Building information modelling and building sustainability assessment: a review

PurposeThe construction sector is increasingly engaged to explore the potential application of building information modelling (BIM) for the sustainability of the buildings. BIM can be applied conjugated to certification methods to evaluate the sustainability of the buildings, and it is known as building sustainability assessment (BSA). This article aims to explore applications of BIM in the sustainability analysis of buildings, including five types of BSA.Design/methodology/approachA literature review from 2009 to 2020 considering a combination of search terms related to BIM and BSA complemented the analysis. The bibliometric analysis indicates an increase in the number of publications on this topic of study in the last five years. A peak occurred in 2015 and 2020, with 51 and 66 publications, respectively.FindingsThe results showed that BIM contributes to achieving part of the sustainability requirements from BSA, especially quantitative requirements that are related to material and resources. However, a complete analysis between BIM and BSA is still a challenge since part of BSA's have a lack information in their requirements and BIM softwares present interoperability problems that difficult an integrated analysis to extract information directly from the software to attend BSA's requirements.Originality/valueThe results contribute to analysing the evolution of studies about BIM and to understand the limitation in the applicability with sustainability rating systems. Future directions of research indicate the necessity to improve the use of BIM in the sustainability analysis of the buildings, but with a good perspective regarding the application of BIM in material and resources requirements, and waste management in construction sites.

Effects of built environment on healing the mental health of the people–literature review

PurposeThe coronavirus disease 2019 (COVID-19) pandemic has been reported to have a major impact on the mental health of an individual. Healing the mental stress, anxiety, depression and insomnia of an individual's immediate surroundings play a major role. Therefore, this study reviews how the built environment impacts the healing of an individual's state of mind.Design/methodology/approachVarious works of literature on healing environments were analysed to create frameworks that can facilitate psychological healing through architectural elements. Articles were selected from various journals like SAGE, PubMed, Journal of Applied and Computational Mechanics (JACM), Routledge Taylor and Francis, Journal of Contemporary Urban Affairs (JCUA), ScienceDirect, and Emerald databases, news articles, official web pages, and magazines that have been referred.FindingsIndicators (spatial, sensory comfort, safety, security, privacy and social comfort) are linked to sub-indicators (access, distractions and views) and design characteristics (indoor climate, interior view, outside view, privacy, communication, noise, daylighting, temperature) which help in better connection of the built environment with individual's mental health. From the above indicators, sub-indicators and design characteristics, the authors have come to a conclusion that a view to the outside with better social interaction has an in-depth effect on an individual's mental health.Research limitations/implicationsThis study predominantly talks about healing in hospitals but quarantining of COVID-19 patients happens in residences too. So, it is important to find the healing characteristics in residences and in which typology the recovery process is high.Originality/valueThis paper has been written completely by the author and the co-authors and has not been copied from any other sources.

Performance evaluation of direction-finding techniques of an acoustic source with uniform linear array

PurposeThe purpose of this paper is to show a comparative study of different direction-of-arrival (DOA) estimation techniques, namely, multiple signal classification (MUSIC) algorithm, delay-and-sum (DAS) beamforming, support vector regression (SVR), multivariate linear regression (MLR) and multivariate curvilinear regression (MCR).Design/methodology/approachThe relative delay between the microphone signals is the key attribute for the implementation of any of these techniques. The machine-learning models SVR, MLR and MCR have been trained using correlation coefficient as the feature set. However, MUSIC uses noise subspace of the covariance-matrix of the signals recorded with the microphone, whereas DAS uses the constructive and destructive interference of the microphone signals.FindingsVariations in root mean square angular error (RMSAE) values are plotted using different DOA estimation techniques at different signal-to-noise-ratio (SNR) values as 10, 14, 18, 22 and 26dB. The RMSAE curve for DAS seems to be smooth as compared to PR1, PR2 and RR but it shows a relatively higher RMSAE at higher SNR. As compared to (DAS, PR1, PR2 and RR), SVR has the lowest RMSAE such that the graph is more suppressed towards the bottom.Originality/valueDAS has a smooth curve but has higher RMSAE at higher SNR values. All the techniques show a higher RMSAE at the end-fire, i.e. angles near 90°, but comparatively, MUSIC has the lowest RMSAE near the end-fire, supporting the claim that MUSIC outperforms all other algorithms considered.

An investigation into occupational health and safety of scaffolding practices on construction sites in Malaysia

PurposeStatistics show that the construction sector has the second-highest number of accident cases in Malaysia. A total of 100, 000 construction workers suffer from work-related bad health each year. Scaffolding accidents are the second cause of accidents on construction sites. Therefore, this present research provided answers to the following questions: (1) what are the causes of scaffolding accidents and (2) what are the possible measures to reduce scaffolding accidents?Design/methodology/approachThe research developed a questionnaire instrument that included 24 causes of scaffolding accidents and 21 remedial actions. The research was based on a cross-sectional survey questionnaire administered to 129 members of construction organizations.FindingsData revealed that scaffolding-related cases caused a total of 70% of the deaths/injuries on sites. Furthermore, scaffolding accidents were mainly caused by a lack of guard rails on scaffoldings, poor inspections, improper assembly, a poor safety culture, poor attitudes towards safety, poor footing of scaffoldings and unsecured planking. To reduce scaffolding accidents, there must be a lifeline on scaffolding, proper guardrails and proper assembling of scaffoldings, and preventing access to incomplete or defective scaffoldings. The 24 causes are structured into six factors through factor analysis and the 21 remedial actions into six factors.Originality/valueThis research serves as the first attempt to conduct broad research on the causes and remedial actions concerning scaffolding accidents on construction sites in Malaysia. Theoretically, the research has provided fresh insights into the impact of scaffolding accidents.

Stakeholder identification methods used in private organisations’ projects in Nigeria

PurposeThe purpose of the study is to examine the stakeholder identification (SI) methods used in building projects procured by private corporate organisations in Southwestern Nigeria to draw a correlation between methods used for SI and project performance in the study area, thereby enhancing project performance.Design/methodology/approachThe study used a census survey to purposively select 30 projects managers (who indicated from a first-stage questionnaire) that they have participated in structured stakeholder management (SM) from a list of 106 project managers and client representatives who have been involved in SM of building projects procured by private corporate organisations between 2008 and 2017 in the study area. A second-stage questionnaire was designed to elicit information from the respondents. The quantitative data that were collected were analysed using mean score (MS) analysis and Analysis of variance (ANOVA).FindingsThe study found that brainstorming in group meetings (MS = 4.33), interviews with the expert (MS = 3.20) and identification by other stakeholders (MS = 3.00) are the most frequently used SI methods in the study area. It was also found that the use of a questionnaire (MS = 0.87), Delphi method (MS = 0.80) and public hearing (MS = 0.57) was rare for SI in the study area. A further result showed that there was no significant difference in the opinion of project managers on 85% of methods used for SI in the study area irrespective of the procurement method employed.Practical implicationsThe study examined the methods project managers used for SI on building projects procured by private corporate organisations to advocate for more robust and all-inclusive SI methods.Originality/valueThe study empirically examined methods used for SI and correlated them to project performance.

Systematic review of application of artificial intelligence tools in architectural, engineering and construction

PurposeThis study reviews the extent of application of artificial intelligence (AI) tools in the construction industry.Design/methodology/approachA thorough literature review (based on 165 articles) was conducted using Elsevier's Scopus due to its simplicity and as it encapsulates an extensive variety of databases to identify the literature related to the scope of the present study.FindingsThe following items were extracted: type of AI tools used, the major purpose of application, the geographical location where the study was conducted and the distribution of studies in terms of the journals they are published by. Based on the review results, the disciplines the AI tools have been used for were classified into eight major areas, such as geotechnical engineering, project management, energy, hydrology, environment and transportation, while construction materials and structural engineering. ANN has been a widely used tool, while the researchers have also used other AI tools, which shows efforts of exploring other tools for better modelling abilities. There is also clear evidence of that studies are now growing from applying a single AI tool to applying hybrid ones to create a comparison and showcase which tool provides a better result in an apple-to-apple scenario.Practical implicationsThe findings can be used, not only by the researchers interested in the application of AI tools in construction, but also by the industry practitioners, who are keen to further understand and explore the applications of AI tools in the field.Originality/valueThere are no studies to date which serves as the center point to learn about the different AI tools available and their level of application in different fields of AEC. The study sheds light on various studies, which have used AI in hybrid/evolutionary systems to develop effective and accurate predictive models, to offer researchers and model developers more tools to choose from.

Tradeoffs between safe/comfortable headways versus mobility-enhancing headways in an automated driving environment: preliminary insights using a driving simulator experiment

PurposeThe anticipated benefits of connected and autonomous vehicles (CAVs) include safety and mobility enhancement. Small headways between successive vehicles, on one hand, can cause increased capacity and throughput and thereby improve overall mobility. On the other hand, small headways can cause vehicle occupant discomfort and unsafety. Therefore, in a CAV environment, it is important to determine appropriate headways that offer a good balance between mobility and user safety/comfort.Design/methodology/approachIn addressing this research question, this study carried out a pilot experiment using a driving simulator equipped with a Level-3 automated driving system, to measure the threshold headways. The Method of Constant Stimuli (MCS) procedure was modified to enable the estimation of two comfort thresholds. The participants (drivers) were placed in three categories (“Cautious,” “Neutral” and “Confident”) and 250 driving tests were carried out for each category. Probit analysis was then used to estimate the threshold headways that differentiate drivers' discomfort and their intention to re-engage the driving tasks.FindingsThe results indicate that “Cautious” drivers tend to be more sensitive to the decrease in headways, and therefore exhibit greater propensity to deactivate the automated driving mode under a longer headway relative to other driver groups. Also, there seems to exist no driver discomfort when the CAV maintains headway up to 5%–9% shorter than the headways they typically adopt. Further reduction in headways tends to cause discomfort to drivers and trigger take over control maneuver.Research limitations/implicationsIn future studies, the number of observations could be increased further.Practical implicationsThe study findings can help guide specification of user-friendly headways specified in the algorithms used for CAV control, by vehicle manufacturers and technology companies. By measuring and learning from a human driver's perception, AV manufacturers can produce personalized AVs to suit the user's preferences regarding headway. Also, the identified headway thresholds could be applied by practitioners and researchers to update highway lane capacities and passenger-car-equivalents in the autonomous mobility era.Originality/valueThe study represents a pioneering effort and preliminary pilot driving simulator experiment to assess the tradeoffs between comfortable headways versus mobility-enhancing headways in an automated driving environment.

Quality issues related to the design and construction stage of a project in the Indian construction industry

PurposeQuality in the construction industry is an important issue yet ignored during the initial stages of the life cycle of a project, that is, the design and construction stage. The contribution of stakeholders, especially the architects is generally suspended though it has huge significance in terms of cost and time related to quality. This research endeavors to examine the issues related to the design and construction stages of the project from architects' purview, to understand the relative importance of these issues in the Indian construction industry.Design/methodology/approachThe study of qualitative data conducted formed a basis for online quantitative data collection that was further analyzed with the help of cross-tabulation and multiple correspondence analysis methods.FindingsThe study concludes that the budget of a project is a corresponding factor related to quality concern for architects. The study also established that the quality issues corresponding to high budgets are closely related to the construction stage and are identified as preparation of checklist, and bidding process of hiring the contractor on the lowest bid.Research limitations/implicationsThe study is limited to analyzing the perspective of architects; however, other stakeholders of the construction industry may represent a different opinion.Practical implicationsThis research emphasizes the importance of the client's role, and need for integration and coordination among stakeholders in the construction industry for effective quality control and management.Originality/valueThe research presents an exhaustive literature review on quality issues and its importance with respect to cost implications, standard practices, sustainability and the life cycle of the project.

Potential measures towards the reduction of cooling loads of office buildings in Ghana

PurposeGiven the climatic context and economic challenge of Ghana in its developmental strides, energy use of office buildings continues to be a task on the economy. Therefore, the study was about finding measures that could reduce cooling loads in 10 office buildings. The paper presents the outcome of a long-term study of the thermal conditions in a selected number of office buildings in Accra and Kumasi, Ghana.Design/methodology/approachThrough long-term monitoring of environmental data, the buildings were consequently modelled in a simulation application. Thereafter, a validation of the simulation models (using regression coefficients, r2 of 0.53–0.90) was undertaken towards finding measures to reduce cooling loads.FindingsThe results showed various potentials of efficient lighting, thermal mass, night ventilation, insulation to attic floors, efficient glazing, blind deployments, etc. in reducing cooling loads in the range of 2–17.5%. By combining the potential measures to study their synergistic effects on the loads, 35, 39 and 38% improvements were achieved for the low-rise, multi-storey and fully glazed office buildings.Originality/valueThese potential measures ought to be incorporated in the design, specification, construction and operation of Ghanaian office buildings to reduce the burden on the economy and the environment. Now more than ever, there is the need for climatic regions to come up with empirical data that could help relieve the world's economies from the post-pandemic stress.

Using new artificial bee colony as probabilistic neural network for breast cancer data classification

PurposeBreast cancer is an important medical disorder, which is not a single disease but a cluster more than 200 different serious medical complications.Design/methodology/approachThe new artificial bee colony (ABC) implementation has been applied to probabilistic neural network (PNN) for training and testing purpose to classify the breast cancer data set.FindingsThe new ABC algorithm along with PNN has been successfully applied to breast cancers data set for prediction purpose with minimum iteration consuming.Originality/valueThe new implementation of ABC along PNN can be easily applied to times series problems for accurate prediction or classification.