioural changes, the CE transition is sociotechnical in nature. Yet, prolific studies focus on scientific knowledge and technologies alone, while studies on promoting CE practices or built environment stakeholders’ behaviour are limited. Using Stakeholder Theory, a comprehensive literature review on CE drivers was conducted. Through a questionnaire survey of professionals, key drivers identified were deployed to develop a 20-driver model for CE transition in the built environment. The model is relevant to policymakers and practitioners because it highlights essential drivers for optimum resource allocation. Moreover, the findings apprise policymakers of the drivers that pertain to key stakeholders (i.e., professional and higher educational institutions, society and clients, government and firms), thus stating the requirements for driving each stakeholder to achieve this sociotechnical transition.
Keywords
circular economy; sociotechnical transition; sustainability; drivers; stakeholder theory; waste reduction
Ohene, E., Nani, G., Antwi-Afari, M. F., Darko, A., Addai, L. A., & Horvey, E. (2024). Big data analytics in the AEC industry: scientometric review and synthesis of research activities. Engineering, Construction, and Architectural Management. https://doi.org/10.1108/ECAM-01-2024-0144
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Abstract
Unlocking the potential of Big Data Analytics (BDA) has proven to be a transformative factor for the Architecture, Engineering and Construction (AEC) industry. This has prompted researchers to focus attention on BDA in the AEC industry (BDA-in-AECI) in recent years, leading to a proliferation of relevant research. However, an in-depth exploration of the literature on BDA-in-AECI remains scarce. As a result, this study seeks to systematically explore the state-of-the-art review on BDA-in-AECI and identify research trends and gaps in knowledge to guide future research.
This state-of-the-art review was conducted using a mixed-method systematic review. Relevant publications were retrieved from Scopus and then subjected to inclusion and exclusion criteria. A quantitative bibliometric analysis was conducted using VOSviewer software and Gephi to reveal the status quo of research in the domain. A further qualitative analysis was performed on carefully screened articles. Based on this mixed-method systematic review, knowledge gaps were identified and future research agendas of BDA-in-AECI were proposed.
The results show that BDA has been adopted to support AEC decision-making, safety and risk assessment, structural health monitoring, damage detection, waste management, project management and facilities management. BDA also plays a major role in achieving construction 4.0 and Industry 4.0. The study further revealed that data mining, cloud computing, predictive analytics, machine learning and artificial intelligence methods, such as deep learning, natural language processing and computer vision, are the key methods used for BDA-in-AECI. Moreover, several data acquisition platforms and technologies were identified, including building information modeling, Internet of Things (IoT), social networking and blockchain. Further studies are needed to examine the synergies between BDA and AI, BDA and Digital twin and BDA and blockchain in the AEC industry.
The study contributes to the BDA-in-AECI body of knowledge by providing a comprehensive scope of understanding and revealing areas for future research directions beneficial to the stakeholders in the AEC industry.
Keywords
Big data; Big data analytics; AEC; Bibliometric analysis; Systematic analysis