bluuebunny/crossref_metadata_2025_split huggingface dataset:
The social and environmental impact of building integrated photovoltaics technology
Authors: Pavlakis Sotiris , Teo Pauline , Jayasuriya Sajani 
Published: December 2022

Abstract
Various sustainable energy technologies are evolving around the world to reduce the carbon footprints in buildings. Building integrated photovoltaics (BIPV) is one of the emerging sustainable technologies and it refers to a technology where the elements of the building envelope such as façade and roof are replaced with solar cells. However, the adoptability of BIPV technology in buildings is limited as its costs and benefits are unknown to the public. This study aims to review the BIPV literature qualitatively, to explore the beneficial-related and cost-related factors of adopting BIPV technology. A thematic analysis was undertaken among journal papers published between 2011 to 2019 that focused their investigation on integrated solar renewable systems. The identified cost and benefit-related factors were classified into environmental, health, design, and social themes. It is recommended that further research can be undertaken to explore the importance of cost and beneficial factors identified in this study quantitatively. Finally, these factors will assist in quantitatively measuring the societal impacts of BIPV technology.
Shoreline Recognition Using Machine Learning Techniques
Authors: Zhong Yunshun , El-Diraby Tamer 
Published: December 2022

Abstract
Coastal areas have emerged to be the most significant and dynamic regions worldwide. Therefore, automating shoreline recognition will aid non-profit conservation authorities to reduce public budget expenditures, relieve erosion damage, and increase the climate resilience of the natural environment. In this paper, advanced ML boosting algorithms including XGBoost, and LGBM are firstly applied into shoreline recognition with aerial images (of Lake Ontario in this study). This paper first discussed the significance and a literature review of recent progress in shoreline detection. Then, this paper adopted semantic segmentation instead of detecting shoreline directly, which enables the (Machine Learning) ML model to achieve relatively high accuracy with a small amount of data. 5 high-resolution images are used for training the model in which shorelines are detected. The work was carried out in four steps: 1) labeling the contents of shoreline images as areas of water and banks; 2) training ML algorithms; 3) using the trained algorithms to classify the image content as either water or land objects; 4) post-processing by de-noising image pixels (applying a Fourier transform algorithm) to obtain a defined shoreline. The averaged training time per image for Random Forest, XGBoost, and LGBM algorithms are 195.2 sec, 71.0 sec, and 8.6 sec, respectively. The averaged accuracy is 95.6%, 96.0%, and 94.8%, respectively; the XGBoost algorithm has slightly higher accuracy, while LGBM has a significantly shorter runtime. Cross-validation of the LGBM algorithm reduced the training time by around 23% (7.0 sec) and increased the accuracy by only 1.1% (to 95.9%).
A review of sustainable technologies for energy efficient upgrade of existing buildings and systems
Authors: Dadzie John , Pratt Isaac , Frimpong-Asante James 
Published: December 2022

Abstract
Sustainable upgrades include actual case studies with before and after retrofit results, case studies with simulated results and use of computer systems to predict energy savings based on exiting building parameters. In the latter no actual renovations are done thus technologies and systems are assumed. The review used real cases including simulations and adopts a mix of systematic and content analysis approaches. Thus, over 288 articles were gathered from all the major scientific journals using Scopus, ProQuest, Web of Science etc. The sample was reduced to 230 articles based on the search themes; thereafter, a detailed focus on the methods used provided basis to trim the articles to 47. Sustainable technologies identified cover those installed to the external façade, indoor areas, air filtration, insulation systems, building elements, heating, ventilation and cooling (HVAC) systems, sensors, lighting, hot and cold water systems such as boilers, chillers, pumps, motors and renewable energy technologies. The results show sustainable technologies have been used to improve various existing buildings. Also, the results indicate high rate of adoption of insulation systems for external and internal walls, roofing and ceiling elements. This paper provides evidence to support the drive towards environmental sustainability through the adoption and installation of sustainable technologies. Policies to trigger demand and installation could further improve actions towards greenhouse gas reduction.
Assessment of Occupant Adaptive Heating Behaviour in Office Buildings - A Pilot Field Study
Authors: Andrade I , Krumdieck S , Becker S 
Published: December 2022

AbstractBuildings are responsible for 39% of total global CO2 emissions worldwide, with 33% of energy consumption attributed to space heating in commercial buildings. Adaptive Heating Behaviour (AHB) of office users has a direct impact on energy use and depends on building characteristics which determine the heating load. This pilot field study focuses on the assessment of the AHB of office users of a recently retrofitted university building in Christchurch, New Zealand. AHB was reported by users during three consecutive days with a total heating degree days (HDD at 18°C) of 26.8. Indoor temperature and relative humidity were monitored during the study, and a qualitative analysis was performed to understand occupants’ behavioural patterns to maintain or recover thermal comfort in office settings. Participants were categorized according to (i) their reported thermal comfort issues at work, (ii) the adaptive responses they took to recover thermal comfort, and (iii) the effectiveness of such actions. The methods used in this pilot study to assess occupant AHB, were informative to future research on how to link environmental conditions to user behaviour in office settings, through the analysis of qualitative and quantitative data. Identifying patterns and triggers for AHB on a per-case basis is necessary, especially as AHB can significantly influence the building energy consumption.
Social sustainability indicators for road infrastructure projects: A systematic literature review
Authors: Vijayakumar Ankitha , Mahmood Muhammad Nateque , Gurmu Argaw , Kamardeen Imriyas , Alam Shafiq 
Published: December 2022

Abstract
Australia’s population is predicted to grow to 31.4 million by 2034, according to Infrastructure Australia Audit 2019, resulting in additional demand for road infrastructure. Although road infrastructure projects have a significant positive impact at the regional level regarding reduced travel time, improved accessibility, and amenities, they may also have negative social impacts at the local level. However, road infrastructure projects are often seen as key drivers of economic development. Social aspects are generally less considered in the decision-making process of the project lifecycle. The existing sustainability assessment models focus on economic and environmental aspects and lack social considerations. To bridge the gap, this paper aims to examine the existing literature on social sustainability in the construction industry and identify the social aspects and relevant indicators to be considered in assessing the social sustainability performance of road infrastructure projects. Through systematic literature review, using Scopus, Web of Science, EBSCO and google search databases from an initial set of 1178 journals, conference papers, books, book chapters and other relevant industry reports, 80 articles related to social sustainability in the construction industry were selected for the study. Based on the analysis, nine social sustainability criteria such as quality of life, equity, employment, health and safety, stakeholder participation, culture and heritage, compensation strategies, governance, macro-social activities and 78 respective indicators were identified. The findings of this study may assist policymakers and industry practitioners in developing comprehensive assessment models for benchmarking social sustainability in Australian road infrastructure projects.
Forecasting Green Building Growth in Different Regions of China
Authors: Chen Linyan , Chan Albert P.C. , Yang Qiang , Darko Amos , Gao Xin 
Published: December 2022

Abstract
Green building has significant merits in energy conservation and resource efficiency, making it prevalent in many countries. Forecasting green building growth helps governments develop relevant policies and benefits researchers to solve the problem of lack of data. Although there were various studies on green building development, few forecasted growth to inform green building policy. To fill the gap, this study aims to develop an innovative approach to predict green building growth in different regions of China. A long short-term memory (LSTM) model with an attention mechanism was put forward in this study. Results show that the innovative model performed well in forecasting green building growth. The green building development in China keeps an increasing trend and will continue the growth at a higher speed in the following years. Moreover, geographical clustering patterns of green buildings were investigated, and a three-step distribution pattern was observed. Although this research was conducted in the Chinese context, it provides references to other countries by proposing an innovative model, which helps them better understand the patterns of green building growth. This study developed an innovative approach to forecasting green buildings, contributing to the existing green building knowledge body. Furthermore, it benefits governments and practitioners in decision-making.
An investigation into green gentrification in the Silo District, Cape Town, South Africa
Authors: Ordor U , Spriestersbach R J , Aitken T 
Published: December 2022

Abstract
Despite the plethora of studies on gentrification, knowledge about green gentrification is limited, especially in a South African context. Green gentrification is the process in which providing green amenities and cleaning up pollution attracts wealthier residents or tenants to a previously rundown neighbourhood, thereby increasing property values. This paper explores whether the characteristics of green gentrification can be identified in the transformation of the Silo District of the V&A Waterfront, Cape Town, and therefore its effect on the perception of ‘green gentrification’, if it is found to occur in the area. The research was based on a single case study with three sources of data collection – a critical literature review, photographic and documentary evidence and semi-structured interviews. The findings show that the transforming of the Silo District, by implementing green and environmental amenities, attracted wealthy individuals and organisations to the area. The findings show that green gentrification occurs in the Silo District, and its transformation had a limited influence on this perception. The study reveals an inadvertent insidious phenomenon in redevelopment initiatives, especially with growing consciousness of sustainability issues. However, the limitations of a single case study research makes further research imperative, and results tested using contextually relevant methods.
Comparison of Perceived Data Skills of Quantity Surveying Undergraduates and Graduates in Malaysia
Authors: Chia F C , Sim Y C , Wong P F 
Published: December 2022

Abstract
The technological innovation is driving the future workforce proficient with a new set of data skills. Quantity Surveyors being one of the key actors in the construction industry have no exception. This paper aims to explore how the quantity surveying undergraduates and graduates perceived their own level of data skills possessed and their stances on data skills to be taught in quantity surveying programmes. Five categories of data skills namely, data collection, data processing, data analysis, data ethics and data privacy have been synthesised from 30 data skills through the literature reviewed. The questionnaire survey participated by 574 of undergraduates and graduates shows the self-perceived level of data skills in descending order are data collection, data processing, data analysis, data privacy and data ethics, which are differing with the stances on the data skills to be taught by the higher education institution, i.e. data analysis, data collection, data ethics, data processing and data privacy. Data analysis skill is mostly expected to be enhanced in the QS programme. The findings can be served as an input to the providers of QS programmes to enhance the course curriculum, particularly on the digital skill.
The influences of facilities management on mental health of underground development users during the pandemic in Hong Kong
Authors: Chen Hao , Chan Isabelle Y.S 
Published: December 2022

Abstract
The outbreak of COVID-19 has triggered an unprecedented health crisis across the world. Previous research indicated that the fear of being infected in public place has transportation hindered the commuters’ choice on. In fact, underground transportation systems, especially those located in high- density cities, have been perceived as high risk environments under the pandemic. In addition, the prolonged COVID-19 outbreak, together with the negative public impression towards underground environment, have to certain extent triggered various mental health responses amongst citizens (e.g., 42.3% increase of anxiety in Hong Kong). This study thus aims to investigate the impacts of FM on underground development users’ mental health in Hong Kong. To achieve this aim, a questionnaire survey approach is adopted. The survey is designed to contain three parts: background information, satisfaction towards underground FM (space management, building services, and supporting facilities related to the pandemic), and mental health level (emotional exhaustion, depersonalization, and claustrophobia). Data is collected over four underground subway stations in Hong Kong. Person correlation and regression analysis are conducted to determine the statistically significant relationships between underground FM and users’ mental health. The results indicated that satisfaction towards visual access, immediate access, and hygiene practices have negative relationship with the occurrence of emotional exhuastion and depersonalization, except for claustrophobia symptoms. The study results provide empirical evidence for practitioners to make informed decisions in FM plans for enhancing mental health of underground development users under and after the pandemic.
Developing an AI-powered smart insole system to reduce the possibility of back pain among older workers: lessons from the Norwegian construction industry
Authors: Ishtiaque Tausif Ahmed , Cepuran Ana , Salaj Alenka Temeljotov , Torp Olav , Diaconu Mara Gabriela 
Published: December 2022

AbstractBlue-collar workers are generally more susceptible to specific health conditions such as musculoskeletal disorders, among which back pain is a significant problem for older workers. This study presents the design of a smart insole system developed as a part of the research and the practicality of its use in the construction industry, including an evaluation of its benefits and limitations. Pressure sensors in the soles generate heatmaps that allow us to identify incorrect posture using an adaptable Artificial Intelligence lifting engine. The data is used to evaluate the lifting actions in real-time and preemptively warn the individuals. Using the principles of participatory design as a starting point, the pilot phase, and testing of the solution, the pre-use survey was conducted among construction workers to understand their experience while interacting with the solution. The user testing period was followed by the feedback and evaluation period, which included getting informal feedback on the system. While it has shown the promise of a new solution, it still needs improved robustness and simpler instructions. Some minor technical challenges must be addressed before moving to the commercial stage. The results are used to evaluate further, improve the system, and make decisions in the product design.
Improving the built environment for manual wheelchair users: A review
Authors: Flemmer C L 
Published: December 2022

AbstractThe aim of Universal Design is to make the built environment accessible to all people regardless of disability. This is a laudable aim, but most people are unaware of the many barriers manual wheelchair users actually face when accessing the built environment. The main challenges for manual wheelchair users arise from three areas. Firstly, there are intrinsic limitations arising from the manual wheelchair user’s condition and capability. Secondly, there are features such as ramps and cross slopes in the built environment that fail to comply with building codes relating to wheelchair access. Thirdly, there are cosmetic features such as cracked paths, obstructions and poorly placed signage that place an additional burden on manual wheelchair navigation. Each of these three areas is discussed in this article.The intrinsic limitations of user condition and capability include a wide range of physical impairments and an inherently inefficient manual wheelchair propulsion mechanism. The typical code compliance requirements for wheelchair access in the built environment range from limitations on minimum path widths to maximum permissible ramp slopes. However, even when these features comply with code requirements they may be compromised by temporary obstructions or by poor maintenance so that they become insurmountable challenges to manual wheelchair users. An understanding of these challenges is necessary to improve the built environment so that it is more accessible to manual wheelchair users in the future.
Social distance monitoring of site workers for COVID-19 using context-guided data augmentation, deep learning, and homography transformation
Authors: Chen H , Hou L , Zhang G 
Published: December 2022

Abstract
Because of the COVID-19 pandemic, many industries have developed efforts to minimize COVID-19’s spread. For example, the construction industry in Melbourne practices social distancing and downsizes the number of workers on the job site. The surveillance system integrated with deep learning models has been extensively utilized to enhance construction safety. However, such 2D-based approaches suffer from occlusions, and the workers may not be accurately detected under this circumstance. To this end, this paper proposes a novel context-guided data augmentation method to enhance deep learning models’ performance under occlusions. The context-guided method can automatically augment images by adding occlusions to the objects. Using this way, deep learning models can learn the object’s features in various occlusion scenarios. Later, this method is validated by a real-time social distancing violation detection system. Specifically, this system utilizes a modified YOLOv4 model to detect workers by bounding boxes. Then, the DeepSORT algorithm is used to track the worker trajectories. Finally, homography transformation is used to calculate the distance between workers in each frame. The system has revealed robust results using the data augmentation method, and promising results indicate that the system can well support worker health during COVID-19.
New Zealand’s response to the COVID-19 pandemic and the effects of its governance on the construction industry
Authors: Mirhosseini S F , Wilkinson S , Babaeian Jelodar M 
Published: December 2022

AbstractThe global COVID-19 pandemic has impacted the construction industry. The pandemic caused wide international disruption to employment, supply chain, costs, skills, and other aspects, and it caused huge uncertainty. Around the world, governments dealt with the crisis in different manners. This study investigates the ways New Zealand responded to this pandemic and examined the effects of its governance on the construction industry. This is done through examining and analysing government records and guidelines in response to COVID-19 at different stages and alert levels. Relevant government information portals and websites such as “Ministry of Business, Innovation and Employment”, “Construction Sector Accord”, and “Covid.govt.nz” are investigated to find guidelines and information to help the construction industry respond to the impacts of COVID-19. These guidelines and information were compared to understand how similar these recommended responses were. The findings show the mitigating implications and solutions to the construction industry’s current disruption and demonstrate the similarity of the recommended solutions.
Industrialization of housing construction in Brazil: current situation and trends
Authors: Cardoso L R A , Freschi G D R 
Published: December 2022

Abstract
Brazilian housing needs are high. Even with important technological advancements taking place in recent decades, the degree of industrialization of housing construction remains relatively low in Brazil. The perception of the sector is that housing needs can only be equated by a significant increase in the industrialization of construction, and that the technologies available can support such increase. Currently, the existence of barriers and difficulties for industrialization are out of the production area, concentrated in the production chain, and in the macroeconomic, and political-institutional environments. The purpose of this paper is to provide an overview on the subject. For that, the following items were developed: technological base of housing construction, the main industrialization technologies available, and the barriers and difficulties to be faced in order to support the increase in industrialization. Finally, scenarios of the future trends of evolution in the sector are discussed. This research is exploratory, based on literature review, and the results may support actions in the sector aimed at overcoming the barriers and difficulties for industrialization. It may also contribute to increasing knowledge, and furthering studies on the subject.
Analysis of sustainable procurement in supplying recycled content: A case study in Western Australia
Authors: Shooshtarian S , Le T (TJ) , Feng Y , Bettini L 
Published: December 2022

Abstract
Extensive construction activities across Australia have resulted in an unpreceded rate of construction and demolition (C&D) waste generation. A fraction of this waste is currently being recycled and supplied to the market. However, the reports indicate that the Australian market is not prepared to uptake such a quantity of recycled content (RC). A successful policy approach in increasing RC uptake in the construction industry is sustainable government procurement. However, the benefits of this policy instrument have not been fully realised in Australia. Therefore, this study aims to understand the dynamics of sustainable procurement using the Roads to Reuse (RtR) Program managed by Western Australia Main Roads as a case study. This public organisation is responsible for managing road networks across Western Australia. The study employs an interview with a senior sustainability advisor of this organisation. The interview is guided by a framework for enabling sustainable procurement seeking transformation in behaviour, culture, context and processes in the government and industry sectors. The results of the study shed light on sustainable procurement opportunities and challenges in the Australian context. Furthermore, a series of recommendations proposed to improve the status quo towards a more sustainable future. The findings can be used by policymakers, government procurement experts, and industry practitioners to drive sustainable procurement planning and practices changes.