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This work aims to develop a web platform for inspecting roof structures for technical assistance supported by drones and artificial intelligence. The tools used were HTML, CSS and JavaScript languages; Firebase software for infrastructure; and Custom Vision for image processing.

This study adopted the design science research approach, and the main stages for the development of the web platform include (1) creation and validation of the roof inspection checklist, (2) validation of the use of Custom Vision as an image recognition tool, and (3) development of the web platform.

The results of automatic recognition showed a percentage of 77.08% accuracy in identifying pathologies in roof images obtained by drones for technical assistance.

This study contributed to developing a drone-integrated roof platform for visual data collection and artificial intelligence for automatic recognition of pathologies, enabling greater efficiency and agility in the collection, processing and analysis of results to guarantee the durability of the building.

Building defects are becoming recurrent phenomena in most high-rise buildings. However, little research exists on the analysis of defects in high-rise buildings based on data from real-life projects. This study aims to develop dashboards and models for revealing the most common locations of defects, understanding associations among defects and predicting the rectification periods.

In total, 15,484 defect reports comprising qualitative and quantitative data were obtained from a company that provides consulting services for the construction industry in Victoria, Australia. Data mining methods were applied using a wide range of Python libraries including NumPy, Pandas, Natural Language Toolkit, SpaCy and Regular Expression, alongside association rule mining (ARM) and simulations.

Findings reveal that defects in multi-storey buildings often occur on lower levels, rather than on higher levels. Joinery defects were found to be the most recurrent problem on ground floors. The ARM outcomes show that the occurrence of one type of defect can be taken as an indication for the existence of other types of defects. For instance, in laundry, the chance of occurrence of plumbing and joinery defects, where paint defects are observed, is 88%. The stochastic model built for door defects showed that there is a 60% chance that defects on doors can be rectified within 60 days.

The dashboards provide original insight and novel ideas regarding the frequency of defects in various positions in multi-storey buildings. The stochastic models can provide a reliable point of reference for property managers, occupants and sub-contractors for taking measures to avoid reoccurring defects; so too, findings provide estimations of possible rectification periods for various types of defects.

Retrofitting and rehabilitation are part of the conservation approach in Heritage Building Conservation Guideline 2016 in Malaysia. Heritage buildings can be retrofitted to preserve their culture and history while being given a new lease. Rehabilitation is a preservation requirement that is more flexible since it assumes that the structure has already deteriorated to the point where repairs are required to prevent further deterioration. Although the strategies of these two approaches are different, their combination resulted in sustainable heritage building maintenance. This long-term maintenance strategy is necessary, especially for Malaysia's numerous heritage schools, which have serious maintenance problems as a result of infrequent maintenance, repairs, and funding shortages.

This study involved secondary data from an intensive literature review along with a comparative study from articles review and context analysis. A comparative study was conducted to determine the typical issue with heritage school buildings and the best maintenance practice for these structures. Finally, it involved a SWOT analysis study of retrofitting and rehabilitating heritage school buildings will be discussed in this study as well.

The findings of this study will focus on developing a strategic planning framework and maintenance for heritage school buildings in Malaysia to achieve sustainable maintenance. It will also highlight sustainable maintenance best practices for heritage school buildings in Malaysia. Finally, SWOT analysis will go over the pros and cons of retrofitting and rehabilitation for these buildings.

This paper put forward the requirements of strategic planning in heritage school buildings and outlines the significance of sustainable maintenance for educational buildings. It is an alternative for cost savings that has not been extensively investigated in previous studies.

In recent years, augmented reality (AR) has shown its potential to assist various construction activities. Its use commonly requires additional refinement to be integrated into the building information modeling (BIM) process. Nevertheless, few studies have investigated AR implementation in BIM-enabled projects because of numerous challenges related to its implementation. This study aims to investigate the implementation of AR in construction and identify the critical mechanisms for implementing BIM-AR successfully.

A mixed methodology was adopted for this study. First, this work presents a bibliometric analysis covering articles obtained from Scopus database published between 2000 and 2022. A sample size of 65 research papers pertinent to AR in construction was analyzed using VOSviewer software. Second, a participatory case study was conducted for a BIM-enabled project in China to gain insight into how BIM-AR implementation in construction is achieved.

The findings from the bibliometric analysis show an increasing interest in AR research within construction. The results indicate that AR research focuses on four clusters: real-time communication, project management, construction activities and education. Findings from the case study provide an empirical experience of AR application scenarios in a BIM-enabled project. Concomitantly, 15 critical success factors that influence BIM-AR implementation were finally identified and demonstrated.

This study provides a rich insight into the understanding and awareness of implementing AR. First, the findings are beneficial to construction practitioners and researchers because they provide a concentrated perspective of AR for emerging activities in the construction industry. Second, the results obtained from the case study could provide a useful guide for effectively implementing AR in a BIM-enabled construction project. Overall, this study may stimulate further research on AR-related studies in construction, such as BIM integration, factor analysis and construction education.

The purpose of this study is to explore the suggestions that construction processes could be considerably improved by integrating building information modelling (BIM) with 3D laser scanning technologies. This case study integrated 3D laser point cloud scans with BIM to explore the effects of BIM adoption on ongoing construction project, whilst evaluating the utility of 3D laser scanning technology for producing structural 3D models by converting point cloud data (PCD) into BIM.

The primary data acquisition adopted the use of Trimble X7 laser scanning process, which is a set of data points in the scanned space that represent the scanned structure. The implementation of BIM with the 3D PCD to explore the precision and effectiveness of the construction processes as well as the as-built condition of a structure was precisely captured using the 3D laser scanning technology to recreate accurate and exact 3D models capable of being used to find and fix problems during construction.

The findings indicate that the integration of BIM and 3D laser scanning technology has the tendency to mitigate issues such as building rework, improved project completion times, reduced project cost, enhanced interdisciplinary communication, cooperation and collaboration amongst the project duty holders, which ultimately enhances the overall efficiency of the construction project.

The acquisition of data using 3D laser scanner is usually conducted from the ground. Therefore, certain aspects of the building could potentially disturb data acquisition; for example, the gable and sections of eaves (fascia and soffit) could be left in a blind spot. Data acquisition using 3D laser scanner technology takes time, and the processing of the vast amount of data acquired is laborious, and if not carefully analysed, could result in errors in generated models. Furthermore, because this was an ongoing construction project, material stockpiling and planned construction works obstructed and delayed the seamless capture of scanned data points.

These findings highlight the significance of integrating BIM and 3D laser scanning technology in the construction process and emphasise the value of advanced data collection methods for effectively managing construction projects and streamlined workflows.

Sustainability has become an integral part of the real estate industry, alongside advancing globalization and demographic development. Due to real estate's influence on greenhouse gas emissions throughout its life cycle, both the regulatory and legal requirements concerning the sustainability of real estate are growing and, as a result of social responsibility, the interest of tenants and investors in sustainable real estate. However, criteria for measuring the ecological sustainability of a real estate investment in the purchase process in order to reduce the risk of including “stranded assets” in the portfolio are missing. This paper aims to address the need to integrate the issue of carbon stranding into existing sustainability rating tools.

Existing tools are examined based on defined criteria to determine whether they are suitable for purchasing a property before suitable tools for purchase are compared. Strengths and weaknesses are identified, which are to be remedied with the scoring tool. Taxonomy regulation is integrated into the existing valuation basis as a legal regulation.

The result is a scoring tool that enables real estate companies to measure and evaluate the ecological sustainability performance of a property during the acquisition process, taking into account the three aspects of sustainability and considering them when determining an appropriate purchase price in line with market conditions. Moreover, the developed tool helps to minimize the risk of acquiring a stranding asset.

The environmental, social and governance (ESG) framework employed in this study does not incorporate governance considerations. While the analysis extensively evaluates the building's environmental and social aspects, it does not extend to examining the governance practices of the companies involved. Thus, the assessment is confined solely to the physical attributes of the property without accounting for broader corporate governance factors.

The developed scoring tool represents a valuable tool for the real estate industry, offering insights into sustainability performance during property acquisitions and providing a structured framework for decision-making. By addressing both certification and taxonomy regulation requirements, the tool contributes to the industry's evolution toward more sustainable and environmentally responsible real estate practices.

In response to the growing importance of sustainability in the real estate industry, this paper introduces a novel scoring tool for evaluating the sustainability of real estate investments during the acquisition process.

This paper presents a developed BIMxAR application, an integration of building information modeling (BIM) with augmented reality (AR) linked with real-time online database to support the building facility management work. The primary aim of this research was to develop and empirically examine the applicability of a BIM-based AR (BIMxAR) application in building facility management.

The BIMxAR application was developed and experimented with maintenance work of a university laboratory building. The experiment consisted of a comparison of supportive maintenance tasks performed using the traditional approach and the BIMxAR approach by 38 university students. The time taken to complete each task was recorded and analyzed using statistical analyses to compare the performance between the tasks completed using each approach.

The results indicated that the group using the BIMxAR application approach completed the tasks correctly in a significantly shorter time compared to that using the traditional approach. The findings supported the applicability of the developed BIMxAR application and the improvement of the building facility management tasks when using the proposed approach.

This paper presents a methodological approach in developing a mobile application that integrates BIM with AR for facility management work, leveraging real-time information exchange through a cloud-based platform. The paper also provides empirical evidence that demonstrates how the integration between BIM and AR could be achieved and implemented to help facilitate building maintenance tasks.

Despite the number of quality management procedures being currently applied, construction defects in the domestic sector are acknowledged to contribute to the energy performance gap of buildings. This paper investigates the limitations and challenges to the implementation of project quality plans (PQPs) and their impact on the achievement of expected thermal performance in the UK social housing projects.

A qualitative approach, guided by grounded theory, was used in this research. This methodology provided the structure for systematic data analysis iterations, enabling cross-case analysis. An analytic induction process was designed to seek the explanation of the targeted phenomenon and required data collection until no new ideas and concepts emerged from the research iterations. This study collected data from five social housing projects through interviews, site observations and project documentation.

Multiple limitations and challenges were identified in the implementation of PQP to deliver thermal efficient social housing. Generally, there is the need for more objective quality compliance procedures based on required evidence. When investigating the root of the challenges, it was concluded that the adoption of statutory approval as the main quality compliance procedure led to the dilution of the responsibility for prevention and appraisal of defects that compromised the effectiveness of PQP devised by housing associations (HA) and contractors.

This study identifies the shortcomings of PQP in addressing quality issues with potential to undermine the thermal performance of social housing projects. The findings could be used by HA, contractors and policymakers as steppingstones to improve the energy efficiency in the domestic sector.

The use of renewable energy has become necessary because of the harmful effects of current energy sources on the environment, limited availability and financial crisis. Transparent solar panels have emerged as a promising technology for integrating renewable energy generation into building structures. Therefore, this paper aims to explore the feasibility of transparent solar panels for high-rise building façades in Sri Lanka.

The research apprehended a qualitative approach, including two expert interview rounds adhering to the Delphi technique with 17 and 15 experts each per round. Manual content analysis was incorporated to analyse the collected data.

Regarding operation and maintenance, the study emphasizes the importance of regular inspection, cleaning and repair of transparent solar panels to ensure optimal performance and longevity. These activities contribute to maximizing energy generation and maintaining the aesthetic appeal of the building. The benefits of implementing transparent solar panels on building façades are manifold. They include renewable energy generation, reduced greenhouse gas emissions, improved energy efficiency and enhanced architectural aesthetics. Furthermore, the research findings underscore the potential of transparent solar panels to contribute to Sri Lanka’s sustainable development goals and address the country’s increasing energy demand. However, the study also identifies challenges that need to be addressed for successful implementation.

This study contributes to understanding the feasibility of transparent solar panels for high-rise building façades in Sri Lanka. The research findings offer valuable insights into the operation and maintenance aspects, benefits, challenges and strategies for implementing transparent solar panels effectively. This knowledge can guide policymakers, architects and developers in making informed decisions regarding the integration of transparent solar panels, thereby promoting sustainable and energy-efficient building practices in Sri Lanka.

Monitoring of the quality of precast concrete (PC) components is crucial for the success of prefabricated construction projects. Currently, quality monitoring of PC components during the construction phase is predominantly done manually, resulting in low efficiency and hindering the progress of intelligent construction. This paper presents an intelligent inspection method for assessing the appearance quality of PC components, utilizing an enhanced you look only once (YOLO) model and multi-source data. The aim of this research is to achieve automated management of the appearance quality of precast components in the prefabricated construction process through digital means.

The paper begins by establishing an improved YOLO model and an image dataset for evaluating appearance quality. Through object detection in the images, a preliminary and efficient assessment of the precast components' appearance quality is achieved. Moreover, the detection results are mapped onto the point cloud for high-precision quality inspection. In the case of precast components with quality defects, precise quality inspection is conducted by combining the three-dimensional model data obtained from forward design conversion with the captured point cloud data through registration. Additionally, the paper proposes a framework for an automated inspection platform dedicated to assessing appearance quality in prefabricated buildings, encompassing the platform's hardware network.

The improved YOLO model achieved a best mean average precision of 85.02% on the VOC2007 dataset, surpassing the performance of most similar models. After targeted training, the model exhibits excellent recognition capabilities for the four common appearance quality defects. When mapped onto the point cloud, the accuracy of quality inspection based on point cloud data and forward design is within 0.1 mm. The appearance quality inspection platform enables feedback and optimization of quality issues.

The proposed method in this study enables high-precision, visualized and automated detection of the appearance quality of PC components. It effectively meets the demand for quality inspection of precast components on construction sites of prefabricated buildings, providing technological support for the development of intelligent construction. The design of the appearance quality inspection platform's logic and framework facilitates the integration of the method, laying the foundation for efficient quality management in the future.