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The Use of 4IR by Architects in Prevention of Pre-Construction project delays in South Africa
No full textThe purpose of this poster, based on a master\u27s degree research is to examine how 4IR affects architects\u27 abilities in South African pre-construction project development planning. The study will examine the competencies needed by architects in the early phases of project development, with an emphasis on their capacity to conceptualize, design, and schedule projects in a way that satisfies client needs, complies with legal requirements, and advances sustainability objectives. In addition to a thorough literature review to determine the body of knowledge already in existence on this subject, the research will include an overview of the potential application of 4IR technologies to improve the competencies of architects. Data will then be gathered from architects employed by various South African architectural firms through a quantitative survey. The results will show where architects now stand in terms of pre-construction project development planning competences, point out areas where they lack expertise, and make recommendations for professional development and architectural education initiatives in Uganda and South Africa. The goal of this research is to improve architectural practice and the general sustainability and efficiency of the building sector in South Africa
An Experimental Investigation for the Influence of Glass Type on Indoor Thermal Comfort and Cooling Energy Consumption
Get PDFAligned with the sustainable development goals of affordable energy, health, and well-being, there is a growing focus on building energy efficiency and indoor environmental quality (IEQ). Solar radiation increases indoor mean radiant temperature, causing thermal discomfort for occupants near windows. To mitigate discomfort, it is inevitable to lower the indoor temperature, which may lead to increased electricity consumption. We set up test units with glass types having SHGC from 0.28 to 0.85 and also installed sensors near windows to measure the impacts of solar radiation on PMV and cooling consumption. Environmental Quality Index (EQI) serves as an indicator for assessing thermal conditions. EQI categorizes time fractions into seven levels (A to G), based on PMV categories of the thermal environment. At a set-point of 26°C, the test unit equipped with the lowest SHGC records an average daily electricity consumption of 1.23 kWh/day, with an EQI of C. In comparison, the test unit with the highest SHGC consumes 2.96 kWh/day, reflecting an EQI of G. Lower SHGC glass effectively blocks incident sunlight, resulting in reduced electricity consumption and improved indoor thermal comfort. To address discomfort stemming from high SHGC values, the set point was lowered to 24°C. Consequently, the test unit with the highest SHGC experienced an increase in EQI to E, accompanied by higher electricity consumption of 3.57 kWh/day. This study emphasizes the importance of using EQI as a unified benchmark for comparing the energy-saving potential of glasses, as temperature-based assessments may underestimate the potential of low SHGC glass
Challenges and Benefits of Using BIM Technologies to Improve Construction Safety: An Exploratory Case Study
No full textBuilding Information Modeling (BIM) continues to experience rapid growth in the construction industry. BIM changes how design and construction can be approached by using algorithms that automatically assess various elements of project designs and construction, including potential safety risk. Compared with other approaches which evaluate safety risk during the design and execution phases, BIM models can help reduce the number of workers and resources used to ensure proper safety management. This paper presents a research study to investigate BIM technologies (e.g., Robotic Total Station and Navisworks) commonly implemented and any challenges and needed improvements to benefit construction safety. The research consisted of an explanatory investigation of a case study to gather comprehensive data on BIM implementation. The case study project was a life sciences building project in Portland, Oregon, USA, where the project personnel used BIM technologies to visualize the project and simulate environmental conditions for coordination to ensure efficient installation, stay on schedule, and identify potential hazards. The study revealed major challenges, including: (1) familiarity with BIM expectations, (2) financial challenges, and (3) turnover to the owner. The research contributions and outcomes benefit construction practitioners when training engineers to use BIM to predict potential hazards. The research also provides future recommendations on the use of BIM for construction safety management and practices
Developing a Smart Retrofitting Decision-Making Model for Office Buildings: A Case Study
No full textIn an era where the imperative for global sustainable development has never been more pronounced, this paper unveils the process in developing a novel, Smart Retrofitting (SR) decision-making model for buildings. With various intelligent automation routes/options offered by smart retrofits, streamlining the decision-making process in choosing the optimal retrofit options not only enhances efficiency but also empowers building stakeholders to play a pivotal role in advancing sustainable practices, fostering resource efficiency, and contributing to the global commitment to sustainable development goals. Employing a mixed-method approach, the early stages of this research, which involved an extensive literature review, a focus group study and a questionnaire survey, identified criteria for making SR decisions. The criteria were prioritized using the Analytic Network Process (ANP) weights derived from expert interviews. The developed model, as reported in this paper, was empirically tested on an office building in Hong Kong, showcasing its practical application. Utilizing Entropy-based weights and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method, the model enabled efficient selection of an optimal smart retrofit option, with the essential environmental, economic, technical, user-comfort and legal issues duly considered. The results of this research contribute to the discourse on sustainable urban development by offering not only a tangible framework for decision-making but also actionable guidance that can streamline smart decision-making in future SR initiatives in densely populated cities similar to Hong Kong
ConPPMF: Construction Datasets for Privacy-Preserving Mental Fatigue
No full textConstruction workers’ unsafe behavior is the leading cause of on-site accidents, greatly influenced by mental fatigue. Existing available datasets for mental fatigue are scarce in construction. Moreover, collecting and using private data, such as facial images, bio-signals, and speech, raises significant privacy concerns, leading to difficulty in data collection during model implementation. To tackle these challenges, this research aims to introduce a replicable multi-modal dataset named ConPPMF to monitor mental fatigue on construction sites, focusing on worker comfort and privacy. The dataset comprises physiological data from smartwatches and time-synchronized visual data from cameras. Fatigue status is labeled through self-reported assessments and on-the-job performance. The dataset includes 92 videos from 17 male workers in various trades, such as crane operators, truck drivers, excavators, and pavers, collected at three construction sites during actual work hours. The dataset has been rigorously evaluated under eight quality metrics: data integrity, interpretation, lineage, accessibility, accuracy, reliability, relevance, and privacy. Besides, ConPPMF achieved an F1-score of 0.84 and a recall of 0.95 in predictive models, outperforming YawDD and DROZY. These findings highlight the feasibility and ethical considerations of the ConPPMF dataset for real-world mental fatigue monitoring in construction. This research contributes to developing robust, privacy-preserving tools for early fatigue detection, ultimately enhancing construction safety and reducing on-site accidents
Indigenous Engagement Role in Sustainable Pipeline Construction: Canadian Insights
No full textThis paper examines the pivotal role of Indigenous engagement (IE) in fostering sustainable pipeline construction in Canada. It delves into how meaningful engagement with Indigenous communities contributes to social acceptance and project success. it examines how IE impacts the ESG score for pipeline projects, which in turn, affects the cost of capital for proceeding with projects. Using a case study, the paper finds that Indigenous engagement plays a crucial role in determining the weight and score of the social component in ESG evaluations. It concludes that improvements in Indigenous engagement can lead to a lower cost of capital, ultimately enhancing the economic sustainability of pipeline projects
Off-Site Construction SMEs Transition to Net-Zero
Get PDFWith the imperative to combat climate change and achieve net-zero targets by 2050, the construction industry faces growing pressure to adopt sustainable practices and reduce carbon emissions. Small and medium-sized enterprises (SMEs), which constitute the majority of the industry, often lack the resources and expertise to make this transition effectively. This paper investigates how off-site construction SMEs can implement actions to achieve net-zero carbon emissions, focusing on the integration of sustainable practices through Building Information Modelling (BIM) and Lean principles within a small off-site construction company. Using an action research approach, the study employed iterative cycles of planning, action, and reflection. Data collection included carbon footprint assessments, process mapping, stakeholder interviews, and workshops. The analysis identified inefficiencies that informed targeted interventions, such as enhancing in-house capabilities and digitalising processes to streamline operations and improve monitoring. Collaborative engagement ensured that solutions were both technically feasible and economically viable. The findings highlight the potential of Lean principles and BIM in advancing net-zero goals. The research offers valuable insights for SMEs, highlighting the critical role of collaborative and innovative approaches in driving net-zero transformation
Assessing AI Techniques for Precision in Property Valuation: A Systematic Review of the Four Valuation Methods
Get PDFProperty valuation is a critical component of real estate management, influencing decisions on investments, sales, and financing. Traditional methods, such as Linear Regression and Multiple Regression Analysis, often struggle to address the complexities of modern property markets. In response, Artificial Intelligence (AI) offers innovative solutions by utilising advanced models for more accurate predictions of property value. This paper presents a Systematic Literature Review (SLR) using Scopus database, focusing on 37 selected papers. It evaluates the effectiveness of key AI models in property valuation, assessing their predictive power, interpretability, robustness, and flexibility, and examines how well these models generate reliable valuations and their accuracy. The key models were referred to as the “Valuation Four”: Support Vector Machines (SVM), Random Forest (RF), Decision Trees (DT), and Regression Models (RM). The review highlights each model’s ability to handle complex real estate data, with SVM and RF demonstrating superior accuracy. At the same time, DT excels in interpretability, making it more user-friendly for decision-making. Regression-based models continue to serve as useful benchmarks but are less effective for intricate datasets. The findings of this study provide valuable insights for real estate professionals and policymakers by identifying the AI models that support precise and reliable property valuation on basis of dataset and factors considerations. This contributes to the ongoing evolution of automated valuation methods and helps advance data-driven decision-making in real estate
What is Stopping Building Information Modeling (BIM)-based Whole Life Carbon Assessment of Buildings in Hong Kong?
Get PDFBuilding information modeling (BIM)-based whole life carbon assessment (WLCA) of buildings is critical to reaching Hong Kong’s 2050 Net Zero target. However, the adoption of BIM-based WLCA is not as apparent as it should have been. This study aims to examine the criticality of various challenges that prevent the wide adoption of BIM-based WLCA in Hong Kong. To this end, 20 challenges were identified from a comprehensive literature review, and a questionnaire survey was performed with 80 construction professionals. The mean score ranking analysis results indicated that 13 challenges were critical. The top three most critical challenges were “data collection difficulty due to the fragmented nature of the construction industry”; “lack of standardized and regional carbon emissions datasets”; and “lack of training and technical knowledge of 6D BIM applications and WLCA”. The factor analysis further revealved that the challenges were segregated into six key groups: information technology (IT), market readiness, workflow, project management, organizational, and knowledge challenges. The IT challenges were the most dominant. The findings would be useful to policymakers and practitioners in developing suitable policies and strategies to overcome the challenges and promote the wider adoption of BIM-based WLCA towards reaching the 2050 Net Zero target. They also contribute to the body of knowledge by analyzing the challenges of BIM-based WLCA within the context of a high-rise high-density city. Although the study was conducted in Hong Kong, the findings and implications may be applicable to other jurisdictions where Net Zero by 2050 remains a crucial target
Mapping Construction 4.0 and Sustainability for Innovation in the Construction Industry of Developing Countries
Get PDFA country\u27s inclusive and sustainable growth depends largely on efficient infrastructure, making it a crucial aspect of governmental, urban, and social decisions, particularly in developing countries. However, these regions face significant barriers to progress, such as low digitalization rates, limited adoption of technology, and socio-economic obstacles that hinder sustainable development. Addressing these challenges is vital to fulfilling the United Nations’ Sustainable Development Goals (SDGs) and requires strategic partnerships, innovative practices, and integration within the construction sector. Furthermore, Industry 4.0 represents a promising pathway toward sustainable, technologically advanced construction; however, its adoption in developing countries remains in the early stages and faces considerable barriers. While each concept has been independently researched, their combined effect in this context remains understudied. Using bibliometric analysis, this study aims to explore the intersection of construction 4.0, sustainability, and innovation within the construction industry of developing countries to map their scientific development, providing an overview of the existing literature and identifying key areas of focus. The findings reveal crucial thematic areas, such as the prominent role of Building Information Modeling (BIM) in sustainability, material innovation focused on concrete properties, and the growing importance of prefabricated construction and social network analysis. Additionally, the study identifies critical research gaps including a lack of empirical validation of socio-economic impacts and the need for qualitative studies that delve into the policy, ethical, and social dimensions of Construction 4.0. The study provides a foundation for future research by highlighting the need for holistic approaches that integrate technological advancements with environmental and social considerations