BIM-enabled built-asset information management conceptual framework: A case of public university buildings in Addis Ababa, Ethiopia.

The integration of BIM with other digital advancements has demonstrably led to an increase of performance in the Architecture, Engineering, Construction and Operation (AECO) industry. This integration not only is showing promising results in boosting the industry's performance, but also the productivity and promotes data-driven decision-making. Despite these benefits, there are limited studies that address the integration of BIM and digital data for managing built-assets in general and in developing countries in particular. To fill this gap, a closer assessment of current built-asset information management practice is necessary. The assessment of the practice examines how digital processes and/or technology can be seamlessly integrated into existing practices. In this regard, this study aims to provide valuable insights into increasing the maturity of built-asset information management by integrating digital data with BIM. The study uses a case-based research design using built-assets (universities in Addis Ababa) as public building representative to capture the prevailing information management practices in Ethiopian public buildings. The findings reveal that traditional paper-based practices still dominate the management of built-assets. This leads to difficulties in terms of data loss, unavailability, inaccuracy, and unreliability, all of which are detrimental to the overall performance. Based on these findings, a conceptual framework is designed to improve the performance of built-assets and help owners, end-users, and managers in defining data and information requirements for BIM-enabled asset information management. The framework delineates processes for structured information requirements definition and validation of various asset data from varying sources. The framework utilizes a BIM-enabled platform as a single source of truth and offers a comprehensive solution to the identified challenges. The findings of this study holds significant promise for improving the existing practice of built-asset information management within the study context.

Integrated Building Modelling Using Geomatics and GPR Techniques for Cultural Heritage Preservation: A Case Study of the Charles V Pavilion in Seville (Spain).

This paper highlights the fundamental role of integrating different geomatics and geophysical imaging technologies in understanding and preserving cultural heritage, with a focus on the Pavilion of Charles V in Seville (Spain). Using a terrestrial laser scanner, global navigation satellite system, and ground-penetrating radar, we constructed a building information modelling (BIM) system to derive comprehensive decision-making models to preserve this historical asset. These models enable the generation of virtual reconstructions, encompassing not only the building but also its subsurface, distributable as augmented reality or virtual reality online. By leveraging these technologies, the research investigates complex details of the pavilion, capturing its current structure and revealing insights into past soil compositions and potential subsurface structures. This detailed analysis empowers stakeholders to make informed decisions about conservation and management. Furthermore, transparent data sharing fosters collaboration, advancing collective understanding and practices in heritage preservation.

The Representational Challenge for Designing and Managing 5P Medicine Ecosystems.

Health and social care systems around the globe currently undergo a transformation towards personalized, preventive, predictive, participative precision medicine (5PM), considering the individual health status, conditions, genetic and genomic dispositions, etc., in personal, social, occupational, environmental and behavioral context. This transformation is strongly supported by technologies such as micro- and nanotechnologies, advanced computing, artificial intelligence, edge computing, etc. For enabling communication and cooperation between actors from different domains using different methodologies, languages and ontologies based on different education, experiences, etc., we have to understand the transformed health ecosystems and all its components in structure, function and relationships in the necessary detail ranging from elementary particles up to the universe. That way, we advance design and management of the complex and highly dynamic ecosystem from data to knowledge level. The challenge is the consistent, correct and formalized representation of the transformed health ecosystem from the perspectives of all domains involved, representing and managing them based on related ontologies. The resulting business view of the real-world ecosystem must be interrelated using the ISO/IEC 21838 Top Level Ontologies standard. Thereafter, the outcome can be transformed into implementable solutions using the ISO/IEC 10746 Open Distributed Processing Reference Model. Model and framework for this system-oriented, architecture-centric, ontology-based, policy-driven approach have been developed by the first author and meanwhile standardized as ISO 23903 Interoperability and Integration Reference Architecture.

A method of building information modelling implementation for structural engineering firms.

Building Information Modelling (BIM), a new concept and methodology, has received much attention lately. Various Structural Engineering Firms (SEFs) have observed substantial competitive benefits after its deployment. BIM offers a wide range of advantages, but its capacity has not even been completely exploited. The challenges of firm implementation, a procedure that necessitates significant alterations in firm business structure, are a major factor in this. However, there hasn't been much in-depth research on the assessment and integration of the research around the application of BIM in firms. To address the planning phase's complexity, which makes implementing BIM in these workplaces challenging, this article provides a framework for BIM deployment in the SEF. Additionally, a brand-new hybrid African Buffalo and African Vulture Optimization (AB-AVO) has been created to assess the state of technology. The technique suggested for BIM execution within SEF obviously and effectively recognises the firm's expectations and resources, sets out the needs required to create the BIM technique, and offers technical and clinical suggestions for monitoring and planning the execution. It is categorised by resource utilization, versatility, and adaptability.•This paper introduces a new concept and methodology of using BIM•The technique suggested for BIM execution within SEF obviously and effectively recognises the firm's expectations and resources•The method establishes guidelines for structural firm to adopt BIM in their monitoring, and planning the execution.

A bibliometric analysis of building information modelling implementation barriers in the developing world using an interpretive structural modelling approach.

Over the past 20 years, the phrase "Building Information Modelling" (BIM) has spread throughout the Architecture, Engineering and Construction (AEC) industries. BIM usage in the construction industry is vital in the revolution towards Industry 4.0 in the AEC Industry. BIM contributes to this change due to its automatization and sustainability features. However, there are growing concerns about its implementation in the developing world context. The BIM Implementation Barriers (BIMIBs) in individual countries and on a global scale have been examined in a variety of studies and works of literature, but two research questions are still open; (1) what specific BIMIBs are the AEC industries in the developing world encountering the most, and (2) what is the interrelationship between these barriers? Through a combination of expert interviews and a bibliometric analysis of published relevant empirical studies on the subject, the aim of this study is to identify these frequently occurring BIMIBs in the developing world and to determine the interrelationships between these barriers using an Interpretive Structural Modelling (ISM) approach and MICMAC analysis. The study identified the 14 BIMIBs with 'high associated cost' as the most fundamental of all. A comparison of the study's findings and a proposed 3-level barrier mitigation strategy with other studies identified the lack of governmental support for BIM implementation and research as a root cause of majority of the BIMIBs identified in the developing world. This study lays forth the knowledge base for future studies in the area of BIM implementation in the developing world.

Dataset of characterised construction safety risks and related treatments.

The Safety Risk Library [1] is a structured database [2] that integrates knowledge drawn from multiple sources to address the problem of information disaggregation in the construction industry. This knowledge base maps construction safety risk scenarios to treatment suggestions that help designers implement the concept of prevention through design. In the context of the Safety Risk Library, risk scenarios are characterised by six data categories based on a formalised ontology [3]. To build the first iteration of the Safety Risk Library, nine different risk scenarios were identified and mapped to relevant risk treatments in focus groups. Subsequently, the Safety Risk Library was pilot tested in six construction projects, and user feedback and input were used to expand the list of risk scenarios and treatment prompts. Additionally, public press releases reporting construction accidents were analysed to identify and characterise risk scenarios, which were then mapped to appropriate treatment suggestions and included in the Safety Risk Library. This dataset can assist construction industry stakeholders in identifying, characterising, communicating and mitigating safety risks in construction projects. It can also be integrated into building information modelling environments to assist designers to implement prevention through design.

Construction and Maintenance of Building Geometric Digital Twins: State of the Art Review.

Most of the buildings that exist today were built based on 2D drawings. Building information models that represent design-stage product information have become prevalent in the second decade of the 21st century. Still, it will take many decades before such models become the norm for all existing buildings. In the meantime, the building industry lacks the tools to leverage the benefits of digital information management for construction, operation, and renovation. To this end, this paper reviews the state-of-the-art practice and research for constructing (generating) and maintaining (updating) geometric digital twins. This paper also highlights the key limitations preventing current research from being adopted in practice and derives a new geometry-based object class hierarchy that mainly focuses on the geometric properties of building objects, in contrast to widely used existing object categorisations that are mainly function-oriented. We argue that this new class hierarchy can serve as the main building block for prioritising the automation of the most frequently used object classes for geometric digital twin construction and maintenance. We also draw novel insights into the limitations of current methods and uncover further research directions to tackle these problems. Specifically, we believe that adapting deep learning methods can increase the robustness of object detection and segmentation of various types; involving design intents can achieve a high resolution of model construction and maintenance; using images as a complementary input can help to detect transparent and specular objects; and combining synthetic data for algorithm training can overcome the lack of real labelled datasets.

Monitoring and Assessment of Indoor Environmental Conditions in Educational Building Using Building Information Modelling Methodology.

Managing indoor environmental quality (IEQ) is a challenge in educational buildings in the wake of the COVID-19 pandemic. Adequate indoor air quality is essential to ensure that indoor spaces are safe for students and teachers. In fact, poor IEQ can affect academic performance and student comfort. This study proposes a framework for integrating occupants' feedback into the building information modelling (BIM) methodology to assess indoor environmental conditions (thermal, acoustic and lighting) and the individual airborne virus transmission risk during teaching activities. The information contained in the parametric 3D BIM model and the algorithmic environment of Dynamo were used to develop the framework. The IEQ evaluation is based on sensor monitoring and a daily schedule, so the results show real problems of occupants' dissatisfaction. The output of the framework shows in which range the indoor environmental variables were (optimal, acceptable and unacceptable) and the probability of infection during each lecture class (whether or not 1% is exceeded). A case study was proposed to illustrate its application and validate it. The outcomes provide key information to support the decision-making process for managing IEQ and controlling individual airborne virus transmission risks. Long-term application could provide data that support the management of ventilation strategies and protocol redesign.

Long-Standing Themes and Future Prospects for the Inspection and Maintenance of Façade Falling Objects from Tall Buildings.

The increasing number of accidents arising from falling objects from the façade of tall buildings has attracted much attention globally. To regulators, a preventive approach based on a mandatory periodic façade inspection has been deemed as a necessary measure to maintain the functionality and integrity of the façade of tall buildings. Researchers worldwide have been working towards a predictive approach to allow for the assessment of the likely failure during some future period, by measuring the condition of the façade to detect latent defects and anomalies. The methods proposed include laser scanning, image-based sensing and infrared thermography to support the automatic façade visual inspection. This paper aims to review and analyse the state-of-the-art literature on the automated inspection of building façades, with emphasis on the detection and maintenance management of latent defects and anomalies for falling objects from tall buildings. A step-by-step holistic method is leveraged to retrieve the available literature from databases, followed by the analyses of relevant articles in different long-standing research themes. The types and characteristics of façade falling objects, legislations, practices and the effectiveness of various inspection techniques are discussed. Various diagnostic, inspection and analytical methods which support façade inspection and maintenance are analysed with discussion on the potential future research in this field.

BIM-based task and motion planning prototype for robotic assembly of COVID-19 hospitalisation light weight structures.

Fast transmission of COVID-19 led to mass cancelling of events to contain the virus outbreak. Amid lockdown restrictions, a vast number of construction projects came to a halt. Robotic platforms can perform construction projects in an unmanned manner, thus ensuring the essential construction tasks are not suspended during the pandemic. This research developed a BIM-based prototype, including a task planning algorithm and a motion planning algorithm, to assist in the robotic assembly of COVID-19 hospitalisation light weight structures with prefabricated components. The task planning algorithm can determine the assembly sequence and coordinates for various types of prefabricated components. The motion planning algorithm can generate robots' kinematic parameters for performing the assembly of the prefabricated components. Testing of the prototype finds that it has satisfactory performance in terms of 1) the reasonableness of assembly sequence determined, 2) reachability for the assembly coordinates of prefabricated components, and 3) capability to avoid obstacles.

Implementation of Facility Management for Port Infrastructure through the Use of UAVs, Photogrammetry and BIM.

The maintenance of port infrastructures presents difficulties due to their location: an aggressive environment or the variability of the waves can cause progressive deterioration. Maritime conditions make inspections difficult and, added to the lack of use of efficient tools for the management of assets, planning maintenance, important to ensure operability throughout the life cycle of port infrastructures, is generally not a priority. In view of these challenges, this research proposes a methodology for the creation of a port infrastructure asset management tool, generated based on the Design Science Research Method (DSRM), in line with Building Information Modeling (BIM) and digitization trends in the infrastructure sector. The proposal provides workflows and recommendations for the survey of port infrastructures from UAVs, the reconstruction of digital models by photogrammetry (due to scarce technical documentation), and the reconstruction of BIM models. Along with this, the bidirectional linking of traditional asset management spreadsheets with BIM models is proposed, by visual programming, allowing easy visualization of the status and maintenance requirements. This methodology was applied to a port infrastructure, where the methodology demonstrated the correct functionality of the asset management tool, which allows a constant up-dating of information regarding the structural state of the elements and the necessary maintenance activities.

Generative Design in Building Information Modelling (BIM): Approaches and Requirements.

The integration of generative design (GD) and building information modelling (BIM), as a new technology consolidation, can facilitate the constructability of GD's automatic design solutions, while improving BIM's capability in the early design phase. Thus, there has been an increasing interest to study GD-BIM, with current focuses mainly on exploring applications and investigating tools. However, there are a lack of studies regarding methodological relationships and skill requirement based on different development objectives or GD properties; thus, the threshold of developing GD-BIM still seems high. This study conducts a critical review of current approaches for developing GD in BIM, and analyses methodological relationships, skill requirements, and improvement of GD-BIM development. Accordingly, novel perspectives of objective-oriented, GD component-based, and skill-driven GD-BIM development as well as reference guides are proposed. Finally, future research directions, challenges, and potential solutions are discussed. This research aims to guide designers in the building industry to properly determine approaches for developing GD-BIM and inspire researchers' future studies.

BIM and Data-Driven Predictive Analysis of Optimum Thermal Comfort for Indoor Environment.

Mechanical ventilation comprises a significant proportion of the total energy consumed in buildings. Sufficient natural ventilation in buildings is critical in reducing the energy consumption of mechanical ventilation while maintaining a comfortable indoor environment for occupants. In this paper, a new computerized framework based on building information modelling (BIM) and machine learning data-driven models is presented to analyze the optimum thermal comfort for indoor environments with the effect of natural ventilation. BIM provides geometrical and semantic information of the built environment, which are leveraged for setting the computational domain and boundary conditions of computational fluid dynamics (CFD) simulation. CFD modelling is conducted to obtain the flow field and temperature distribution, the results of which determine the thermal comfort index in a ventilated environment. BIM-CFD provides spatial data, boundary conditions, indoor environmental parameters, and the thermal comfort index for machine learning to construct robust data-driven models to empower the predictive analysis. In the neural network, the adjacency matrix in the field of graph theory is used to represent the spatial features (such as zone adjacency and connectivity) and incorporate the potential impact of interzonal airflow in thermal comfort analysis. The results of a case study indicate that utilizing natural ventilation can save cooling power consumption, but it may not be sufficient to fulfil all the thermal comfort criteria. The performance of natural ventilation at different seasons should be considered to identify the period when both air conditioning energy use and indoor thermal comfort are achieved. With the proposed new framework, thermal comfort prediction can be examined more efficiently to study different design options, operating scenarios, and changeover strategies between various ventilation modes, such as better spatial HVAC system designs, specific room-based real-time HVAC control, and other potential applications to maximize indoor thermal comfort.

Application of Building Information Modelling (BIM) in the Health Monitoring and Maintenance Process: A Systematic Review.

Improvements in the science of health monitoring and maintenance have facilitated the observation of damage and defects in existing structures and infrastructures, such as bridges and railways. The need to extend sensing technology through the use of wireless sensors as well as the lack of description tools for understanding, visualizing, and documenting sensor outputs has encouraged researchers to use powerful tools such as Building Information Modelling (BIM) systems. BIM has become important because of conducting tools widely used in the Architecture, Engineering, and Construction (AEC) industry to present and manage information on structural systems and situations. Since combining health monitoring and maintenance results with BIM models is a new field of study, and most projects utilize various aspects of it, we have conducted a review of important work related to this subject published from 2010 to November of 2020. After reviewing 278 journal articles, research trends, approaches, methods, gaps, and future agenda related to BIM in monitoring and maintenance were highlighted. This paper, through a bibliometric and content analysis, concludes that besides main improvements, some limitations now exist which affect the modeling and maintenance process. These limitations are related to extending the IFC schema, optimizing sensor data, interoperability among various BIM platforms, optimization of various sensing technologies for fault detection and management of huge amounts of data, besides consideration of environmental effects on monitoring hazards and underground objects. Finally, this paper aims to help to solve the mentioned limitation through a comprehensive review of existing research.

Building information modelling to mitigate the health and safety risks associated with the construction industry: a review.

As the construction industry continues to develop across the world, it is crucial that the industry begins to integrate digital technologies into all aspects of design, planning, construction, maintenance and even demolition of construction projects. This review explores the current use of this technology to help mitigate risks on site with a focus on proactive design rather than reactive mitigations, with the aim of directing further research on the topic to help improve the health and safety record in construction. A variety of literature was reviewed specifically relating to the integration of building information modelling into construction alongside an array of construction safety literature. Integrating these two strands of literature has allowed for the suggestion of new practical methods of recording and presenting health and safety information by facilitating a risk identification process that assigns assets with hazards and mitigations.

A Framework for an Indoor Safety Management System Based on Digital Twin.

With the development of the next generation of information technology, an increasing amount of attention is being paid to smart residential spaces, including smart cities, smart buildings, and smart homes. Building indoor safety intelligence is an important research topic. However, current indoor safety management methods cannot comprehensively analyse safety data, owing to a poor combination of safety management and building information. Additionally, the judgement of danger depends significantly on the experience of the safety management staff. In this study, digital twins (DTs) are introduced to building indoor safety management. A framework for an indoor safety management system based on DT is proposed which exploits the Internet of Things (IoT), building information modelling (BIM), the Internet, and support vector machines (SVMs) to improve the level of intelligence for building indoor safety management. A DT model (DTM) is developed using BIM integrated with operation information collected by IoT sensors. The trained SVM model is used to automatically obtain the types and levels of danger by processing the data in the DTM. The Internet is a medium for interactions between people and systems. A building in the bobsleigh and sled stadium for the Beijing Winter Olympics is considered as an example; the proposed system realises the functions of the scene display of the operation status, danger warning and positioning, danger classification and level assessment, and danger handling suggestions.

Clean construction and demolition waste material cycles through optimised pre-demolition waste audit documentation: A review on building material assessment tools.

Waste from the construction sector poses huge challenges for sustainable waste management. This is not only due to the vast amount of waste produced in construction and demolition activities, but also due to pollutants potentially contained in these products. Subject to these conditions, waste management must ensure recovery of as many resources as possible, while making sure to keep material loops clean. This demanding task requires more knowledge about the existing building stock and an adaptation of current demolition processes. Innovative technologies, such as Building Information Modelling, or modern frameworks, such as Geographic Information Systems, offer a high potential to synoptically provide stock material information for future demolition activities for individual objects to be deconstructed as well as for whole cities as a basis for managing the anthropogenic stock and potential urban mining. Suitable methods of data collection allow for acquiring the desired input for the generation of building stock models enriched with demolition-related information. With the latter, selective deconstruction strategies as well as appropriate waste stream routing agendas can be planned and executed, thereby securing safety at work during the demolition process itself and a waste stream routing according to the waste hierarchy. This review article gives an overview of currently deployed building material assessment tools (data capture and visualisation), both a prerequisite for improved information on materials and geometry (and thereby mass/volume). In addition, this article describes workflows employable for the purpose of urban mining in end-of-life buildings, of which one holistic approach will be described in depth.

Examining Green Star certification uptake and its relationship with Building Information Modelling (BIM) adoption in New Zealand.

Although academia has concentrated on issues related to green building recently, Green Star, considered as the primary green rating system in New Zealand, has not caught adequate attention, leading to its slow development with a modest number of certified projects. This research aims to explore the perspectives of the key stakeholders in the New Zealand construction industry towards the use of Green Star, as well as its relationship and possible integration with Building Information Modelling (BIM). Specifically, six themes including 1) benefits of Green Star certification uptake; 2) challenges/barriers to Green Star certification uptake; 3) solutions for Green Star certification uptake; 4) relationship between BIM adoption and Green Star certification uptake; 5) barriers/challenges to the integration of BIM between Green Star; and 6) solutions for the integration between BIM and Green Star were highlighted. The data was collected from 21 semi-structured interviews with industry experts. The results identified a range of benefits and barriers/challenges to the use of Green Star. The research offers a variety of suggestions to encourage Green Star development, with more extensive education playing a critical role, combined with greater integration of BIM with Green Star. The results could be considered baseline information for the construction professionals and academia to have effective strategies towards BIM and Green Star adoption.

Methods for monitoring construction off-road vehicle emissions: a critical review for identifying deficiencies and directions.

The paper reviews the existing applications of sensing technologies for measuring construction off-road vehicle emissions (COVE) such as earthmoving equipment. The current literature presented different measurement methods and reported the results of utilisation of new technologies for measuring COVE. However, previous papers used different technology applications covering only a part of the monitoring process with its own limitations. Since technologies are advancing and offering novel solutions, there is an urgent need to identify the gaps, re-evaluate the current methods, and develop a critical agenda for automating the entire process of collecting emissions data from construction sites, and monitoring the emission contributors across cities. This paper systematically identifies relevant papers through a search of three key databases-Web of Science, Engineering Valley and Scopus-covering the publications in the last decade from 2008 to 2017. An innovative robust research method was designed to select and analyse the relevant papers. The identified papers were stored in a data set, and a thematic algorithm employed to find the clusters of papers which might be potentially relevant. The selected papers were used for further micro-thematic analysis to find key relevant papers on COVE, and the gap in the literature. A sample of relevant papers was found relevant to COVE and critically reviewed by coding and content analysis. This paper critically reviews the selected papers and also shows that there is a considerable gap in the applications of new technologies for measuring in-use COVE in real time based on real activities toward automated methods. This review enables practitioners and scholars to gain a concrete understanding of the gap in measuring COVE and to provide a significant agenda for future technology applications.

Orientation-Constrained System for Lamp Detection in Buildings Based on Computer Vision.

Computer vision is used in this work to detect lighting elements in buildings with the goal of improving the accuracy of previous methods to provide a precise inventory of the location and state of lamps. Using the framework developed in our previous works, we introduce two new modifications to enhance the system: first, a constraint on the orientation of the detected poses in the optimization methods for both the initial and the refined estimates based on the geometric information of the building information modelling (BIM) model; second, an additional reprojection error filtering step to discard the erroneous poses introduced with the orientation restrictions, keeping the identification and localization errors low while greatly increasing the number of detections. These enhancements are tested in five different case studies with more than 30,000 images, with results showing improvements in the number of detections, the percentage of correct model and state identifications, and the distance between detections and reference positions.