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The use of building information modelling (BIM) methodology has been increasing in the architecture, engineering, construction and operation sector, driven to a new paradigm of work with the use of three-dimensional (3D) parametric models. However, building information modelling (BIM) has been mostly used for as-built models of a building, not yet been widely used by designers during project and construction phases for occupational risks prevention and safety planning. This paper aims to show the capacity of developing tools that allow adding functionalities to Revit software to improve safety procedures and reduce the time spent on modelling them during the design phase.

To reach this objective, a structural 3D model of a building is used to validate the developed tools. A plugin prototype based on legal regulations was developed, allowing qualitative safety assessment through the application of job hazard analysis (JHA), SafeObject and checklists. These tools allow the automated detection of falls from height situations and the automated placement of the correspondent safety systems.

Revit application programming interface allowed the conception and addition of several functionalities that can be used in BIM methodology, and more specifically in the prevention of occupational risks in construction, contributing this paper to the application of a new approach to the prevention through design.

This paper is innovative and important because the developed plugins allowed: automated detection of potential falls from heights in the design stage; automated introduction of safety objects from a BIM Safety Objects Library; and the intercommunication between a BIM model and a safety database, bringing JHA integration directly on the project. The prototype of this work was validated for fall from height hazards but can be extended to other potentials hazards since the initial design stage.

In recent years, deep learning and extended reality (XR) technologies have gained popularity in the built environment, especially in construction engineering and management. A significant amount of research efforts has been thus dedicated to the automation of construction-related activities and visualization of the construction process. The purpose of this study is to investigate potential research opportunities in the integration of deep learning and XR technologies in construction engineering and management.

This study presents a literature review of 164 research articles published in Scopus from 2006 to 2021, based on strict data acquisition criteria. A mixed review method, consisting of a scientometric analysis and systematic review, is conducted in this study to identify research gaps and propose future research directions.

The proposed research directions can be categorized into four areas, including realism of training simulations; integration of visual and audio-based classification; automated hazard detection in head-mounted displays (HMDs); and context awareness in HMDs.

This study contributes to the body of knowledge by identifying the necessity of integrating deep learning and XR technologies in facilitating the construction engineering and management process.

The purpose of this paper is to investigate building information modelling (BIM) integrated Internet of Things (IoT) architectures extensively and provide comparative evaluation of those against deciding parameters pertaining to their characteristics and subsequent applications in construction industry.

This paper identifies BIM-integrated cyber physical system frameworks, specific to project objectives, comprising of sensors working as physical assets and BIM-based virtual models acting as the cyber component , connected via wired or wireless protocols (e.g. WiFi, Zigbee, near-field communication, mobile-to-mobile, Zwave, 3 G, 4 G, long-term evolution, 5 G and low-power wide-area networks) and their potential applications in decision-making, visual management, logistics and supply chain management, smart building system management and structural performance assessment, etc. Such proposed architectures are evaluated against deciding parameters such as availability, reliability, mobility, performance, management, scalability, interoperability and security and privacy to evaluate their respective efficiencies.

This study finds that the underlying aim of planned IoT frameworks is to integrate systems and processes for a better information flow and to initiate shift from silo solutions to a smart ecosystem. The efficiencies of such frameworks are completely subjective to their respective project natures, objectives and requirements.

This study is unique in its nature to identify requirements of an efficient BIM-integrated IoT architecture and provide comprehensive insights about potential applications in construction industry.

Accidents resulting from poorly planned or setup work environments are a major concern within the construction industry. While traditional education and training of personnel offer well-known approaches for establishing safe work practices, serious games in virtual reality (VR) are increasingly being used as a complementary approach for active learning experiences. By taking full advantage of data collection and the interactions possible in the virtual environment, the education and training of construction personnel improves by using non-biased feedback and immersion.

This research presents a framework for the generation and automated assessment of VR data. The proposed approach is tested and evaluated in a virtual work environment consisting of multiple hazards. VR requires expensive hardware, technical knowledge and user acceptance to run the games effectively. An effort has been made to transfer the advantages VR gives to a physical setup. This is done using a light detection and ranging sensing system, which collects similar data and enables the same learning experiences.

Encouraging results on the participants’ experiences are presented and discussed based on actual needs in the Danish construction industry. An outlook presents future avenues towards enhancing existing learning methods.

The proposed method will help develop active learning environments, which could lead to safer construction work stations in the future, either through VR or physical simulations.

The utilization of run-time data collection and automatic analysis allows for better personalized feedback in the construction safety training. Furthermore, this study investigates the possibility of transferring the benefits of this system to a physical setup that is easier to use on construction sites without investing in a full VR setup.

The current fire protection measures in buildings do not account for all contemporary fire hazard issues, which has made fire safety a growing concern. Therefore, this paper aims to present a critical review of current fire protection measures and their applicability to address current challenges relating to fire hazards in buildings.

To overcome fire hazards in buildings, impact of fire hazards is also reviewed to set the context for fire protection measures. Based on the review, an integrated framework for mitigation of fire hazards is proposed. The proposed framework involves enhancement of fire safety in four key areas: fire protection features in buildings, regulation and enforcement, consumer awareness and technology and resources advancement. Detailed strategies on improving fire safety in buildings in these four key areas are presented, and future research and training needs are identified.

Current fire protection measures lead to an unquantified level of fire safety in buildings, provide minimal strategies to mitigate fire hazard and do not account for contemporary fire hazard issues. Implementing key measures that include reliable fire protection systems, proper regulation and enforcement of building code provisions, enhancement of public awareness and proper use of technology and resources is key to mitigating fire hazard in buildings. Major research and training required to improve fire safety in buildings include developing cost-effective fire suppression systems and rational fire design approaches, characterizing new materials and developing performance-based codes.

The proposed framework encompasses both prevention and management of fire hazard. To demonstrate the applicability of this framework in improving fire safety in buildings, major limitations of current fire protection measures are identified, and detailed strategies are provided to address these limitations using proposed fire safety framework.

Fire represents a severe hazard in both developing and developed countries and poses significant threat to life, structure, property and environment. The proposed framework has social implications as it addresses some of the current challenges relating to fire hazard in buildings and will enhance overall fire safety.

The novelty of proposed framework lies in encompassing both prevention and management of fire hazard. This is unlike current fire safety improvement strategies, which focus only on improving fire protection features in buildings (i.e. managing impact of fire hazard) using performance-based codes. To demonstrate the applicability of this framework in improving fire safety in buildings, major limitations of current fire protection measures are identified and detailed strategies are provided to address these limitations using proposed fire safety framework. Special emphasis is given to cost-effectiveness of proposed strategies, and research and training needs for further enhancing building fire safety are identified.

The purpose of this paper is to investigate hazards for minor users while they are exposed to social networks. In particular, it provides the statistical relationship of these hazards with the exposure time as well as the amount of published personal information.

An experiment was conducted that has revealed a huge number of personal information exposed by users of social network applications. Moreover, a significant amount of suspicious activity against minors has been recorded. Experimental data led to the hypothesis that online hazards can be modeled with known statistical distributions. In order to examine this hypothesis, survival analysis techniques, which involve the estimation of certain functions that reflect the relation of a disastrous event with time, were applied.

The results show that the incoming hazards for minor female profiles follow the Logistic distribution, while the corresponding hazards for minor male profiles follow the Normal distribution.

The findings of this work are crucial for developing an effective system for automated grooming recognition in real time by optimizing the detection threshold as a function of time. Thus, the threshold sensitivity can be appropriately adjusted such that lower frequencies of occurrence lead to lower threshold sensitivities, and higher frequencies of occurrence lead to higher threshold sensitivities.

The development of communication and artificial intelligence technologies has raised interest in connectivity and increased autonomy of automated earthmoving equipment for earthwork. These changes are motivating work to reduce uncertainties, in terms of improving equipment object detection capability and reducing strikes and accidents on site. The purpose of this study is to illustrate industrial drivers for automated earthwork systems; identify the specific capabilities which make the transformation happen; and finally determine use cases that create value for the system. These three objectives act as components of a technology roadmap for automated and connected earthwork and can guide development of new products and services.

This paper used a text mining approach in which the required data was captured through a structured literature review, and then expert knowledge was used for verification of the results.

Automated and connected earthwork can enhance construction site and its embraced infrastructure, resilience by avoiding human faults during operations. Automating the monitoring process can lead to reliable anticipation of problems and facilitate real-time responses to unexpected situation via connectedness capabilities. Research findings are presented in three sections: industrial perspectives, trends and drivers for automated and connected earthwork; capabilities which are met by technologies; and use cases to demonstrate different capabilities.

This study combines the results of disintegrated and fragmented research in the area of automated and connected earthwork and categorises them under new capability levels. The identified capabilities are classified in three main categories including reliable environmental perception, single equipment decision-making toward safe outcomes and fleet-level safety enhancement. Finally, four different levels of automation are proposed for earthwork technology roadmap.

The purpose of this paper is to investigate the critical time window for pro-active construction accident prevention and response. Large to small organisations throughout the entire construction supply chain continue to be challenged to adequately prevent accidents. Construction worker injuries and fatalities represent significant waste of resources. Although the five C’s (culture, competency, communication, controls and contractors) have been focusing on compliance, good practices and best-in-class strategies, even industry leaders have only marginal improvements in recorded safety statistics for many years.

Right-time vs real-time construction safety and health identifies three major focus areas to aid in the development of a strategic, as opposed to tactical, response. Occupational safety and health by design, real-time safety and health monitoring and alerts and education, training and feedback leveraging state-of-the-art technology provide meaningful predictive, quantitative and qualitative measures to identify, correlate and eliminate hazards before workers get injured or incidents cause collateral damage.

The current state and development of existing innovative initiatives in the occupational construction safety and health domain are identified. A framework for right-time vs real-time construction safety and health presents the specific focus on automated safety and health data gathering, analysis and reporting to achieve better safety performance. The developed roadmap for right-time vs real-time safety and health is finally tested in selected application scenarios of high concern in the construction industry.

A strategic roadmap to eliminate hazards and accidents through right-time vs real-time automation is presented that has practical as well as social implications on conducting a rigorous safety culture and climate in a construction business and its entire supply chain.

The purpose of this article is to illustrate how sensors impart perceptive capabilities to robots. This is the second part of a two-part article. This second part considers positional awareness and sensing in the external environment, notably but not exclusively by autonomous, mobile robots.

Following a short introduction, this article first discusses positional sensing and navigation by mobile robots, including self-driving cars, automated guided vehicles, unmanned aerial vehicles (UAVs) and autonomous underwater vehicles (AUVs). It then considers sensing with UAVs and AUVs, and finally discusses robots for hazard detection. Brief concluding comments are drawn.

This shows that sensors based on a multitude of techniques confer navigational capabilities to mobile robots, including LIDARs, radar, sonar, imaging and inertial sensing devices. UAVs, AUVs and mobile terrestrial robots can be equipped with all manner of sensors to create detailed terrestrial and underwater maps, monitor air and water quality, locate pollution and detect hazards. While existing sensors are used widely, many new devices are now being developed to meet specific requirements and to comply with size, weight and cost restraints.

The use of mobile robots is growing rapidly, and this article provides a timely account of how sensors confer them with positional awareness and allow them to act as mobile sensing platforms.