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Incipient detection of pavement deterioration (such as crack identification) is critical to optimizing road maintenance because it enables preventative steps to be implemented to mitigate damage and possible failure. Traditional visual inspection has been largely superseded by semi-automatic/automatic procedures given significant advancements in image processing. Therefore, there is a need to develop automated tools to detect and classify cracks.

The literature review is employed to evaluate existing attempts to use Hough transform algorithm and highlight issues that should be improved. Then, developing a simple low-cost crack detection method based on the Hough transform algorithm for pavement crack detection and classification.

Analysis results reveal that model accuracy reaches 92.14% for vertical cracks, 93.03% for diagonal cracks and 95.61% for horizontal cracks. The time lapse for detecting the crack type for one image is circa 0.98 s for vertical cracks, 0.79 s for horizontal cracks and 0.83 s for diagonal cracks. Ensuing discourse serves to illustrate the inherent potential of a simple low-cost image processing method in automated pavement crack detection. Moreover, this method provides direct guidance for long-term pavement optimal maintenance decisions.

The outcome of this research can help highway agencies to detect and classify cracks accurately for a very long highway without a need for manual inspection, which can significantly minimize cost.

Hough transform algorithm was tested in terms of detect and classify a large dataset of highway images, and the accuracy reaches 92.14%, which can be considered as a very accurate percentage regarding automated cracks and distresses classification.

The implementation of smart maintenance (SM) has greatly benefited facility managers, construction project managers and other stakeholders within the built environment. Unfortunately, its actualization for stakeholders in the built environment in the fourth industrial revolution (4IR) era remains a challenge. To reduce the challenge, this study aims at conducting a bibliometric analysis to unearth the critical success factors supporting SM implementation. The future direction and practice of SM in the construction industry were also explored.

A bibliometric approach was adopted for reviewing articles extracted from the Scopus database. Keywords such as (“smart maintenance“) OR (“intelligent maintenance”) OR (“technological maintenance”) OR (“automated maintenance”) OR (“computerized maintenance”) were used to extract articles from the Scopus database. The studies were restricted between 2006 and 2021 to capture the 4IR era. The initial extracted papers were 1,048; however, 288 papers were selected and analysed using VOSviewer software.

The findings revealed that the critical success factors supporting the implementation of SM in the 4IR era are collaboration, digital twin design, energy management system and decentralized data management system. Regarding the future practice of SM in the 4IR era, it was also revealed that SM is possible to evolve into maintenance 4.0. This will support the autonomous maintenance of infrastructures in the built environment.

The use of a single database contributed to the limitation of the findings from this study.

Despite the limitations, the findings of this study contributed to practice and research by providing stakeholders in the built environment with the direction of SM practice.

Stakeholders in the built environment have clamoured to implement SM in the 4IR era. This study provided the critical success factors for adopting SM, guaranteeing the 4IR era. It also provides the research trends and direction of SM practice.

Current research efforts exhibit a surge imperative for a building information modelling (BIM) approach that embodies a repository of all relevant data of existing building components while monitoring and consistently recording numerous components’ functions throughout its lifecycle, especially in Egypt. This research paper aims to develop an integrated as-is BIM-facility management (FM) information model for the existing building’s components via a case study, depicting a repository for historical data and knowledge amassed from inspections and conveying maintenance decisions automatically during the FM practices.

The developed approach pursues four successive steps: data acquisition and processing of building components; components recognition from point clouds; modelling scanned point clouds; and quick response code information transfer to BIM components.

The proposed approach incorporates the as-is BIM with the building components’ as-is FM information to portray a repository for historical data and knowledge collected from inspections to proactively benefit facility managers in simplifying, expediting and enhancing maintenance decisions automatically during FM practices.

This paper presents a digital alternative to manual maintenance recordkeeping concerning building components to retrieve their as-is and historical data using a case study in Egypt. This paper proposes a broad scan to as-is information BIM approach for the existing building’s components to condone maintenance interventions using a versatile, affordable, readily available and multi-functional method for scanning the building’s components using a handheld tool.

Construction safety is a crucial aspect that has far-reaching impacts on economic development. But safety monitoring is often reliant on labor-based observations, which can be prone to errors and result in numerous fatalities annually. This study aims to address this issue by proposing a cloud-building information modeling (BIM)-based framework to provide real-time safety monitoring on construction sites to enhance safety practices and reduce fatalities.

This system integrates an automated safety tracking mobile app to detect hazardous locations on construction sites, a cloud-based BIM system for visualization of worker tracking on a virtual construction site and a Web interface to visualize and monitor site safety.

The study’s results indicate that implementing a comprehensive automated safety monitoring approach is feasible and suitable for general indoor construction site environments. Furthermore, the assessment of an advanced safety monitoring system has been successfully implemented, indicating its potential effectiveness in enhancing safety practices in construction sites.

By using this system, the construction industry can prevent accidents and fatalities, promote the adoption of new technologies and methods with minimal effort and cost and improve safety outcomes and productivity. This system can reduce workers’ compensation claims, insurance costs and legal penalties, benefiting all stakeholders involved.

To the best of the authors’ knowledge, this study represents the first attempt in Bangladesh to develop a mobile app-based technological solution aimed at reforming construction safety culture by using BIM technology. This has the potential to change the construction sector’s attitude toward accepting new technologies and cultures through its convenient choice of equipment.

As an advanced manufacturing method, additive manufacturing (AM) technology provides new possibilities for efficient production and design of parts. However, with the continuous expansion of the application of AM materials, subtractive processing has become one of the necessary steps to improve the accuracy and performance of parts. In this paper, the processing process of AM materials is discussed in depth, and the surface integrity problem caused by it is discussed.

Firstly, we listed and analyzed the characterization parameters of metal surface integrity and its influence on the performance of parts and then introduced the application of integrated processing of metal adding and subtracting materials and the influence of different processing forms on the surface integrity of parts. The surface of the trial-cut material is detected and analyzed, and the surface of the integrated processing of adding and subtracting materials is compared with that of the pure processing of reducing materials, so that the corresponding conclusions are obtained.

In this process, we also found some surface integrity problems, such as knife marks, residual stress and thermal effects. These problems may have a potential negative impact on the performance of the final parts. In processing, we can try to use other integrated processing technologies of adding and subtracting materials, try to combine various integrated processing technologies of adding and subtracting materials, or consider exploring more efficient AM technology to improve processing efficiency. We can also consider adopting production process optimization measures to reduce the processing cost of adding and subtracting materials.

With the gradual improvement of the requirements for the surface quality of parts in the production process and the in-depth implementation of sustainable manufacturing, the demand for integrated processing of metal addition and subtraction materials is likely to continue to grow in the future. By deeply understanding and studying the problems of material reduction and surface integrity of AM materials, we can better meet the challenges in the manufacturing process and improve the quality and performance of parts. This research is very important for promoting the development of manufacturing technology and achieving success in practical application.

An interaction between emerging technologies (ETs) for facility management (FM) activities and stakeholder skills is necessary to promote the optimization of FM performance. Previous studies do not show strategies for the selection of ETs in FM considering the technological competencies of stakeholders. Thus, this study analyzes the interactions between ETs and FM from the perceptions of Brazilian professionals, identifying the most appropriate and effective technological solutions, based on a broad literature review.

The steps of the methodology are as follows: systematic literature review (SLR); detailing the ETs for FM; online questionnaire based on SLR findings; sample of Brazilian FM professionals; statistical treatment; and discussion.

Results indicate wireless sensor network, Internet of Thing, building information modeling and Big Data as ETs in FM with greater potential for optimization in the performance of FM activities, from survey respondents.

The scope of possible findings may have been biased, considering the small number of research participants and current transformations resulting from the COVID-19 pandemic (e.g. changes to standard operating procedures).

The results ensure greater security to facility managers in the effective implementation of ETs in FM activities.

The research explores the published studies and the consultation with Brazilian FM professionals in the selection of ETs.

Many economic, political and socio-cultural events in the 2020s have been strong headwinds for architecture, engineering and construction (AEC). Nevertheless, technological advancements (e.g. artificial intelligence (AI), big data and robotics) provide promising avenues for the development of AEC. This study aims to map the state of the literature on automation in AEC and thereby be of value not only to those researching automation and its composition of a variety of distinct technological and system classes within AEC, but also to practitioners and policymakers in shaping the future of AEC.

This review adopts scientometric methods, which have been effective in the research of large intra and interdisciplinary domains in the past decades. The full dataset consists of 1,871 articles on automation in AEC.

This overarching scientometric review offers three interdisciplinary streams of research: technological frontiers, project monitoring and applied research in AEC. To support the scientometric analysis, the authors offer a critical integrative review of the literature to proffer a multilevel, multistage framework of automation in AEC, which demonstrates an abundance of technological paradigm discussions and the inherent need for a holistic managerial approach to automation in AEC.

The authors underline employee well-being, business sustainability and social growth outcomes of automation and provide several managerial implications, such as the strategic management approach, ethical management view and human resource management perspective. In doing so, the authors seek to respond to the Sustainable Development Goals proposed by the United Nations as this becomes more prevalent for the industry and all levels of society in general.

This research aims to analyze the literature on Quality 4.0 and pinpoint the essential factors contributing to its success. Additionally, the research aims to develop a framework that can be used to create a capable workforce necessary for the successful implementation of Quality 4.0.

By following a systematic approach, the authors could ensure that their literature review was comprehensive and unbiased. Using a set of pre-determined inclusion and exclusion criteria, the authors screened 90 research articles to obtain the most relevant and reliable information for their study.

The authors' review identified essential findings, including the evolution of literature in the field of Quality 4.0 and the systematization of previous literature reviews focusing on training and development. The authors also identified several training barriers to implementing Quality 4.0 and proposed a model for building a competent workforce using Kolb's experiential learning model.

The authors' research offers insights into the training barriers that must be considered when building a competent workforce. Using the framework proposed in the authors' research, consultants and managers can better integrate Quality 4.0 into their organizations.

The adoption of Quality 4.0 has significant social implications and is essential for advancing sustainability. It can improve efficiency, reduce waste, minimize environmental impacts and better meet the needs and expectations of stakeholders.

The authors' study stands out as one of the earliest reviews of the literature on Quality 4.0 to incorporate the theory-context-method (TCM) framework, allowing to provide unique insights into future research directions that had not been previously explored.

This paper aims to explore augmented reality (AR) applications in construction safety academic literature and propose possible improvements for future scholarly works. The paper explicitly focuses on AR integration with Construction 4.0 technologies as an effective solution to safety concerns in the construction industry.

This study applied a systematic review approach. In total, 387 potentially relevant articles from databases were identified. Once filtering criteria were applied, 29 eligible papers where selected. The inclusion criteria were being directly associated with construction safety focused on an AR application and AR interactions associated with the Construction 4.0 technologies.

This study investigated the structure of AR applications in construction safety. To this end, the authors studied the safety purposes of AR applications in construction safety: pre-event (intelligent operation, training, safety inspection and hazard alerting), during-event (pinpointing hazard) and post-event (safety estimation) applications. Then, the integration of AR with Construction 4.0 technologies was elaborated. The systematic review also revealed that the AR integration has contributed to developing several technical aspects of AR technology: display, tracking and human–computer interaction. The study results indicate that AR integration with construction is effective in mitigating safety concerns; however, further research studies are required to support this statement.

This study contributes to exploring applications and integrations of AR into construction safety in order to facilitate the leverage of this technology. This review can help encourage practitioners and researchers to conduct further academic investigations into AR application in construction safety.

Green building (GB) maintenance is increasingly accepted in the construction industry, so it can now be interpreted as an industry best practice for maintenance planning. However, the performance competency and design knowledge of the practice's building control instrument process can be affected by its evaluation and the information management of building information modelling (BIM)–based model checking (BMC). These maintenance-planning problems have not yet been investigated in instances such as the Grenfell Tower fire (14 June 2017, approximately 80 fatalities) in North Kensington, West London.

This study proposes a theoretical framework for analysing the existing conceptualisation of BIM tools and techniques based on a critical review of GB maintenance environments. These are currently employed on GB maintenance ecosystems embedded in project teams that can affect BMC practices in the automation system process. In order to better understand how BMC is implemented in GB ecosystem projects, a quantitative case study is conducted in the Malaysian public works department (Jabatan Kerja Raya (JKR)).

GB ecosystem projects were not as effective as planned due to safety awareness, design planning, inadequate track insulation, environmental (in) compatibility and inadequate building access management. Descriptive statistics and an ANOVA were applied to analyse the data. The study is reinforced by a process flow, which is transformed into a theoretical framework.

Industry practitioners can use the developed framework to diagnose BMC application issues and leverage the staff competency inherent in an ecosystem to plan GB maintenance environments successfully.