Advances in Informatics and Computing in Civil and Construction Engineering

The use of Building Information Models (BIM) for design and construction processes are growing as a whole, especially in terms of mobility platforms that help with managing the construction process. One area, however, that is lagging in the use of BIM for automated or semi-automated processes such as estimating. Literature has explored some reasons for this lack of adoption of BIM for estimating as issues with the user trusting the model’s accuracy when that model is created by someone else when using a federated model approach. In order to enhance user confidence of BIM results with automated processes two areas were examined: (1) the use of historic data to create a reliability model based on risk and financial impact of systems and (2) examining factors of project delivery that influence the use of BIM. This paper discusses a two part survey that examined the project delivery system and various other factors as to how they relate to the user’s confidence in the accuracy of a model. Results indicate that personal relationships are more influential than contractual obligations. Finally, findings of the survey that identify common trends of respondents in terms of setting up a project delivery to maximize the utilization of BIM are included.

Among Information and Communication Technologies (ICT) developed in the past decades—and successfully applied to Construction—is Building Information Modeling (BIM). One possible use of BIM models is Phase Planning (4D modeling), i.e., the integration of schedule with 3D building components of the BIM model. In addition, there is the growth in the use of: (1) technologies, such as augmented-reality equipment, to bring BIM models to the field; (2) sensor networks to feedback data about the daily progress of construction work on-site. However, the connection between 4D models, and real-world data from sensors on the construction site, to promote integration between design and construction (among other possible applications) is still in its infancy. The question addressed by this research is: how to use simulation as a link between 4D BIM models and a network of sensors on-site (off-site)? Simulation would be considered as a set of interlinked models of different construction processes, which should evolve in time based on (partial) data received from sensors. In that context, the objective of this preliminary work is to study and validate the level of detail in one construction process model, necessary to incorporate one specific type of sensor, and to quantify, even if indirectly, the amount of progression in construction work on the field. Given the availability of the ProModel software, the present research aimed to develop different models of the same construction process, with different levels of details, to draw conclusion that could be extrapolated to other processes.

Cross-domain analytical techniques have made the prediction of outcomes in building design more accurate. Yet, many decisions are based on rules of thumb and previous experiences, and not on documented evidence. That results in inaccurate predictions and a difference between predicted and actual building performance. This article aims to reduce the occurrence of such errors using a combination of data mining and semantic modelling techniques, by deploying these technologies in a use case, for which sensor data is collected. The results present a semantic building data graph enriched with discovered motifs and association rules in observed properties. We conclude that the combination of semantic modelling and data mining techniques can contribute to creating a repository of building data for design decision support.

Information about historic buildings is extensive and fundamental for maintenance, preservation, and restoration purposes. However, a common problem is lack of standardization and documentation updating. This work aims to gather 3D BIM model of historic buildings with their knowledge-base through a formal ontology. A terrestrial laser scanner was used to collect geometrical data. The resulted point cloud was delimited by Regions of Interest (ROI) then downsized and segmented. The selected case study is the Ballroom, part of the Pampulha Architectural Ensemble designed by the renowned architect Oscar Niemeyer. This building, located in Belo Horizonte, Brazil, has a unique, sinuous and irregular shape, recently listed as World Heritage site by UNESCO, rising its documentation importance both locally and worldwide. The CIDOC-CRM (International Committee for Documentation—Conceptual Reference Model) and FRBRoo (Functional Requirements for Bibliographic Records—object oriented) is the source for create the building ontology, later connected to the model. The proposed methodology shows that linking geometric and semantic database into a BIM environment can improve heritage documentation.

Building Information Modelling (BIM) is gaining popularity worldwide as a system of collaboration and data management for the AEC sectors. However, the usefulness of BIM has largely been seen in the design and construction phases, rather than in post-construction—for example in facilities management or occupancy. As the concept of BIM has matured, there has been increasing interest in applying these concepts and technologies to heritage buildings (HBIM), despite some fundamental differences: heritage buildings usually have a long history of use, re-use and alteration; their management is often related to conservation rather than occupancy; and they are often a social and community resource. Therefore, HBIM is faced with a different set of stakeholders to ‘standard BIM’, which leads us to question the optimistic perceptions of its usefulness when BIM is applied to a historic built environment context. We investigate this question by thinking about how we can characterise HBIM, and what sort of information will give us further insights. Using published case studies as a source of secondary data, we have collected information about specific characteristics, which we analyse and use to discuss the uptake of HBIM, the purpose of HBIM and the role of stakeholders. We conclude that there needs to be a significant change in perception of HBIM by academics and technicians, before it is likely to be adopted by practitioners in the heritage sector.

Bridges are one of the most important elements of the sustainable transportation infrastructure network that require significant care and consideration. Aging and deterioration are two main complications in their operation and maintenance that require precise data and efficient technologies to improve the quality of their lifecycle management. Intelligent transportation systems (ITS) have been altering the infrastructure management process by converting it into an automated process to capture, store, analyze, and manage the data. While the data have helped the management process, the issues of heterogeneity of the data and non-interoperable databases are still challenges for fully integrated management of the infrastructure. Thus, there is a crucial need for an integrated database that can help in consolidation of data management. Building Information Modeling (BIM) is one of the recent technologies that its benefits have motivated its utilization in the transportation infrastructure, and their specific use for bridges is known as Bridge Information Modeling (BrIM). Currently bridges are being inspected biannually and only structural data are being recorded for their assessment. This paper suggests the inclusion of traffic data in lifecycle management of bridges and introduces ITS as a great source of data, and BrIM as a great visual database that can help in enhancing the integration and management of databases. Fusion of ITS data with BrIM can provide many benefits for efficient operation and management of bridges that eventually improves the quality of facility management and helps as a reliable tool for decision making and budget allocation. In this paper, BIM and ITS capabilities have been discussed and finally a framework has been suggested to illuminate the dataflow process.

Distributed ledger technologies (DLTs) including blockchain are increasingly being investigated as a potential solution to address many of the challenges hindering the construction industry’s performance such as collaboration, information sharing and intellectual property rights. Existing studies addressing blockchain applications within construction and the built environment have ignored the interrelation of social and technological dimensions. To address this gap, this paper proposes a multi-dimensional emergent framework for DLT adoption within the construction sector. The framework was developed following a focus group discussion and took a socio-technical systems approach that encompasses three dimensions: political, social and technical. The framework was overlaid with an extensive set of construction-related challenges and opportunities and identified a number of associated agents across the dimensions. The structured and inter-connected dimensions provided by the framework can be used by field researchers as a point of departure to investigate a range of research questions from political, social or technical perspectives.

The objective of this paper is to propose an ontology capable of supporting a structured coordination of spatial-temporal conflicts in highway projects plans. For many highway agencies, there are different functional groups in charge of capital projects planning, safety, design and construction, maintenance and rehabilitation, and short-term operational tasks. However, many of these functional groups tend to have a “siloed” approach to planning. Integrated planning is therefore challenged by the existence of multiple incompatible legacy systems and the lack of a standardized knowledge representation format for planned highway projects information. Current literature and existing formal representations fail to address the level of information coverage and depth to support the integrated planning of highway projects. Accordingly, this study proposes an ontology-enabled knowledge representation which allows relevant planned projects information and inter-project conflicts to be processed in a standard computer interpretable manner. Ontology development was done through the analysis of project attributes of more than 30 highway agencies, review of existing ontologies, and interviews with team leads of different functional groups of highway agencies. The proposed representation was validated via logical consistency checks and competency questions evaluations in the Protégé environment. Future work will aim to employ this ontology to capture and implement tacit integrated projects planning knowledge for improved decision support.

In recent years, Building Information Modelling (BIM) has been pushing forwards the digitalization of global AEC industries continuously. Developing countries with low computerized level, such as China, still use CAD drawings as delivery in building project. It is significant to transform architecture drawings to BIM models in a cost-efficient way. Current researches on 3D reconstruction of architecture drawings are restricted by accuracy and automation level. In this paper, an automated layer classification method is proposed as pretreatment in transforming CAD to BIM models. It analyses the content in each layer of a drawing and classifies the layer into a specific category. Detailed methods to find out grid text layer, dimension layer, window and door layer and wall layer are presented in the paper. The approach is tested using 70 sample drawings. The average accuracy degree of classification is around 95%. Based on layer classification, the existed recognition algorithms could have better performance since obstructs are removed, and the detection method of section drawings can be optimized.

Each construction project goes through the cycle of different phases such as feasibility studies, engineering design, bid, construction, commissioning, and operations and maintenance. Within these phases, the 3D models and the project schedules have different levels of development (LODs) ranging from summarized to detailed operational information. These LODs affect the development of 4D simulation and result in ill-defined LOD of the 4D models. For example, applying 4D simulation in rehabilitation projects requires special attention to the operational constraints imposed by the need for the continuity of service of the facility. For this purpose, the 4D simulation should be applied at several LODs in order to capture the potential issues in the rehabilitation plan. The objective of this paper is to provide a guideline for defining 4D-LODs for the simulation of major capital construction projects based on the needs and available information. This guideline can provide a handy reference for the project personnel and help reducing the project cost.

A building design must satisfy diverse requirements including building codes, owner’s specifications, design guidelines, and project requirements. In addition, there is a growing need for an automated design evaluation process involving intelligent checking and reporting capabilities that addresses the inefficiency and error-prone nature of the current manual checking practice. To leverage the automated rule checking procedure, we need to overcome two existing key challenges, which are the inherent complexity of rules and the impracticability of checking methods. To address these challenges, this research proposes a node-based visual language approach integrated with the emerging open standard LegalRuleML, which allows the flexibility in defining and executing design rules in a machine-readable and implementable format. The approach effectively facilitates the entire rule-checking process including the rule interpretation from natural language-based requirements to machine-readable forms, rule categorization, rule parameterization, and checking execution with a BIM model. The LegalRuleML-based visual programming language approach for rule checking will help automatically and iteratively evaluate the quality and defects of information conveyed in a given building model interactively as an essential part of design process.

This paper presents a framework in which a building spatial design optimisation toolbox and a building information modelling environment are coupled. The coupling is used in a case study to investigate the possible challenges that hamper the interaction between a designer and an optimisation method within a BIM environment. The following challenges are identified: Accessibility of optimisation methods; Discrepancies in design representations; And, data transfer between BIM models. Moreover, the study provides insights for the application of optimisation in BIM.

Model View Definition (MVD) is developed as a subset of the IFC schema to define BIM data exchangeBIM data exchange requirements of the architecture, engineering, construction, and facility management industries. Several domains such as the Precast/Pre-stressed Concrete Industry, the American Concrete Industry (ACI), the American Industry of Steel Construction (AISC), and the U.S. Federal Highway Administration (Brim MVD) have defined or are currently defining model views for formally representing their BIM data exchange requirements and assisting their exchange processes using the neutral data format, IFC. However, even though several domain industries involve the same or similar sets of data exchange requirements for their MVDs, a lack of a proper approach for reusing existing MVDs results in that a data exchange process of new MVD including the same entities, attributes, and relationships of other MVDs contains inconsistent and heterogeneous sets of data exchange requirements. For accelerating the consistent MVD development reusing previous efforts and the interoperable BIM data exchangeBIM data exchange environment, this paper involves the investigation of existing MVDs and their module-based definition processes to identify the current problems in MVD development regarding reusability and contains the discussion of the promising method for utilizing predefined MVDs for new MVD development.

Building Information Modelling is a well-known acronym in the construction industry. BIM process is more than modelling buildings, and it provides the opportunity to drive efficiency and effectiveness to the information management of build projects. Accordingly, Building Information Models (BIMs), typically known as semantic three-dimensional parametric models, are fast becoming the comprehensive information source in Architecture, Engineering and Construction (AEC), and Facility Management (FM). The use of BIM in existing buildings has been hampered by the challenges and limitations surrounding the available technologies. The most popular and commonly used approach for generating models is to manually generate 3D artefacts utilizing point measurements extracted from range-based technologies (typically 3D laser scanning). In the recent past, several studies have been carried out to make the retro t BIM development process as effective and efficient as possible by developing different methods for mapping 3D models using Point Cloud Data (PCD) as the main source of information. However, an appropriate fully generated parametric model is still some way away. In this paper, we review the-state-of-the-art to address the research gap and challenges involved in generating parametric models before outlining the proposal of our approach. In this research, we employ Semantic Web technologies to capture parametric models. Elements are first recognized in PCD, and corresponding geometric information extracted from PCD are then tagged with Universally Unique Identifiers (UUIDs). Tags are then linked with the generated Resource Description Framework (RDF) data for each element. The core and challenging part of this research is the standardization process where RDF as a serialization is translated to Industry Foundation Classes (IFC) as a data model. The generated IFC format is then utilized to capture corresponding models. The primary results are very promising and should be of interest to the modelling of all kinds of building components, particularly historical building information modelling (HBIM).

BIM coordination is an iterative process that requires an accurate roadmap to adequately manage the exchange of information, overcome communication barriers, improve the decision-making environment and guarantee a successful and collaborative work throughout the project’s lifecycle. Although the actual coordination practice satisfies the requirement of routing the whole systems in a proper way, it presents a lack of sequential, constructability, operation and maintenance issues. In order to contribute to the BIM coordination process knowledge, this paper introduces a coordination methodology that is based on the sequential approach and includes O&M (Operation and Maintenance) criteria. Regarding the previous idea, the project information should be organized in a coordination matrix that adds accessibility, functionality and installation requirements to each discipline. This proposal guarantees that the maintenance criteria and physical constraints are consistently meet, preserving a continuous flow and identifying wastes, delays, rework and cost overruns from the first stages of the buildings lifecycle. The suggested methodology aims to generate a more efficient coordination process which ensures that all efforts are headed in the right direction. As a result, the coordinated model will become the As-Built one.

In this paper, we propose an ontology improving the use of Building Information Modelling (BIM) models as a virtual interactive environment (IVE) generator. The result is not only the ability to create a bidirectional link between the informed 3D database and the virtual reality application, but to automatically generate object-specific functions and capabilities according to their taxonomy. We present the results based on the Risk-Hunting training application. In this context, the notions of weight, object handles and, scheduling of the construction are essential for the immersion of the future trainee and educational success.

The digital era of construction has enabled new types of decision support for all phases of the building lifecycle. New capabilities to support the management of end-to-end service operations are emerging due to the outputs of building information modelling. Previous research has identified how the application of systems engineering activities in construction can inform the development of new methods and processes to better support a facility’s life cycle. However, gaps remain in holistic systems approaches relative to how data is structured, reused and managed through-life. The paper discusses systems engineering management activities and reviews the related literature, examining the significance of these concepts in different sectors of construction. The paper identifies gaps in collaborative and progressive modelling methodologies and identifies the main challenges that industry face in adopting a systems mindset when implementing BIM on complex projects.

Few construction companies apply the available lean tools and processes in an integrated manner when managing design. Additionally, various lean design management -tools and -processes have each their own strengths and optimal phases in project when to apply them. Earlier approaches in lean design management have not explicitly included level of detail of BIM-models in connection with planning methods in an appropriate manner. For example, the Last Planner System (LPS) is a planning and control system that uses collaborative social methods to get task dependencies and commitments from project stakeholders, but it does not provide any guidance what those tasks should be in a BIM-based process. On the other hand, location-based methods such as Location-based Management System and takt planning have provided guidance for scheduling production by using (LPS). Thus, by combining information from various sources we were able to define a location-based design management process using the concept of level of detail that can be integrated with LPS. The level of detail definition must start from the end-user of the information in each stage of the construction project. The model was co-created and validated in focus group meetings with design and construction companies. In future research we will run case-studies to test the model in real-life settings.

Today, collaborative environment method is of with widespread use among project stakeholders. They benefit project planning in a variety of ways, including by enabling team members to build stronger relationships, enhance communication, and perform efficient planning, to name several. The collaboration occurs in sessions that immerse stakeholders in an environment commonly referred to as a BIM roomBIM room —a shared space that enables project stakeholders, such as architects, general contractors, structural and MEP trades, and other specialized knowledge actors, to physically or virtually meet and to establish constant presence. The BIM room is a medium for stakeholders (BIM-room participants) to more accurately and efficiently make informed decisions on end to end construction problems. This project is aimed at investigating the use of information technology as a mediating mechanism to facilitate sharing meanings of expressions and to assist stakeholders in effectively finding relevant information that connects to their intent in the BIM-room. This research proposes the creation and implementation of a cognitive assistant to project stakeholders: BIMbot. The BIMbot is an agent that will have the ability to simulate a conversation or a messaging exchange with a present actor. From the actor-BIM-bot exchange and having an order, command, or request, BIMbot will carry common functions for the actors within the BIM roomBIM room like retrieve the current version of family-objects of the BIM; load, filter, and view section(s) of interest; automate object placement; etc. BIMbot is designed to produce significantly more efficient interaction of collaborative meetings in the BIM room.

The increased affordability of mobile devices, wider network coverage, and better mobile applications have changed the ways communication and information transfer take place in the construction industry in both developed and developing countries. While considerable research has been conducted on the extent of usage of mobile information and communication technologies (mobile ICT) and development of prototype applications in the context of construction projects, less attention has been paid on examining the perceptions of construction management (CM) professionals regarding implications of using mobile ICT. The present study identified different ways in which the use of mobile ICT translates into better productivity in construction projects. A questionnaire survey conducted across the Indian construction industry revealed that the use of mobile ICT improves construction productivity due to four factors: (1) improved communication and information flow, (2) better project execution, (3) improved access to data, and (4) proper defect management. While attributes related to communication and access to information received high rankings, the respondents perceived that the use of mobile ICT has low positive influence on attributes such as cost savings, speed of construction, sustainability, and construction errors.

A large number of construction workers are struggling with high stress associated with their perilous job sites. Excessive occupational stressOccupational Stress can cause serious job difficulties by negatively impacting workers’ productivity, safety, and health. The first step to decrease the adverse outcomes of this work-related stress is to measure workers’ stress and detect the factors causing stress among workers. Various self-assessment instruments (e.g., a stress assessment questionnaire) have been used to assess workers’ perceived stress. However, these methods are compromised by several drawbacks that limit their use in the field. Firstly, these methods interrupt workers ongoing tasks. Secondly, these methods are subject to a high degree of bias, which can lead to inconsistent results. The authors’ earlier work attempted to address the limitations of these subjective methods by applying different machine learning methods (e.g., Supervised Learning algorithms) to identify the pattern of workers’ brain waves that is acquired from a wearable Electroencephalography (EEG) device, while exposed to different stressors. This research thus attempts to improve the stress recognition accuracy of the previous algorithms by developing an EEG-based stress recognition framework by applying two Deep Learning Neural Networks (DNN) structures: a convolutional deep learning neural network (deep CNN) and a Fully Connected Deep Neural Network. Results of the optimum DNN configuration yielded a maximum of 86.62% accuracy using EEG signals in recognizing workers’ stress, which is at least six percent more accurate when compared with previous handcraft feature-based stress recognition methods. Detecting workers’ stress with a high accuracy in the field will lead to enhancing workers’ safety, productivity, and health by early detection and mitigation of stressors at construction sites.

Due to the labor-intensive nature of construction tasks, a large number of construction workers frequently suffer from excessive muscle fatigue. Workers’ muscle fatigue can adversely affect their productivity, safety, and well-being. Several attempts have been made to assess workers’ fatigue using subjective methods (e.g., fatigue questionnaire). Despite, the success of subjective methods in assessing workers’ fatigue in a long period, these methods have limited utility on construction sites. For instance, these methods interrupt workers’ ongoing tasks. These methods are also subject to high biases. To address these issues, this study aims to examine the feasibility of a wearable Electromyography (EMG) sensor to measure the electrical impulses produced by workers’ muscles as a means to continuously evaluate workers muscle fatigue without interfering with their ongoing tasks. EMG signals were acquired from eight subjects while lifting a concrete block using their upper limbs (i.e., elbow and shoulder muscles). As the first step, filtering methods (e.g., bandpass filter, rolling filter, and Hampel filter) were applied to reduce EMG signal artifacts. After removing signal artifacts, to examine the potential of EMG in measuring workers’ muscle fatigue, various EMG signal metrics were calculated in time domain (e.g., Signal Mean Absolute Value (MAV) and Root Mean Square (RMS)) and frequency domain (e.g., Median Frequency (MDF) and Mean Frequency (MEF)). Subjects’ perceived muscle exertion (Borg CR-10 scale) was used as a baseline to compare the muscle exertion identified by EMG signals. Results show a significant difference in EMG parameters while subjects were exerting different fatigue levels. Results confirm the feasibility of the wearable EMG to evaluate workers’ muscle fatigue as means for assessing their physical stress on construction sites.

The importance of knowledge transfer or mentoring as a way to pass tacit knowledge (experience) across generations is discussed widely. Within project management this tends to rely on proximity and mutual exchange. The sender/receiver approaches used to transfer learning from one project to another is inhibited by the context of the projects, and the lack of time, which may obscure its relevance or purpose. There is concern that the knowledge captured in the minds of senior project managers is not being passed on to the next generation. Conversely it may be that much of the knowledge senior project managers have is obsolete or has been superseded by new methods and systems. This study used a grounded theory approach when interviewing 25 construction project managers from Australia on the management of project risk. Experience accumulated over time was considered by almost all interviewees to be the most important way of accumulating knowledge. Methods such as lessons learnt and close off reports are poorly used; most tacit knowledge is transferred through mentoring with very limited use of technology in this process. Changing construction technology did not concern the PMs as they perceived their job as managing processes and their role being flexible enough to adapt to change. From an industry perspective this lack of concern with the sharing of tacit knowledge and the lack of effective systems to capture it is going to be detrimental for its future. Project managers tended to still rely on traditional and the often poorly utilized methods such as lessons learnt and mentoring to capture this knowledge. Using this information, the study examines the key issues around knowledge management in project organizations and possible avenues for capturing tacit knowledge. Tacit knowledge will potentially be lost unless better systems are developed. This paper questions how Building Information Modelling, IT systems and the more visually based techniques such as pod casting, 3D photography, time-lapse cameras, web-based methods can to be used to accumulate and enable more effective knowledge transfer. The conclusion derived is that experience accumulated to generate tacit knowledge is essential for the successful management of future projects.

The paper investigates the possibility to extract meaningful information out of natural language design conversation. This meaningful information, referred in this paper as features, represents possible design changes and solutions discussed during collaborative design sessions. Without relying on user input and without disrupting the natural course of the conversations, we envision an automatic implementation of these changes and solutions into a parametric model. The aim of such a system is to allow for an automatic design space exploration without interrupting the design sessions. In this direction, the paper employs mixed research methods which make use of quantitative and qualitative analysis. The results obtained indicate the possibility of extracting structured information to perform changes in various parametric models automatically. The paper also provides discussions around specific limitations, such as unclear precedents due to multimodality input.

Labor intensive and hazardous nature of the construction activities plays an important role on the increase of the amount of accidents and fatalities on sites. One of the most important sources of fatalities occurring on construction sites is falls-from-height (FFH). Despite the various efforts for the solution over decades, the yearly statistics still indicate high amount of fatalities and severe injuries due to FFH accidents on construction sites. Medical literature emphasize that the time passed after the accident is a critical factor for avoiding preventable deaths and permanent disabilities of trauma patients. The objective of this study is to timely detect FFH accidents on construction sites by using a wearable device and to provide a real-time notification to the emergency medical team (EMT) leveraging Internet-of-Things (IoT). This is expected to maintain the earliest possible medical intervention on site in order to help reducing fatal and severe consequences of FFH accidents for construction workers. Test results of the system evaluation show that the fall is detected correctly and the alert message is sent to the prescribed addresses with 100% sensitivity. The system has shown a good accuracy for true detection of the fall height with an overall error rate of 10.8%. Another metric which shows the detection of the disconnected network time of the system has been surveyed and the results are accurate with an overall error rate of 3.16%.

Using augmented reality in construction applications can be a beginning of a new era in the construction industry. This advanced technology has the potential to provide significant benefits to construction companies. Since it is a relatively new technology, the application areas in the construction industry are rather limited. Parallel to the development of augmented reality, it is envisaged that applications will be grow up in the construction sector besides automotive, advertising, food, media, film and many other sectors in the near future. Therefore, it is very important for the construction companies to adapt this technology as fast as possible in order not to lose the competitive advantage in the future. In this study, an augmented reality system is developed for facilitating construction site activities. The system enables managers, engineers and construction workers to follow each step of the construction activities that they are responsible for. Users can access information on training materials and construction methods related to the activities. Thus, the risk of making mistakes in site activities will be minimized. Using smart glasses, the system is tested for steel fixing and brick wall construction. The developed system has the potential to improve the quality and productivity of construction site activities and therefore, provide significant contributions to the construction industry.

Computer-aided compliance checking is always a challenge in the Architecture, Engineering, and Construction (AEC) domain. In recent years, semantic compliance checking has gained a lot of attention. As the critical ingredient of the checking system, rule information needs to be extracted from regulatory texts and be formalized into machine-readable format. This paper proposed a semantic frame-based information extraction method with a focus on domain semantics and lexical semantics. The extraction process is characterized by the enrichment of lexical semantic frames and the mapping with the domain semantic framework. Natural language processing (NLP) and machine learning (ML) techniques were used to implement the extraction mechanism. The preliminary experiment shows a promising performance when extracting rule information from Indian Utility Accommodation Policy.

A large number of different forms of energy consumption information are generated during facility management. In addition, due to the uncertain and ambiguous external and internal environment of construction project, it is an important issue in energy consumption for operation staff to query required information efficiently. Moreover, implementations of BIM technologyBIM technology can provide visualization and integrated information models for FM. In view of the above two aspects, this paper introduces ontology as the modeling approach for information exchange and put forward a semantic retrieval method based on ontology for building energy management. Then this paper realizes the integration between ontology based semantic retrieval system and energy consumption information under BIM environment. In the case study, this paper constructs a domain ontology of energy consumption and then conducts retrieval expansion based on this information model, and the discussion of example provides support for further research.

In recent years, Building Information Modelling (BIM) has been attracting increasing research interest for construction project risk management. However, very few studies exist that explore how to manage and visualise risk information within BIM environment. To overcome this gap, this paper introduces a method that establishes an active link between risk data and BIM, and illustrates and tests the proposed linkage approach by using two case studies to gain a practical understanding on the existing technical limitations and future research opportunities. The first case describes the presentation of risk information as visual objects in a 3D BIM of a highway project in Finland. The second case discusses potential of integrating and visualising risk information into 4D BIM of a footbridge in the UK. Results show the proposed linkage approach could facilitate better communication of risks within multi-disciplinary team; understanding of exact locations of risks, and transparency of risk communication and information management.

The complexity of multi-disciplinary design increasingly relies on the use of digital media to support design team interactions to communicate and understand the design. Digital media are often employed in design process to facilitate team interactions by allowing the team members to visualize and virtually walk through digital information. Hence, it is assumed that these spaces facilitate activities such as authoring, visualizing and sharing design information, as well as establishing mutual understanding of design content among team members. However, detailed understanding of how the design team interact to communicate and understand design information and how specific features of the digital media support activities and actions of the team during architectural design meetings within the context of practice appear to be limited. This study seeks to understand how the design team interact in digitally mediated spaces to communicate and understand design information and how salient features of the digital space mediate activities that emerge during collaborative design task. This paper describes initial analysis of design team activities in digitally mediated design meetings in an architectural design office in UK. The main empirical video recording of de-sign team meetings is ongoing. Initial results reveal that members in design teams accomplish task through sharing of information, description and explanation of design details, evaluation and prediction of alternative solutions, decision making, as well authoring, visualisation and navigation of design data. The paper concludes that design teams interact differently across varying digital media and associated data set and that task performance appears to be higher in digital spaces with varying features and rich data set.

Homeowners are often frustrated in trying to understand and control the use of energy within the home especially in tracking monthly usage and the impact of a change in habit on their bills. Recent advances in computing power and sensing technologies required to implement a smart home energy management system mean small, low price and sustainable devices are available for wider adoption. But how ready are homeowners to allow these devices into their homes to collect personal data? This study attempted to understand users’ perceptions and requirements of smart home systems in order that these may be more readily integrated into new and existing homes. A quantitative approach using self-administered questionnaires was distributed to a random selection of respondents falling within the sample population of households who have access to the internet at home within the Republic of South Africa. Conclusions are that homeowners need to be aware that if they do not implement smart home technology to improve their home management, they will in all likelihood end up paying more or even facing resource shortages due to the inefficiencies of the current methodologies used for managing their homes.

During the design of a new hospital, many different stakeholders are involved. These types of complex projects require more knowledge than any single individual possesses and in this context, it is necessary for all involved stakeholders to understand, participate, communicate, and collaborate with each other to obtain a high-quality outcome. This paper presents a collaborative design system, which support these creative and shared design processes. The presented system, Virtual Collaborative Design Environment (ViCoDE), features a seamless integration of a multi-touch table and several immersive VR-systems that support interactive and collaborative design work. The system has been evaluated during two studies in a real-world context of designing new healthcare environments (e.g. operating theaters). The results show that involved stakeholders better understand, participate, communicate, and collaborate with each other and that the multi-touch table and VR-system complement each other by facilitating different design spaces—both collaborative, as well as individual.

Construction is one of the leading industries in terms of workplace accidents. Safety training provides workers and professionals with tools to actively prevent these accidents. However, previous research has highlighted deficiencies in current safety training methods. Virtual Reality (VR) and Augmented Reality (AR) technologies have been employed to address some of the limitations associated with traditional training methods. While these technologies enable users to safely experience the complex nature of construction sites, they deliver unrealistic computer-generated simulations of the environment. Panoramic augmented reality presents a novel alternative that addresses some of the challenges present in VR and AR techniques in visualizing safety-related information in real construction sites. A pilot study was conducted to assesses the use of this technology as a safety training method for fall hazards. This study describes the development of the prototype training platform, the generation of training materials, and the findings of usability testing performed with university students. The results indicated that the technology was viewed favorably by participants, as the augmentations provided a simple and easy method to learn fall hazard-related information. Using the platform, participants an average 52% of the hazards presented. Participants also indicated that several aspects of the platform required improvement such as image quality, safety information displayed, and user interface interactions.

Due to increased affordability of mobile devices, better network coverage, and availability of a wide range of mobile applications, the use of mobile information and communication technologies (mobile ICT) has increased significantly in construction projects. While considerable research on both positive and negative implications of using mobile ICT has been conducted in different industries and social contexts, relatively few studies have examined the perception of construction management (CM) professionals. A questionnaire survey conducted across the Indian construction industry revealed that the use of mobile ICT could impede construction productivity due to factors such as: (1) pressure to remain accessible outside the work hours, (2) temptation to check it frequently, (3) adverse effects on work-life balance, (4) compulsion to work outside the normal work hours, (5) massive amount of information, (6) distraction, (7) less time to respond to changes, (8) loss of productive time due to personal internet usage, (9) adverse effects on health of the users, and (10) frequent drawing changes. Since potential applications of mobile ICT in construction projects present enormous opportunities for CM professionals, these issues need to be addressed through user awareness, training, and organizational policies.

Efficient construction management is highly depending on respective persons in charge and their ability to steer the inherently complex flow of information. Communication among stakeholders is crucial to improve construction process management, which is usually managed by means of paper-based documents in most of construction sites. To improve on-time delivery of projects and automate construction management, the mobile application—AR4Construction was developed. It integrates technologies such as BIM and AR with Location-based Management System. This application aims to improve productivity, collaboration between project participants as well to provide tailored information to the user. This paper describes concept, framework and functionalities of the AR4C application as well as testing and validation phase.

The relatively low cost and intuitive user interface of modern virtual reality devices offer many possibilities for it to be adopted in various industry. One characteristic that is offered by virtual reality is its ability to enhance user’s perception by making the user immersed in the virtual world. As such, the system has a potential to be used in the Architecture, Engineering, and Construction (AEC) industry, especially during the design and pre-construction phase. Some AEC firms, including architects and general contractors, had implemented this technology into their projects. However, there is little known on how the firms integrated the technology. Previous researches have been studying the impact of this technology but did not analyze the workflow of its implementation. Therefore, the novelty of this study is in the analysis of the workflow. Semi-structured interviews were conducted on AEC firm to develop the workflow and identify several challenges in VR integration into project. The study found that most AEC firms utilize VR technology mostly for building walkthrough. There are several software solutions that were used to build the walkthrough. Depending on the complexity and time constraints, the AEC firms utilize either a one-click solution or develop the walk-through in-house. The study found that latest software solutions allow for quick deployment of VR for visualization purpose. However, AEC firms still must develop their own solution for some other purposes such as model annotation and multi-user environment.

Over the years, information and communication technologies (ICT) have advanced significantly to where their applications in the construction industry have improved the efficiency of projects to a large extent. To continuously thrive in the information and technology-driven industry, it is imperative for construction companies to modify their mode of operations to embrace new technology, methods, and processes to influence the performance and efficiency of construction projects positively. Augmented Reality (AR) as a new and emerging technology generates several opportunities for enhancing traditional methods through the integration of AR technologies in the architecture, engineering, construction, and operations (AECO) industry. However, AR technologies are yet to become prevalent in the AECO industry. While AR has a great potential of impacting the construction process, there has been insufficient research on the identification of specific areas for the integration of AR in all phases of construction projects. The purpose of this paper is to offer construction professionals and researchers an account of the possible implementation of AR technologies in each stage of construction projects. The study provides construction professionals the latest research trends and developments in the application of AR, thus helping in the advancement towards significant implementation in the industry for the improvement of construction processes. The paper describes work performed in different construction stages and presents the potential benefits of AR implementation. Finally, recommendations for future research are discussed.

Collaborative virtual reality (VR), such as room-based or CAVE-type systems, has demonstrated benefits in engaging teams in the shared design exploration. Though much research explores how virtual reality may be affecting and contributing to the quality of the team discussion for making design decisions, evidence of how this technology becomes used and adopted in practical settings remains limited. Studies from other engineering and manufacture domains consistently report on practical, behavioral and organizational challenges and more often, resistance to introducing innovative technologies and processes. This study examines how technology adopters experience virtual reality, and explores the factors determining the extent of its implementation as an innovative practice. Drawing on the concept of technological frames, we examine how collaborative VR may introduce a non-trivial process change in an organization before it can potentially become an everyday practice. A large portable VR display system was set up in the central office of a large infrastructure project over a period of one year. During the latter half of a second study we did not observe the extensive uptake and use that we and the technology sponsors within the project anticipated. To understand the reasons, we use three technological frames that allows us to examine the technology adoption and organizational change: (i) nature of technology, to understand users’ view of the technology; (ii) technology strategy, to understand users’ role-based views of the motivations and incentives for technology adoption within an organization, and (iii) technology in use, to understand how intended users view the technology use on a daily basis.

Today, building information models (BIM) are developed independently among participating project stakeholders, often using independent technology platforms. Integrating the information these models convey into one standalone system results in substantial challenges. It hinders the stakeholders’ use of a shared and common platform, thereby restricting access to a common data environment (CDE). These problems lead to inefficiencies in managing the information exchange process among the actors throughout a project’s lifecycle. Cloud computing has emerged as a new model for hosting and delivering services over the internet. This model has rapidly altered the methods by which information technology is used to meet today’s demand for economically efficient, powerful, and ubiquitously available computer resources. The model promises a technology transformation across the highly interconnected business environments of the architecture, engineering, and construction (AEC) industry. Integrating Cloud computing and BIM technologies is the next generation of BIM development and will further pervade the adoption of BIM in the AEC industry, thereby incorporating new forms of collaboration amongst project stakeholders. Cloud-BIM implementation overcomes the natural limitations of standalone models in multiple ways. Benefits include reducing up-front investments in computer resources, lowering operating and maintenance costs through on-demand service allocation, enabling rapid scalability of computing, and enhancing and facilitating rapid access, to name several benefits. Cloud-BIM models enable distributed and highly intensive data transactions among project actors; however, a new way of operating and transacting, they bring with them challenges related to security management. For instance, data redundancy occurs when multiple instances of the same data exist, and it leads to problems of inconsistency (i.e., identical fields having different or multiple values) where an update is not reflected in all fields. A Cloud-BIM model provides a central access point to the project actors, safeguards data and promotes data consistency by helping to avoid redundant data and promote positive types of data redundancy. Another major challenge is the data breach that involves leaks of information not intended for public release. Data breach is the result of application vulnerabilities, human error, and/or poor security practices. The most common types of security challenges in cloud computing are addressed by this research.

The terms maintainability and maintenance are interrelated and often perceived to be difficult to distinguish from each other. Maintainability refers to the measures and actions taken during the design phase of a product in order to assure that the equipment and the system to which it belongs, can be easily maintained at minimum downtime and cost. On the other hand, maintenance refers to the measures and action taken during the operation phase in order to keep the components at the desired operational condition. The variance between the designers’ and facility managers’ priorities concerning maintainability creates a gap between the design and operation phases. Maintainability is not often considered in design nor is it a priority for designers. Designers consider maintenance access to be one of the least important factors related to maintenance. However, design-related maintainability issues such as maintenance access problems make maintenance activities impractical if not impossible in building operation, and increase the life cycle costs of facilities. These issues can be detected in the design phase if an appropriate tool is available, and can prevent maintenance-related problems in the operation phase. This research proposes a system that can be used alongside BIM and that can bridge the gap between the design and post-construction phases if deployed in the design phase.

Modular coordination in building construction has become increasingly popular, particularly in Northern Europe and North America. Modular construction in Canada gained considerable attention over the last decade due to its positive impact on project constraints, safety, and preventing construction and demolition waste. However, the modular construction industry still adopts the same administrative procedures designed for the conventional construction industry even though the features of modular and conventional construction are different in terms of construction processes and methods. Due to this trend, ambiguities in administrative documents are widely occurred and are one of the main causes to generate conflict, disputes, and claims between owners and modular suppliers as general contractors. As a first step in the on-going research to overcome this challenge, the research team focuses on investigating the contents and structures of the current contracts, which are one of major confusion sources in modular construction, in order to mitigate and/or eliminate the ambiguities in the contracts based on the considering the features of modular construction processes and methods. In this respect, this paper presents a conceptual framework, which is: (1) to classify the major ambiguities in conventional and modular construction contracts; (2) to identify the similarities and differences between Canadian contract documents and benchmark countries. We use text mining to find top terms, including terms with high TF in each document, and high TF-IDF terms, which specifically occur in one document and not others then, we detect manually the three standard contracts and compare them with the output of literature review to identify the major issues that are common.

This paper reports on an industry-academia collaboration for integrating construction and engineering analyses into a graduate-level architecture design studio, including the developed workflow and curriculum, and lessons learned from the students’ and instructors’ experiences. The studio program pursues two learning goals namely implementing multi-variate analyses to develop a sustainable design concept as well as practicing collaboration and communication inside an interdisciplinary team. The results of this paper are mostly useful for students and new professionals in the AEC field who want to take most advantage of the emerging data-driven built environments and adopt a new mindset that supports the integration of construction information into the design process. Specifically, the outcomes of the design studio effort are summarized in the following three categories: (1) the development of a generalized and standard workflow for implementing parametric, computational, and performance-based design and construction approach that assists project teams to create design concepts, evaluate their design performance, and visualize the results, (2) the establishment of a framework for evaluating the quality of design process and collaboration in an integrated design team, and (3) the creation of visual programming methods and tools and design/construction software applications for systematic design programs’ analysis and data visualization/interpretation for knowledge-based decision making (this work is in progress).

European Energy Performance of Building Directive (EPBD) defined a target as all new constructed buildings within the EU region must be a zero-energy building by the end of 2020. Furthermore, all European countries must ensure the minimum comfort threshold in energy calculations. Reducing energy consumption and improving indoor comfort, including visual and thermal comfort, can contribute to economic benefits. However, the main problem is the exitance of conflicts among visual comfort, thermal comfort, energy consumption and life cycle cost. To solve the abovementioned problem and to fulfil the EPBD’s target, this study aims to apply an integration between BIM, optimization and Analytical Hierarchy Process as a multi-criteria decision-making method on an office building in Sweden. Accordingly, 3 types of windows and 5 types of external wall, ground floor and external roof constructions were specified as optimization variables. The combination between the optimization variables generated 375 design alternatives. The performance of all 375 design alternatives were evaluated with respect to visual comfort, thermal comfort, energy consumption and life cycle cost. Later, AHP was used to find a trade-off design alternative. The results show that the combination between window type 1, external wall type 5, ground floor type 1 and external roof type 5 is the trade-off design alternative. Furthermore, the results show the integration enables to solve the abovementioned conflicts and to fulfil the EPBD’s target.

Available data about asset condition and performances can be conveyed into different Key Performance Indicators (KPIs). Many KPIs measuring technical, functional and economic/financial asset performances can be found in literature. Nevertheless, they are often strictly related to a specific scope, thus they provide an incomplete depiction of the whole assets performances. The objective of this research is to provide facility managers and asset owners with an easy instrument to prioritize maintenance. In order to reduce costs related to its use, the instrument, developed in the form of a Decision Support System (DSS), is based on existing and reliable performances metrics and leverages new technologies like Building Information Modelling (BIM). Accordingly, the Facility Condition Index (FCI) is combined with the D index, a KPI related to the age of building components, developed by the authors. The joint use of the FCI and the D index, allows facility managers to make more conscious decisions. The proposed DSS helps in the definition of the best maintenance plan, providing a ranking of building components which require more urgent maintenance interventions. Although the DSS should be tested measuring its ability to preserve buildings and their performances on a long term, the first results are positive, as confirmed by the application to a case study on an office building in Italy. Moreover, the usability of the instrument has been appreciated by the users in a medium size Italian company.

The concepts of structural behavior analysis and optimization have started to be combined in the latest decades with an increasing trend also due to the need of often meeting performance targets, high structural complexity and costs. Nonetheless, existing approaches tackled this issue mainly in the domain of static calculations or referring to a specific type of optimization (e.g., size, topology or geometry). A new methodology is proposed to systematically perform different types of analysis (e.g., linear and nonlinear), by exploiting the Autodesk Robot Structural Analysis API through MATLAB. This approach involves the adoption of ActiveX technologies for the manipulation of COM (Component Object Model) objects in the MATLAB environment. A real-world example of linear dynamic modal analysis is also presented and a synthetic diagnostic of the structure is conducted based on the displacements resulting from the calculation.

Although various BIM capability and maturity models have been developed to meet different BIM capability/maturity assessment purposes, there has not been a model which is broadly used and commonly accepeted in the literature. A Reference Model for BIM Capability Assessment (BIM-CAREM) was developed based on the meta-model of ISO/IEC 33000 to be used for assessing BIM capability levels of AEC/FM processes. This paper aims to compare the components of BIM-CAREM with the assessment questions of the identified models from the literature. Moreover, data collected from a previously performed case study was used to carry out self-assessments by using these models. Then, these assessment results were compared with the findings gathered from assessments performed with BIM-CAREM. The comparison indicated that, BIM-CAREM has more detailed and specified questions for assessing BIM capability of different AEC/FM processes and has comparable assessment results to that of identified capability models.

This paper describes a scientific experiment carried out in the context of the AEC in France. This research is part of the digital transition in architecture, with a particular interest in BIM technology and how to integrate it into architectural design through social sciences. Indeed, the arrival of BIM technology raises both technical and human questions. The design work is changed, the amount of work is moved upstream, but above all we see new tools, new uses, and new practices without any project management method emerging. In other fields such as industry, software engineering and HMI design, we have seen the emergence of methods that focus more on the team and the user than on the process. We find Lean, continuous improvement, or agility, a family of methods that interests us here. Our research hypothesis is that inserting agile practices alongside current business practices will integrate and exploit BIM technology and other digital innovations. To do this, we identified what the problems were with BIM technologyBIM technology , and selected several agile practices highlighting communication, group cohesion and customer needs identification to address them. Thus, we carry out experiments in which we test, analyze and adapt these agile practices to architectural design. This paper then describes a pedagogical experiment conducted with Master 2 students at the École Nationale Supérieure d’Architecture of Nancy in France. In a workshop, the students had to carry out a BIM project, while they used the agile practices that we had adapted: the design matrix, the micro poker, and the stand-up meeting. In addition to these three practices, we took the opportunity to try agile overseeing using what we call a stand-up meeting. The objective is to validate the synergy of these practices while ensuring that they respond to our communication, group cohesion and customer needs integration issues. This experiment takes place over one week and will serve as a basis for us to prepare experiments in a professional context.

Design review is the process of evaluating a design against its requirements to verify the performance of the design and identify issues before construction takes place. The cited methods for automating the design review process are either based on proprietary, domain-specific or hard-coded rule-based representations, which may be successful in their particular implementations, but they have the drawbacks of being costly to sustain, inflexible to change, lack generalized framework of rules and regulations modeling that can adapt to various engineering design realms, and thus don’t support an open neutral standard. They are often referred to as ‘Black Box’ approaches. This study proposes a new comprehensive framework that minimizes the shortcomings of the cited methods. Building regulations for example, are legal documents written and authorized by people to be interpreted and applied by professionals. They are barely precise as formal logic. Engineers can read those documents and translate them into scientific notations and software applications. They can extract any information they need, reason about it, and apply it at various levels of precision. How these extraction and application are carried out is a critical component of automating design review process. The primary project goal is to address this issue by focusing on the development of a Generalized Adaptive Framework (GAF) for an open standard [based on Industry Foundation Classes (IFC)] that enables automating the design review processes to attain design efficiency and cost-effectiveness. The objectives of this paper include: (a) the conceptual and theoretical development of a framework that is adaptive to the target domain and supports an open standard for transforming the written design regulations and rules into a computable model, and (b) defining the different modules needed for the automation of the design review process.

This paper presents an integrated simulation-based methodology for considering the effects of weather on formwork removal times. An expert tool for estimating formwork removal times and weather data with high resolution are integrated into a discrete-event simulation model containing a process model of in situ concrete wall operations. In addition, operational measures (denoted as curing strategies) and their ability to shield concrete curing against various weather conditions are also studied. From the simulation results, it can be concluded that weather conditions and curing strategies may have a significant influence of construction duration. The proposed simulation-based approach facilitates systematic analysis of formwork removal times and curing strategies under various climatic conditions when planning concrete works.

Communication of building project designs to stakeholders is important for successful implementation, but it is often difficult to get feedback from the future occupants of buildings. Yet, there is a growing trend in development of visualization tools to enhance participation of the public by effectively providing building information to stakeholders. However, we lack research evaluating the effectiveness of different building model visualization tools, and their performance with gathering feedback from future building occupants. This study compares the effectiveness of three visualization tools—360° panorama, virtual reality and augmented reality applications—with eliciting feedback from future occupants of a Living Building Challenge project at the Georgia Tech campus compared to more conventional 2D visualizations. The effectiveness comparison was conducted across the seven performance categories defined by the Living Building certification program. The results indicated that the visualization tools had significant differences in communicating information in the Equity, Energy, Health and Happiness, Place, and Water performance areas. This study provides a quantitative perspective on the effectiveness of visualization technologies across the virtuality continuum, and has implications for pre-occupancy surveys by exploring new feedback mechanisms that encourage users to participate in building design.

This study implements Building Information Modeling (BIM) for conducting a simulation design involving the technologies of Fire Dynamics Simulator (FDS) and Agent Based Modeling (ABM) to foresee the relationship between evacuators’ mortality and building layout design. The goals of this paper are to investigate (1) how to predict the building’s Available Safe Egress Time (ASET) by using FDS software; (2) how to reflect the evacuation behavior within an ABM simulation; (3) how would the Required Safe Egress Time (RSET) be impacted by the building properties, fire properties, and human behavior. By making a comparison between ASET and RSET, the optimized building layout design that reflects minimum RSET can be chosen. And finally, BIM serves as the environment to visualize the results of (1) the hazardous zones that reflected in the fire simulation; (2) the effective escape routes that are recommended by the evacuation scenario. These results can be used to improve fire safety management for both fire education and construction design. Following the results, this paper concludes with a description of challenges associated with building fire and agent-based evacuation simulations that would arise from developing a BIM-based framework for highly occupied building fires.

Built environment plays an essential role in shaping the physical, physiological, and psychological human well-being given the fact that we spend more than ¾ of our times indoors. Various studies that investigated the impact of architecture on human health and well-being provided evidences on the influence of architecture with faster recovery in hospitals, better learning in schools, and more productivity in offices under variant configurations of architectural design features. This paper studied the impact of architectural design features (e.g., presence/size of windows, level of natural light and nature view) on human experience in buildings using a mobile eye-tracking solution to capture the subjects’ attention toward various design features. The subjects were exposed to two distinct virtual environments designed with polarizing features, and were instructed to conduct a series of navigational and informational tasks. The eye-tracking results showed that subjects were more focused and had higher attention level in the positively configured virtual environment. The result of the informational task, where the subjects were asked to recall an array of words they just saw in the virtual environment, showed that subjects performed better (i.e., recalled more words) and experienced positive recall (i.e., recalled more positive words) in the positively configured environment.

To improve organizational decision-making process in construction industry, a framework of a multi-objective and multi-criteria based approach has been developed to integrate results from Life-Cycle Analysis (LCA), Life-Cycle Cost Analysis (LCC) and dynamic analysis for multi-storey industrialized timber structure. Two Building Information Modelling (BIM)-based 3D structural models based on different horizontal stabilization and floor systems will be analyzed to reduce both climate impact, material and production costs and enhance structural dynamic response of the floor system. Moreover, sensitivity of the optimal design will also be analyzed to validate the design. The multi-objective and multi-criteria based LCA-LCC framework analyzing the environmental, economic, and dynamic performances will support decision making for different design in the early phases of a project, where various alternatives can be created and evaluated. The proposed integrated model may become a promising tool for the building designers and decision makers in industrialized timber construction.

4D BIM assures more detailed costs and error control, whilst also improving scheduling and coordination. It relies on interoperability and high levels of collaboration, which have increased the value of collective competencies. In addition to the competencies, the collaboration group internal influences and subordination must be considered as well. While the knowledge and competencies of each and every individual team member are important, BIM allows the team to use the entire set of collective knowledge, skills and competencies, which are the key feature for advanced digital management of the AEC project. Such management requires a successful implementation and efficient use of 4D or nD BIM. This study proposes to summarize collaboration personae of AEC project collaborative groups, and to associate the collective knowledge and competencies to 4D BIM uses4D BIM uses . Further, it will be completed with interviews on current 4D practices with BIM professionals. Moreover, through this research, we continue to progress towards a new 4D collective decision-making support proposition.

In the design process the main challenge of the designer is to generate an efficient project resulting from different objectives and associated criteria. These objectives are often conflicting and they are related to programmatic requirements, aesthetic, structural, and cost or energy performance. Multi-objective optimization (MOO) can guide the designer towards efficient design solutions. Parametric tools enable integrating MOO techniques and algorithms in 3D modeling environment. They allow the designers to take decisions during the design process. While the optimization tools are considering physical objectives (building energy, performance and daylighting, form generation, structural optimization …) the current applications often lack the evaluation of performance as perceived by occupants, e.g. based on post-occupancy evaluation studies. POE is defined as the evaluation of the building performance by users. Implementing POE in a parametric environment can improve the design and in particular the reorganization of an interior layout space design.

Increased demand for traffic puts the Aviation industry in front of multiple challenges. Traditional airport design matrices do not cope properly with the evolution of design requirements and project participants’ needs, especially in a multidisciplinary context that requires high skilling. In this setting, Architects are rulers of the terminal and lead managers of Project Information. These are generated and managed through Social processes who leverage the joint use of knowledge to fulfill project requirements. Often the need for reliable project information is not understood by project participants and project clients, therefore causing reworks, overtimes and an overall increase in project cost. Innovative project management methodologies based on social aspects are needed to implement common practices and support collaboration, shared design, problem-solving. The target is producing consistent Project Information. In this exploratory paper, way lay down the foundation and research background for a proposed research that aims to re-align people, process, and technology in Airport Design. A lean design methodology proposal is built on the project sociotechnical system to maximize project value for passengers, airlines, and airport management companies.

4D modeling integrates 3D model with project time schedule to provide virtual simulation for identifying spatio-temporal problems earlier in construction projects. However, constructing a 4D model takes a significant amount of time and is prone to man-made errors due to its manual steps and repetitive nature. Therefore, in this study, a model based two-phase method is developed to facilitate linking 3D model with the schedule by automating the cumbersome steps. In the first phase, 4D Task IDs are created and assigned automatically to the model elements using a pattern that depends on their properties. In the second phase, using these IDs, the method generates a task ID list for scheduling and the search sets for simulation in order to map the model elements with the schedule tasks automatically, according to matching IDs. Hence, using shared IDs enhances the communication between 4D modeling tools. The efficiency of the method was tested with a well-known office building model constructed in Revit. The schedule was completed in Microsoft Project and 4D simulation is performed in Navisworks. The automated steps offered by the method were coded in Dynamo add-in of Revit. The analysis result showed that the developed method generated a 4D model in a shorter time compared to the manually performed one.

This paper presents a mobile platform that autonomously collects 3D thermal/coloured data and obtains a raw 3D thermal model of the insides of buildings. This platform has been developed with two objectives, the first of which is to develop a new hybrid 3D colour/thermal laser scanner system that will provide 3D thermal points of the 360 × 180 space. The second consists of making the earlier thermal scanner autonomous, such that the best scanner positions required to completely cover the scene can be carried out. This entails proposing an original and efficient new next-best-thermal-scan algorithm (NBTS). After collecting, aligning and mixing 3D thermal data from different positions of the scene, a complete thermal point cloud of the scene is generated. The output of the autonomous system is a raw 3D thermal model of a scene, which can be further processed. The system has been tested in the insides of buildings under occlusion conditions, providing promising results.

Globally, the construction industry is a key contributor to national economies including Singapore’s. However, the industry is a serial productivity underperformer. The literature argues that mechanization, automation and use of advanced technologies help improve construction productivity, but real-world case studies are limited in number. This paper presents a case study of the introduction of mechanization to improve the level of construction productivity in Singapore. The case study under investigation was the production/fabrication of steel gratings, the conventional process of which depends heavily on labor with few workers present on site. The majority of these workers are migrant workers, which contributes to a significant social concern in Singapore. The case study organization introduced a more advanced laser cutting machine to the process. The project team observed the process of using the laser cutting machine, and quantitative and qualitative data were obtained. The researchers observed the processes, both conventional and updated, and recorded the data on both methods. The quantitative data were comparatively analyzed to investigate the relative quality, efficiency and productivity of the two methods. The data revealed that the mechanization process achieved a productivity improvement (or savings) in man-days of at least 78%. Material wastage was reduced, and moreover, less reliance was placed on migrant workers, which helped to mitigate the social concerns created by the influx of foreign workers to Singapore. The findings also shed some light on the positive influence of government incentives to improve the industry’s productivity.

One of the potential benefits of using Building Information Modeling (BIM) for Facility Management (FM) targets enhanced tradespeople performance, facilitated by efficient document management, equipment localization and visualization, and integration of building asset data. However, a major bottleneck towards achieving such a benefit is the lack of BIM. In addition, the owners or the facility managers do not want to invest in generating BIM because manually creating BIM for existing buildings is costly, time-consuming, and requires additional labors with specific skills to maintain. Therefore, the authors aim to build an automated Mechanical, Electrical, and Plumbing (MEP) BIM reconstruction framework that uses 2D building mechanical drawings. In this paper, the authors proposed a new method of generating 3D mechanical objects based on all available information in drawings, such as equipment schedules, symbols and spatial and topological relations amongst objects. The results have shown that the proposed approach could reconstruct more than 70% of the mechanical components among duct, VAV, AHU, FCU, BCU, diffuser, register, and sensor. Even though the authors were not able to achieve 100% success, it was shown that the proposed method reduced the time for generating the mechanical components and it is a major step towards the development of a BIM to support FM tasks associated with MEP components.

Symmetry is a fundamental phenomenon in not only nature and science but also cities and architectures. Architectural symmetry detection (ASD) from 3D urban point clouds is an essential step in understanding the architectures as well as creating a semantic city/building information model (CIM/BIM) to enable various applications for a smart and resilient future. However, manual segmentation and recognition of 3D urban point clouds are too time-consuming, tedious, and costly, and automatic ASD is very challenging. This paper presents a derivative-free optimization (DFO) approach for automatic ASD from 3D urban point clouds. In this paper, we formulate the problem of ASD as a nonlinear optimization problem by extending the mathematical definition of geometric symmetry with architectural styles. We develop a ‘divide-and-detect’ process to detect the symmetry hierarchy based on the formulation and apply the state-of-the-art DFO algorithms. A pilot study was conducted on a case of the rooftop of a neoclassical building. The proposed approach detected the global reflection from 1.4 million points in 23.5 s, and the whole symmetry hierarchy of reflections in about ten minutes. The detected symmetry hierarchy was applied to a regularity-based rooftop modeling method. The contribution of this paper is twofold. First, this paper exposes the problem of ASD to many mathematical methods through an innovative problem formulation. Secondly, the proposed DFO approach is accurate, efficient, and capable of processing large-scale 3D urban point clouds for semantic CIMs/BIMs.

For the safety and serviceability of aging bridges, it is important to understand how the current conditions of the bridges will deteriorate in the future as time goes by. The primary goal of this research is to analyze sequential patterns of damages on the bridge elements that are normally recorded through site inspections and managed by the bridge management system (BMS). To achieve the research goal, the research team first discovered a number of bridge clusters with distinguished characteristics by using a data clustering algorithm. Sequential pattern mining was then utilized to extract types and sequences of damages on bridge elements frequently seen in each cluster. The data used for the analyses was collected from BMS managed by the Korea Institute of Civil Engineering and Building Technology. This BMS includes the general, structural, traffic, and weather information of 6773 bridges (i.e., the total of 127 attributes) and contains 834,815 site inspection records of the bridge elements. A preliminary test was performed by using a dataset of 1542 Pre-Stressed Concrete I-shape type bridges for the validation purpose. The results of this study showed application potential to estimating future condition changes of the bridges based on the past inspection records for preventive bridge maintenance.

Prompt emergency detection and response in indoor environments is a significant issue due to the difficulties in detecting indoor emergency eventsEmergency event. However, current indoor monitoring tasks are mainly carried out by manual observations of occupants and such human-dependent methods generally have limitations in taking actions against emergency events. Many researchers have made much effort to develop automated indoor monitoring systems using wearable sensing device technologies and computer vision. While these methods have various advantages, there still remain challenges to be addressed for detecting indoor emergency events; for instance, wearable sensors need to be attached to a human body and occlusions make it hard to recognize the emergencies. To overcome those deficiencies, this paper proposes a sound event recognition (SER)-based indoor event classification (e.g., emergency and normal event) method with a convolutional neural network (CNN). The research consists of four main steps. First, the sound types of indoor events are determined as four emergency sounds (explosion, gunshot, glass break, and scream) and one normal sound (sleeping). Second, 692 sound data of identified events are collected from online sound data sharing services, and the preprocessing is performed. Third, SER model is developed through CNN algorithm with log-scaled mel-spectrogram features. Finally, model performance is evaluated using 5-fold cross validation. The experimental results showed that the sounds caused by indoor emergency events could be automatically recognized by the proposed method with F-score of 77.32%, which demonstrates its applicability for real emergency situations.

A variety of applications require detailed geometric information about a building’s hull. In particular, windows are of high interest in this context. However, common 3D models only roughly outline existing buildings’ geometrical outward appearance. The field of application is, thus, severely limited by now. In this paper, we propose an approach to the automatic detection of windows in facade images complementing common building models by information derived from detected windows to enable new opportunities and widen the spectrum of applications. Therefore, we apply a soft cascaded classifier to identify windows in patches of facade images. Moreover, a postprocessing is applied to the detections. We initially refine their dimensions and alignment on the facade. From these we infer so far non-detected windows. With an overall detection rate of 95 and 97% precision our proposed detection system yields sufficient results for complementing existing 3D building models by information of the detected windows.

Over the past decades, several bridges have collapsed causing many losses. To keep bridges in a fully functional condition, a good maintenance system should be implemented. Although several new techniques have been developed and used recently to detect bridge defects, annual visual inspection remains the main approach for detecting surface defects, such as cracks. An Unmanned Aerial Vehicle (UAV), equipped with Light Detection and Ranging (LiDAR) scanner, can fly to reach all parts of a large structure. This equipment is capable of scanning the inaccessible surfaces of the bridges at a closer distance, which improves safety, accuracy, and efficiency. Using his method in structural inspection is attracting attention in research, and recent advancements have been made to automate and optimize the path planning of the UAV. However, the difference between the criticality levels of sections is not reflected in these methods. This paper proposes a path planning method of LiDAR-equipped UAV for bridge inspection using Genetic Algorithm (GA) and A*A* to solve Traveling Salesman Problem (TSP) considering the potential locations of surface defects such as cracks. The objective is minimizing time-of-flight to achieve acceptable visibility.

Manual visual crack detection and classification for inspection of civil infrastructure is time-consuming and labor-intensive. Many automatic crack detection and classification algorithms have, thus, been developed in the past decade, several of which achieved acceptable performance results for specific applications and using large datasets for training. However, developing training data for automatic crack classification is not an easy task. It requires a large dataset in terms of quantity and variability, as well as well-trained professionals to label the dataset. Hence, there is a need for efficient ways to develop well-labeled datasets that could not only reduce human effort, but also adapt to diverse inspection contexts for improved classification performance. To address this need, this paper proposes a data retrieval and annotation method to automatically retrieve and label crack images from the Web. The dataset can be used as pseudo training data for supervised machine learning-based crack classification algorithms. The proposed method incrementally retrieves and labels crack images. A weak Convolutional Neural Network classifier first learns from a limited set of Web images, and then acts as a machine annotator and further labels a larger size of data. The proposed method was able to retrieve and label a set of images with 95% labeling recall, which shows that the proposed approach is promising.

Existing automated building code checking systems/software highly rely on human interpretation of the code. Different methods have been proposed and implemented to make building codes automatically analyzable and interpretable by computers. These methods have achieved different levels of automation in rule formalization, but they all require some level of human involvement to capture the compliance checking-related semantic information in the natural language building code sentences. For example, the state-of-the art approaches require human annotation or require human effort to develop annotation and/or extraction rules. To reduce the human effort in automated code interpretation, this paper proposes a machine learning-based approach to automatically label the semantic roles in building code sentences for supporting code compliance checking. The proposed method consists of three primary elements: (1) capturing the syntactic and semantic features of the building code sentences using natural language processing techniques; (2) adapting out-of-domain training data to the task at hand based on data similarity; and (3) performing semantic role labeling using a conditional random field (CRF) model. The proposed approach was tested on a corpus of annotated text from the International Building Code, and achieved promising global precision.

Project requirements are wishes and expectations of the client toward the design, construction, and other project management processes. The project definition is typically specified in a contract package including a contract document and many other related documents such as drawings, specifications, and government codes. Project definition determination is critical to the success of a project. Due to the lack of efficient tools for requirement processing, the current practices regarding project scoping still heavily rely on a manual basis which is tedious, time-consuming, and error-prone. This study aims to fill that gap by developing an automated method for identifying requirement texts from contractual documents. The study employed Naïve Bayes to train a classification model that can be used to separate requirement statements from non-requirement statements. An experiment was conducted on a manually labeled dataset of 1191 statements. The results revealed that the developed requirement detection model achieves a promising accuracy of over 90%.

Significant progress has been made towards BIM-based automated rule-checking systems. There are multiple approaches that show varying potentials as crucial components for open and practical rule checking systems. However, in the current state, we are not yet quite there as they are still several barriers that prevent the needed shift from proof-of-concept to the real-world implementation. This paper reviews various language-based rule checking systems that have been proposed and assesses their potentials and gaps that need to be overcome for them to become practical. It introduces metrics of eleven criteria to analyze various approaches to assess their readiness for the real-world implementations. The criteria cover a wide range of aspects including language expressiveness, ease of use to define a rule, openness, level of maturity, and performance. These criteria help to identify gaps that currently exist that need to be overcome to allow a leap from a proof-of-concept to the real-world implementation. From the assessment, it is obvious that no one single approach is currently capable of covering the entire spectrum of requirements for automated rule-checking systems. The assessment also shows that the possibilities of combining two or more approaches may accelerate the realization of an open and practical language-driven automated rule checking system.

Current studies reveal the exceptional advantages of high-efficiency onsite information management for facilitating the design/building progress of construction projects. In particular, the prevailing methods of construction field reporting still primarily rely on manual on-site documentation of project information. Fortunately, state of the art computerized technologies provides solutions with great potential for boosting the efficiency of gathering and managing on-site information for field reporting. Providing on-demand access to such information in real-time requires an autonomous method for localizing and tracking (i.e. calculating the position and orientation) of a construction filed reporter on job site. This, in fact, will reduce both working time and efforts for providing on-demand access to project information. Mobile devices such as smartphones/tablets can be utilized to enable the on-site personnel to manage the project information in a portable fashion while adopting cloud technology for instant online access. In this paper, we proposed a method for on-site localization that can estimate and track the position and orientation of a hand-held device in a near real-time manner. The developed method is infrastructure-independent and marker-less. The proposed method mainly consists of mapping, localization and alignment modules. Initially, a video stream is acquired using the built-in camera of the mobile device scanning the target building. A 3D point cloud is then reconstructed from the acquired video data. Afterward, the localization algorithm outputs the location/orientation of the queried images using feature-based matching with the base 3D point cloud map generated earlier. Finally, global localization of frames is estimated by using the alignment parameters of the 3D point cloud with a Geo-referenced BIM model to transform the localized frames to the global reference. The proposed solution enables the field reporter to access, retrieve, save and edit the project information more efficiently on the construction site.

Collecting load tickets is an example of an antiquated practice that puts inspectors in harm’s way either adjacent to traffic, in close proximity to moving or backing equipment, or at times requires climbing onto trucks to reach tickets. Technology exists to collect this information electronically allowing for safer, efficient inspection methods. Departments of Transportation are charged with inspecting an increasing work load with a diminishing number of inspection staff. Recently, doing more with less has led to the prioritization of inspection activities and resulted in less collection of data and visual inspection on projects. Technology advancements are available to improve data collection and provide for more efficient inspection. Using GPS and GIS technology tied into electronic scale report-out systems, a fleet tracking system traces haul routes, reports travel time and tonnage, and even assists contractors with equipment matching and balancing. Data from this system coupled with other technologies remote monitoring of temperature, intelligent compaction, and network enabled cameras provide an opportunity to enhance inspection and increase construction inspection productivity all the while enriching detail of project records. Challenges to the system include connectivity, interoperability, and usability. The contribution of this paper is to provide a framework in which to combine these commercially available technologies into a multi-faceted, enhanced inspection approach.

Despite of the increased level of automation in vehicles, the detection of pavement distress, such as cracks and potholes, is mostly performed manually. We propose a methodology for automated pavement distress detection based on computer vision. Thereby, images obtained by cameras installed in common passenger vehicles are analyzed in real time, resulting in cost savings and a reduced amount of stored data. For this purpose, the wavelet transform was implemented on Graphics Processing UnitsGraphics processing units (GPU). In addition, median filtering and top-hat transform were also implemented on GPU to enable real-time noise removal and correction of non-uniform background illumination. To distinguish between surface types, we incorporated textural features into our methodology and deep learning was utilized to determine the distress type (cracks, potholes or patches). Results obtained by different vehicles were aggregated to improve the reliability of the methodology. Case studies were conducted for validation and tests achieved promising results.

In 2015, the construction had the highest rate of fatalities among all industries in the United States. Unsafe operation of construction equipment is one of the main causes of fatal incidents. Operation, management and interactions between construction equipment and construction crews should be thoroughly regulated to minimize the risk of fatal incidents on job sites. While use of most traditional construction equipment is regulated, the construction industry has struggled with regulating new, innovative and smart equipment such as Unmanned Aerial Vehicles (UAVs) that have recently been introduced to construction job sites. In this paper, collision avoidance and spatial safety theories in construction are discussed. The bases of these theories are extended to UAV operation in order to establish the first known theory on safe use and operation of UAVs in construction. Also, basic principles of UAV flights are discussed. By applying the basic principles of UAV flights and construction spatial safety theories, a UAV flight simulator in construction environments has been developed in Unity game engine. The flight simulator is designed for UAV pilots, construction managers and safety managers, and enables users to fly a UAV within a simulated environment extracted from a BIM model. This UAV flight simulator is tested in a case study of a building currently under construction. This simulator can be used to assess UAV pilots’ capabilities, test the risks of UAV flights in any construction environment, and UAV safe flight path planning.

Bridge inspection is a critical task that is needed to monitor bridge quality and serviceability. Previous studies indicate that road network and bridges in the U.S. are not of high quality and poorly maintained for decades, and the current manual inspection routine is expensive, time-consuming, hazardous, and subjective. Moreover, current Bridge Management Systems (BMS) may not coordinate management of all phases of the bridge life cycle. Also, the dispersed inspection data drastically reduces the effectiveness of the system. Therefore, there is a need to identify cost-efficient and productive ways to inspect and manage our bridges. The objective of this study is to develop a novel framework for bridge inspections and management. The framework implements Bridge Information Modeling (BrIM) and Unmanned Aerial Systems (UASs) technologies in an integrated manner to solve the issues associated with current manual bridge inspection and management practice. The proposed framework was implemented using data collected from an existing bridge located in Eugene, Oregon. Different types of defects were identified automatically using computer vision algorithms from the digital images captured by the UAS. These defects were assigned to individual BrIM elements. BrIM was used as the central database to store the 3D bridge model and inspection data. The framework also enables bridge inspectors and decision makers to access the most up-to-date inspection data simultaneously by taking advantage of cloud computing technology. The proposed framework: (1) provides a systematic approach for accurately documenting the structural condition assessment data, (2) reduces the number of site visits and eliminates potential errors resulting from data transcription, and (3) enables a more efficient, cost-effective and safer bridge inspection process.

The main mission of the fire service is protecting life, assets, and natural resources from fire and other hazardous incidents. Geographic Information System (GIS) is supposed to ideally decrease the required time for dispatching first responders to the incident site, while it has some deficiencies in showing and analyzing indoor space and routing. Building Information Modeling (BIM) is a data-rich, potential source for finding the most efficient routes within a building. Researchers have developed the methods, algorithms, and platforms to make indoor navigation analysis easy and understandable for occupants. They have worked on different alternatives of indoor network analysis through a process of applying the different methods to a study model, but it has not been defined which method is more appropriate to first responders’ responsibilities. This paper reports on indoor networks analysis for first responders considering the importance of route finding in emergencies. We analyzed the similarities and differences of each method and algorithm, created an indoor network through ESRI’s Campus Viewer Tool and conducted interviews with a fire marshal and his team. Participants reviewed eight models, including the indoor network analysis model created by the researchers. Findings revealed the indoor network analyses most compatible with the 3D model, easy to read, and understood by first responders.

Construction projects are dynamic environments which are hard to monitor in real time conditions. Thus, traditional practices for productivity estimation, such as historical data analysis, do not provide enough information for decision making. This project proposes a new methodology to instrument and collect data in construction sites using embedded systems and IoT technologies. This solution is efficient in terms of energy, range, costs, and security of the data. In particular, it deals with one of the main challenges of implementing a Real Time Location System (RTLS). That is, we use an indoor technology and adapt it to the unfavorable conditions of constructions sites. The designed network is implemented in three different type of construction projects. Results show that our methodology can be used to determine the level of productivity of personnel in site and to record, analyze and rank their performance in different types of construction activities. This allows decision makers to promptly present alternatives to improve productivity, thus, achieving a positive impact in the fulfillment of the scope, schedule, budget, and quality of the projects.

In the realm of smart cities, tools for intelligent, real-time building energy management at the urban-scale are still evolving. Today, most commercial buildings have a dedicated Building Management System (BMS) to manage operations on-site efficiently; but there is no unified approach involving multiple stakeholders to manage them cooperatively in a district or urban scale. Thus, we formulate the following research question: ‘What is a feasible structure and what are the relevant components of a middleware that is easy to integrate within existing BMS/EMS and scalable for application in smart cities?’ To address this knowledge gap, this article proposes a new integrated and non-intrusive approach to cyber-physical middleware design using open-source tools. The implementation of proposed middleware in a case study building-scale project in Singapore is presented. Several features are analyzed to understand the relevance and scalability of proposed middleware as a technology enabler for smart building management in cities. The experiences and lessons learned from this project can be extrapolated to the urban-scale as more buildings are equipped with such systems. For this purpose, middleware code is also made available as open-source.

Construction machinery have long been associated with high accident rates. Mobile cranes are widely used in construction projects and represent one of the main items of machinery that contribute to a large number of construction accidents. While many of these accidents occur due to inadequate planning and a lack of foresight on the potential hazards on site, few of the mobile crane safety issues have been well addressed. This study seeks to address this problem by leveraging the use of Cyber-Physical Systems (CPS) for planning and monitoring mobile crane operations on the construction site. A framework for a CPS-based approach is developed and the key components and enabling technologies are discussed. With a focus on how the virtual interface of the CPS approach was developed and how the system provides safety assistance in mobile crane operations, the modelling process and analytical algorithms are explained in detail. The capability of enhancing bi-directional communication and coordination between virtual components and their physical representations enables CPS to change the way mobile crane planning and monitoring could be done. By enabling pro-active planning and real-time monitoring of crane operations, CPS manages to provide rich multi-modal feedback to crane operators and workers on site, and thus, helps to reduce/avoid mobile crane failures and mobile crane-related accidents.

Post-occupancy evaluation data on both building performance and occupant comfort can be useful for facility operation and management, and for workspace design but are rarely used in practice due to challenges and research gaps in data collection and analysis. We argue that with the growth of mobile and pervasive computing capabilities, future space design and building management will be based on real-time feedback loops of building performance data—qualitative and quantitative—available through the cloud, at stakeholders’ fingertips. We have developed a live, cloud-based system to begin contextualizing fragmented big data sets as evidence to support improvement of workspace management and design, and this paper presents the development process. The proposed system has three functions: data collection, processing, and reporting. A wireless sensor network collects physical environmental data which are then posted to a cloud-hosted server. A smart device-administered survey collects occupants’ perception data. Thermal comfort principles, as well as HCI (human–computer interaction) development guidelines and design principles, were followed during development of the app, which was then rigorously tested. The time-stamped survey data are synchronized with environmental data captured by relevant sensors. Pilot data collection is ongoing, as is the correlation analysis of the two data sets used to validate the process. The real-time reasoning and report generation features, supplemented with additional data, will be beneficial to space design, and to facility operation and management. This holistic system is expected to provide a powerful and practical tool for both designers and facility managers.

This paper examines how runway incursion, one of the major risks in aviation system, arise and propagate during communications and operations necessary for air traffic control. Runway incursions (RIs) refer to incorrect presences of aircraft in protected areas designated for landing and take-off of aircraft. RIs can significantly jeopardize the runway safety. Communication errors between air traffic controllers and pilots are major causes of RIs. How to quantify the probabilistic dependence between contextual factors (airport layout, time of the day, etc.) and communication errors that lead to RIs is thus important for real-time alarming and accident prevention. This study presents a Bayesian Network (BN) modeling approach with a focus on modeling the communication errors causing RIs during aircraft take-offs and how different factors contribute to the accidents according to the information from the aviation accident reports. Major findings indicate that the proposed approach can predict the accident occurrences based on the risk knowledge of anomalies captured in the BN produced by the proposed approach. In practice, the proposed approach has the potential for establishing automated and preventive safety management in aviation systems.

Tower cranes are one of the most expensive assets inside construction projects and they lead the timing of the planned activities. For this reason, assuring the efficient use of this equipment is essential for the productivity of the project. This work presents a monitoring system for tower crane productivity cycles. It uses an Inertial Measurement Unit (IMU) to calculate jib angles in real time which allows the evaluation of the crane position. In addition, a load cell system measures the lifted load by the tower crane. Data is transmitted via Long Range (LoRa) network. Data is tagged from the origin and sent to the brain, which uploads the information to the cloud. Results show that the system can be used for real time monitoring of the tower crane operation by measuring productivity cycles, average lifted load, and operation hours. This information is organized and displayed in a time series platform that generates inactivity and load alerts to construction managers within the projects.

This paper aims at describing the interface layer of a BIM-IoT prototype. The prototype addresses the gap of BIM Model Use (BMU) for energy monitoring by the integration of BIM Models with building systems’ energy consumption information in real-time. Such integration requires a BIM/Internet of Things (IoT) Interfacing due to the connection between real and virtual environments as well as context awareness demands. Also, the need for a user-centered feedback strategy concerns about the information delivery and display to enhance predictive maintenance activities and facilities managers’ decision-making over Energy Management. The BIM-IoT prototype followed the Design, Development and Evaluation (DDE) steps of the Design Science Research. A pilot implementation at an institutional building restricted to a research laboratory enabled a proof of concept and an analytical assessment of the prototype’s capacities. The existing BIM Record Model demanded changes comprising geometric and non-geometric modeling issues (e.g., assets registers) to receive sensor-based dynamic and actual information, and assure its 2D/3D views and semantic context. We observe that the BIM-IoT prototype is a feasible system to support operational strategies based on facilities managers-centered feedback. It contributes to the predictive maintenance and facilitates the comprehension of building systems status and performance. The prototype acts as an accessible and interactive option for energy consumption monitoring.

Improving building energy efficiency requires an understanding of the affecting factors and an assessment of different design and operation alternatives. In this context, accurate prediction of building energy consumption gained a lot of research attention. In recent years, a significant number of building energy consumption prediction models, with various intended uses, have been proposed. However, existing data-driven models are mostly based on outdoor weather conditions, but do not take occupant behavior into account. Towards addressing this research gap, this paper presents a hybrid machine-learning and data-mining approach to develop prediction models that learn from both real data and simulation-generated data. Real data were collected from an office building, including data about building energy consumption, outdoor weather conditions, and occupant behavior. Simulation-generated data were created through simulating an office building in EnergyPlus. A feature selection algorithm was used to determine the critical features in predicting energy consumption for office buildings. A set of regression models were then trained for predicting the hourly values of an outdoor weather-related factor and an occupant behavior-related factor based on these features. Then, an ensembler model—which takes the outputs of the outdoor weather-related factor and occupant behavior-related factor models—was trained to predict cooling energy consumption. In training the models, several machine learning algorithms—such as Gaussian Process Regression (GPR), Support Vector Regression (SVR), Artificial Neural Networks (ANN), and Linear Regression (LR)—were tested. The predicted energy consumption levels showed agreement with the actual levels. This indicates that the proposed regression models can help support decision making related to office buildings.

Architecture’s race skyward has brought with it a variety of functional innovations, one such being glass curtain wall systems. During such building’s operating life, failures of insulation systems create areas of reduced resistance to heat transfer, or thermal bridges. These failures enable energy flows that trigger unanticipated temperature changes and increased energy consumption and ultimately, damage the façade structure and cause problems to occupants. Discussion includes design and test method for rapidly identifying thermal bridges in façade systems, with minimum or no-disturbance of occupants. Research focus is set in determining if the damages are just local failures or if they are related to a poor systematic construction assembly. A non-traditional approach is adopted to survey an entire fully operational building using infrared thermography and an Unmanned Aerial Vehicle (UAV). The system is comprised of a non-contact infrared camera mounted on and operated from the UAV. It enables the registration of the emissivity of the façade materials and calculation of the thermal radiation and equivalent factors to estimate localized temperatures. The registration process yields thermal imaging results of the actual state whose temperature will be analyzed quantitatively using graphs and compared with the ASHRAE standards, retrieving the perfect state using THERM software. After evaluation of the results a statistical analysis will be performed, to inform the Architecture, Engineering, and Construction (AEC) community about the areas of most common failures for existing structures. It is expected that the results will also identify improvements for construction methods by projecting better and more efficient processes.

Global warming and energy shortage has drastically increased the necessity to reduce energy use in buildings. Improving the energy efficiency of buildings is a key step-in achieving the energy and CO2 emission targets globally. In this effort, in the presented paper, advanced modeling methods like BIM and energy simulations are conjoined with lean waste elimination concepts into a building process-centric model. Integrating building systems, processes and energy data supports decision making for retrofitting and process reengineering actions within budget constraints. The proposed approach combines existing BIM-based energy performance tools with the development of a Business Process Reengineering architecture to develop an energy efficiency optimization model. In the first direction, BIM-based energy analysis is performed to automatically assess energy performance under varying building conditions. The Lean Business Process Reengineering (LBPR) architecture describes the fundamental layers needed to achieve more energy efficient organizational environments. These layers refer to “Definition”, “Data Information”, “Analysis” and “Therapy”. As Process Performance Indicators are also augmented to the process model, the impacts of modifications through generating different process views can be compared. An optimization model employing genetic algorithms is developed in which, considering the potential budget shortage for building asset interventions, preselected lean business process scenarios feed the optimization model to investigate the optimum solutions. A pilot case that shows the practicability of the proposed methodology is presented.

Advances in data and information technologies have resulted in the availability of different types of useful data and easy accessibility. However, much of the data is not fully leveraged to gain insights for decision making due to the labor-intensive and time-consuming process of data collection and the unstructured format of data, which imposes challenges for data analytics. This paper discusses a Geographic Information Systems (GIS) based visual analytics framework for highway project performance evaluation in terms of cost and productivity. The study employs web data extraction techniques and database technologies to automatically extract data of interest from different web data sources to develop databases that contain structured data for data analytics. To merge the data from distinct sources, natural language processing techniques are also used to deal with the inconsistency of data terminology and word choices. In addition, the use of GIS technologies allows for the visualization and analysis of data collected from different locations. A case study was undertaken, which implemented part of the framework for unit price visualization, estimation, and evaluation of highway projects.

Adaptive reuse of buildings is considered a superior alternative for new construction in terms of sustainability and Circular Economy (CE). Adaptive reuse takes existing buildings that are reaching the end of their lifespan, restores them, and in some cases, changes their use. The conceptualization and execution phases of adaptive reuse projects involve the integration of emergent complex processes. In comparison to green-field construction projects, adaptive reuse projects require distinct stages, definition of interfaces, decision gates, and planning methods. Therefore, there is a need for defining better ways to identify, record, monitor, and track the project interfaces required for adaptive reuse of buildings. Interface Management (IM) systems are a potential solution for managing the project complexities in these types of projects. Using IM in adaptive reuse projects has the potential of bringing cost and time benefits during project’s execution. The present study proposes a framework for a IM in adaptive reuse projects. First, the concept of adaptive reuse and IM will be explained. Then, an ontology of interfaces for this class of projects will be defined. Finally, a discussion of how IM could be a part of a solution for adaptive reuse projects problems will be presented with a case study.

Recent efforts on automatic 3D modeling of existing buildings often result in semantically poor as-is building information models (BIMs). Such a BIM usually consists of a set of objectified surfaces characterized by the building element types they represent and 3D surface geometries. It cannot be directly used as the geometry input of building energy modeling (BEM) as the key concepts of second-level space boundaries (SBs) are missing. This paper proposes a semantic enrichment approach for automatically adding such semantic concepts inferred from the semantically poor as-is BIM. The output of this approach is a corresponding IFC BIM with second-level SBs, which can be further used by various energy simulation tools. Preliminary experimental results using a building surface model demonstrate the performance of the proposed approach.

Building stocks and infrastructures are representing the largest material stock of industrial economies. In order to minimize the use of primary resources and the dependency on imports, “Urban Mining” strategy aims to recycle these urban stocks. For enabling of higher recycling rates detailed knowledge about the composition of building stocks in needed. Recyclability is also determined through design and is depending on constructive criteria defining accessibility and separability of building components, whereby the early design-stage plays an important role. In order to optimize the recycling potential and material composition of buildings, new design-centric tools and methods are required. The so called Material Passports represent such tools, which next to the design optimization would enable circular economy in the building industry. In this paper we will present the results of funded research project BIMaterial: Process design for BIM-based, Material passport. The main aim of this research is to create a BIM-based Material Passport for the optimization of the building design regarding resources use and documentation of materials, thereby using Building Information Modelling as knowledge base for geometry and material properties and coupling to further databases for assessment of ecologic footprint and recycling potentials. Thereby a framework for modelling and methodology for semi-automated Material Passport assessment will be proposed. As the methods and structured data that would allow an automated creation of a Material Passport are still lacking, therefore the current research has an innovative character and closes a research gap in this field.

Evaluating the impact of learning from weather data, in addition to bridge data, on the performance of bridge deterioration prediction is critical for identifying the right data needed for better prediction for enhanced bridge maintenance decision making. However, the majority of the studies in the bridge domain did not consider such evaluation. For those that conducted the evaluation, their evaluation results usually varied. There is, thus, a need for re-evaluating whether the use of weather data could improve the prediction performance. However, conducting the evaluation is challenging because of class imbalance problems in the bridge domain. Therefore, prior to the evaluation, conducting data sampling to alleviate/eliminate such problems is necessary. To address these needs, this paper offers a pilot evaluation study for better evaluating the impact of learning from weather data on bridge deterioration prediction. To conduct the evaluation, a sampling method was used to deal with the data imbalance problems, and a deep neural network model was developed to predict the condition ratings of decks, superstructures, and substructures. A number of alternative sampling methods were tested and the prediction performances—with and without weather data—were compared. The preliminary experimental results indicated that: (1) the random over-sampling method outperformed the other alternatives; and (2) the change in the prediction performance after further learning from the weather data was only marginal.

Buildings are dominant contributors of global energy consumption. Enhancing building energy efficiency has long been recognized as an important way to achieve energy saving goals and sustainability targets. In response, a body of building energy performance benchmarking models and tools have been proposed during the past decades. The degree of similarity between the compared buildings is the core of the benchmarking process. However, existing benchmarking tools mainly classify buildings only based on building use types, instead of fully considering a wider range of impacting factors. To address this gap, this paper proposes a machine-learning (ML)-based model for classifying buildings—based on building characteristics, occupant behaviors, and geographical and climate features—into three energy-consumption levels: low, medium, and high. Support vector regression models are then fitted to define the predicted energy consumption for benchmarking. The proposed ML-based building energy consumption prediction model was tested on the office buildings in the commercial building energy consumption survey (CBECS) dataset. Principal component analysis (PCA) was used for data dimensionality reduction and feature extraction. Different ML algorithms were tested and compared, including Naïve Bayes (NB), support vector machines (SVM), decision trees (DT), and random forests (RF). The classification algorithms were evaluated in terms of precision and recall; the regression models were evaluated in terms of root mean square error; and the energy consumption prediction results were further compared with the prediction results by EnergyStar. The performance results indicate that, compared with EnergyStar, the proposed model can reduce the prediction error by 13%.

Occupant behavior is considered as one of the important factors that can influence the energy consumption of a building, therefore knowing occupant behavior as supporting data can help architects to design more resilient, and sustainable architecture. Employing this data in the design and construction can help with creating more efficient buildings. Simulation can help us to experiment and understand the behavior of the system using these data by creating logical, justifiable, and valid models. Recently, occupancy behavior data has been used in different simulation tools. However, most of the research focusing on indoor navigation does not consider Building Information Modeling (BIM) and its properties while making the occupancy behavior simulation. When it comes to the energy performance of the building, building model should be taken into account as it would help the design team to with a better understanding of the project. In this paper, we used a BIM-GISBIM-GIS platform, to demonstrate how the occupant tracking and behavior pattern extracted from a simulation model using stochastic data can be used as a facilitating information for the design process.

It is becoming increasingly clear that there is a gap between the expected and actual performance of buildings. A growing body of evidence suggests that the most common barrier to achieving design intent is the absence of comprehensive information during design and construction stages, leading to poor decision-making which impacts on performance and Whole Life Cost (WLC). Building Information Modelling (BIM) has the potential to facilitate a more comprehensive and accurate design approach from the early stages. A detailed and accurate model can allow designers and clients to understand the wider impacts of design changes, and to track this information through construction stages. However, dependencies between design decisions and WLC have yet to be understood. This paper is based on a project that focuses on the Private Rental Sector (PRS), which is the fastest growing new sector in the UK housing market, also known as Build-to-Rent (BTR). The study adopts a mixed method approach for the development and validation of a structured standardised process for more accurate WLC estimation through BIM. As a result, the main problems in WLC BIM management are identified, and coordinated into a reverse-engineered systematic process that uses the Integrated DEFinition (IDEF) 3 structured diagramming modelling technique, and the Industry Foundation Classes (IFC) as a basis for large dataset management. The research outputs aim to enhance BIM lifecycle management through a smart decision-making approach that is integral to the natural design development process.

Maintenance management is an essential operation that should be carried out effectively for maintaining, repairing, and rehabilitating highways and roads. It is necessary to accumulate information produced during the entire life cycle of roads in order to analyze problems and find solutions within a temporal sequence and to maintain them strategically and effectively. The primary objective of this study is to solve above problems on road maintenance and maintain the road efficiency. This paper proposed a road maintenance support system based on product data model using mobile devices. Product data models enable the exchanging and sharing of road information among those involved in road maintenance. The system consists of two use cases: in office and on site. In road administrator’s office, the system is based on two-dimensional paper-based maps and three-dimensional printed models output by a three-dimensional printer. It supports the discussion of maintenance plans and enables sharing the maintenance plan and existing inspection results by using photographs from tablet computers and smartphones in combination with radiofrequency identification (RFID) tags. The system accumulates the photographs of notes and supports referring to them on-site using RFID, QR codes, and a global navigation satellite system. This system consists of two parts: a method of indicating important inspection points on-site by using AR markers, and reference management of inspection and rehabilitation data by using RFID and QR codes. The proposed system was evaluated the usability and capability. The evaluation results indicated usability and capability on site usage.

Construction sites are dynamic and complex; they are the most vulnerable environments to natural disasters such as hurricanes. Wind-caused damage to the construction sites could cause millions of dollar losses, considerable schedule delays, and threats to both worker safety and public safety. Therefore, there is sorely a need to enhance the overall resilience of construction projects and implement resilient construction operations. However, there is a lack of research that focuses on enhancing the resilience of construction operations during the construction phase as most existing research focuses on enhancing the structural resilience of the completed buildings or infrastructures. There is a lack of holistic and systematic knowledge that ensures whole life-cycle disaster management of construction projects. To address the gap, this paper aims to develop an ontology-based semantic model of disaster resilient construction operations to formally represent and reason about the knowledge of resilient construction operations during wind disasters. This paper starts by presenting the research method, and it follows by presenting our initial modeling and validation efforts towards a formal semantic model on disaster resilient construction operations. Finally, the paper discusses our proposed framework for a knowledge-based decision support system that allows for knowledge access, classification, and transfer on disaster resilient construction operations. The model, together with its potential application of the knowledge-based system would allow construction professionals to share and transfer domain-specific knowledge on construction disaster resilience, which will eventually contribute to enhance the whole life-cycle disaster resilience of construction projects.

Asphalt mixture temperature plays an essential role in the road construction process. For high-quality asphalt, it is crucial that the compaction is performed within a certain range of the temperature, known as the compaction window. The compaction of the asphalt at a temperature outside this range would compromise the quality of the final product considerably. The compaction window is predicated on a myriad of parameters such as the type of the asphalt mix, the ambient temperature, etc. However, the operators of the road construction equipment (e.g., rollers and pavers) currently rely on their professional intuitions and experiences to develop their operational strategies. This practice can be significantly improved if the operators can be provided with the real-time information about the temperature of the asphalt mat during the construction. The available solutions for the real-time monitoring of the asphalt are limited to capturing and presenting only the surface temperature or only core temperature of the asphalt mat. Given the complex behaviour of the asphalt with relation to the mixture type and the ambient conditions, this approach cannot best represent the asphalt behaviour during the construction. This paper presents an approach for capturing the real-time asphalt behaviour using multiple sensing technologies. In this approach, the core and surface temperatures of the asphalt are captured using thermologger and linescanner, respectively. These data are then translated into 3D temperature contour plots that represent the asphalt behaviour under the construction site settings in real time. Finally, the data is presented to the equipment operator via a user interface. A prototype is developed and tested to demonstrate the feasibility of the proposed approach. The case study indicates that the presented method can improve the asphalt operation by enabling the operators to better develop their operational strategies.

Affordable computer-aided manufacturing has made possible a new category of timber structure. Components can now be intricately detailed to a high level of precision on a large scale. This approach has meant the increasing use of timber-only joints and more intelligent structural solutions that exploit the inherent qualities of the material. This study suggests that these construction parameters, enabled by computer-aided manufacturing, are advantageous when attempting to eliminate lifecycle building and construction waste. In this research existing and specifically designed low lifecycle waste construction solutions that have used computer-aided manufacturing are compared to conventional platform light timber framing. The study finds that using computer-aided manufacturing technology to fabricate advanced assemblies can lead a 67% reduction in the time required to recover building materials for reuse (versus the cost of reusing materials from traditional construction techniques). The use of a single material with integrated sophisticated jointing conditions is also seen to lead to the potential total elimination of adhesives and composite materials.

Colombia is in the process of modernizing and changing its road infrastructure and, despite the fact that in this process the government entities request the contractors elements of risk analysis and assessment, this country has a precarious risk management for infrastructure projects. This research is intended to determine the project schedule affectation due to the materialization of risks and to stablish a risk assessment methodology considering the context of the project. The proposed methodology first takes into account the quantification of the probability of occurrence of the event or risk with the Bayesian analysis and their respective networks, in order to look at the interaction of their causes and their repercussion in the final event analyzed. Subsequently, the impact of the risk on the duration of the activity is found. Finally, the risk value (P × I) is calculated using a Monte Carlo Simulation technique, obtaining as a result a value in days of possible delay that must be compared with the value that details the initial programming. The methodology is realistic since it considers any type of risk that could be presented in a project, from engineering problems, to social events. Currently, the methodology is being implemented in a real project in order to evaluate it against the progress of the same, obtaining information so that later, organizations can propose the necessary contingency measures to deal with the risks presented.

Safety performance in the construction industry has reached alarming levels and continues to be a primary source of concern to industry stakeholders. The construction industry is considered more hazardous than other major industries such as manufacturing. In the other industries, safety performance has been substantially improved and generally falls within acceptable levels. One noticeable difference between construction and other industries is that the rate of technology implementation in the other industries is significantly higher than in construction. High rates of technology implementation are expected to lead to improved safety and non-safety performance. The primary objective of the present study is to summarize the use of technology alternatives in the application of the hierarchy of controls using a preliminary, unstructured review of literature. The hierarchy of controls is a systematic method to reduce worker exposure to workplace hazards and mitigate potential safety risks on jobsites. The result of the study indicated that there are several technological controls used to mitigate workplace safety hazards during construction. Although virtual reality and building information modelling (BIM) are more effective than others in mitigating workplace safety hazards, the other technologies such as wearable sensing devices, warning systems, drones, and robotics can play significant role in protecting and/or alerting workers from potential workplace safety hazards. It is expected that the present study will help industry practitioners improve their understanding of technological controls used to mitigate workplace hazards and motivate higher levels of technology adoption in construction.

The rapid development and use of BIM in the Architecture, Engineering, Construction and Facility Management (AEC/FM) industry requires an adequate understanding of the roles and competencies that professionals should develop and maintain. Besides, as the specific processes associated with BIM remain closely linked to the nature of the activities and teams involved in each project, one can consider that the definition of roles and competencies requires a project-level discussion and alignment. This article presents the main results achieved through the BIM4VET research project. It focuses first on the matrix of responsibilities defined for BIM profiles, and presents the global approach for assessing competency maturity and further recommends training courses, thanks to a benchmark carried out by the project partners. Second, the paper describes the BIM4VET toolset developed, and its associated repository of training modules, the management of users and their maturity assessment, and further the collective decision-makingCollective decision support system intending to help practitioners collaboratively elaborating project-level responsibilities and registering for training sessions. The assessment of results is presented, through both (1) a Delphi questionnaire for achieving a sector-wide validation of roles and responsibilities, and (2) an experimental protocol involving observation of professionals using the tools.

This paper explores a pedagogical approach to teaching construction students how to plan, execute and monitor an efficient collaborative information delivery plan from the perspective of managing scope of work, time, resources and communication. This study extends the work of similar studies that tasked students with developing BIM process maps to gauge any shift in the students’ perception on their ability to map the process. In this context, students in the final year of an undergraduate construction management program participate in a team-based project to plan, execute, update and evaluate the efficiency of their collaborative information delivery plan. To plan this process, the students use references including both UK-based BIM Level 2 standards and US-based CIC BIM Project Execution Planning Guide. Through a semester-long sequence of modeling and planning activities, the students specifically aim to address the following learning objectives: (i) define and allocate project- and information delivery responsibilities; (ii) identify information workflows and respective tasks with estimated durations, and (iii) execute and update their plan to record actual tasks, durations and outcomes. Comparing the initial and executed plan would provide the students with the basis to reflect on the influence of formal planning guides on their understanding of efficient collaborative information management and delivery. In this aspect, the study contributes to the knowledge of how to pedagogically deploy industry-oriented process planning approaches for effectively teaching roles and responsibilities for engaging in interdisciplinary teams.

With the availability of online teaching tools, educators got the opportunity to create learning environments for students that are flexible and user-friendly. Though being exciting and intuitive, this opportunity comes with great responsibility, as students may be lost in online education without any face-to-face (FTF) contact. Engaging online students becomes even harder in an independent research study course, where students are expected to perform a high level of self-directed work. It is a challenge to promote an online independent study, as students need to be active, engaged, motivated, and prepared in the virtual environment. Additionally, the non-traditional nature of online students requires flexibility and interactive teaching methods to sustain collaborative and connected learning. The Construction Management (CM) Masters’ Project at Jefferson is an independent research study that serves as the culminating experience in the program, where students choose their own project to produce a comprehensive Project Manual with an oral defense presented at the end of the semester. This paper identifies best practices for delivering an online Masters’ Project course, which is engaged, collaborative, real world-based, and grounded in the liberal arts and sciences. The methodology will include creation of online learning models, assessing principles of online independent study development, and evaluating the new online Masters’ Project delivery model with a pilot group of students. Results will be used to create guidelines and assessment methods for faculty, who teach online independent study courses and who are willing to embrace the emerging online education phenomenon in construction.

The question of how to best integrate BIM into the curriculum is one of significant debate, especially at the university level. This paper presents the ongoing development of a third-year BIM integration curriculum within an Architectural Science undergraduate program, with a specific focus on a project designed to introduce students to data-driven design. This project has students create a series of massing models in Autodesk Revit, which are analyzed for both initial cost and life-cycle energy performance and these iterations guide studio project development. This paper presents the pedagogical approach developed to introduce students to advanced BIM use cases such as cost analysis and energy simulation and evaluates the first three years of integration of these topics into an architectural curriculum. From 2015 to 2017, over 300 students participated in this project, creating and evaluating over 1000 model iterations. Student feedback obtained through surveys and course evaluations demonstrates that this project is effective not only to provide students with increased BIM capabilities, but also encourage them to synthesize a broad range of data generated through simulation to refine and develop their designs.

In Brazil, undergraduate courses in architecture and urbanism under promote technologically mediated collaboration in design studio classes. The industry is incorporating BIM and has been looking for collaborative skilled employees. Teaching BIM should take into account issues related to student integration through collaborative methods. This paper presents the summary of a study to evaluate the collaborative process mediated by BIM over the past ten years in its capstone course, contemplating learning and educational strategies. Therefore, the following questions ought to be asked: Were design exercises appropriate? Was the adopted dynamics of collaboration coherent? Did the collaborative tools and standards serve the mediating function? Was collaborative training fostered? Action research is the methodology used to conduct this study. Each year, the evaluation process of the previous sequence is carried out, followed by the planning of the current one. Through the historical comparison between the course curriculum and collaboration strategies adopted over the years, there have been changes in the understanding of how to use BIM in a collaborative process for educational purposes. The two-axes collaborative integration method developed over the years of the course, where students are tested to collaborate, at the same time, in a design process and in a research process that assists the design, is an innovation that results from the evaluation cycles based on the research-action method. It was possible to conclude that the essence of teaching collaboration mediated by BIM follows the same precepts of the current BIM definition. To teach BIM, one must comprehend how the processes, policies, and technologies are related to the design teaching goals.

Building Information Modeling (BIM) offers a variety of tools to help a wide range of stakeholders in the construction industry. There has been substantial research on the advantages and challenges of implementing BIM for large-scale construction projects; however, there is a dearth of research on the benefits and challenges faced by smaller construction firms when adopting BIM. Thus, this paper focuses on the cause-and-effects of BIM adoption in the construction industry. To achieve this objective, first, a literature review covering different aspects of BIM adoption was conducted. Second, large-sized construction firms who already have implemented BIM in several of their projects were interviewed through questionnaires. Based on the findings from the interviews, a set of survey questions was prepared and distributed among all types of construction firms to identify their innovativeness and level of BIM adoption. The survey contains company and demographics, innovativeness, and BIM-specific questions. Survey results show that small-sized construction companies are indeed far behind large-sized companies in respect to BIM adoption. This paper highlights the findings from the literature review and survey. Future research will take place to dive further into the survey data results and develop a roadmap that identifies a BIM function that can be adopted easily by small-sized construction companies.

The Architecture Engineering and Construction (AEC) sector has been facing considerable challenges recently due to the scale and complexity of the projects. Mega projects are more difficult to manage in terms of decreasing cost and increasing quality and productivity. Innovative approaches have been proposed to overcome the various challenges that the AEC sector tries to address. Achieving integration and thereby a more collaborative project environment is essential in this process. Today’s key trend in successful business strategy is put as “combine and conquer” which includes innovating business models together with transforming the core engineering systems around digital. Accordingly, it has been observed that there is rapid increase in implementing Building Information Modeling (BIM) in mega projects. BIM provides significant increase in efficiency of project execution through optimizing project constraints of scope, time, cost, quality, and resources. Therefore, incentivizing all project parties to work in a collaborative fashion can be considered as an important key success factor. This study investigates the challenges and enablers of BIM implementation through a case study on Istanbul Grand Airport (IGA) Project in Turkey to provide a solid understanding of BIM applications in mega infrastructure projects

This paper provides various aspects to consider during the creation of a novel virtual learning environment (VLE) for the education of construction workers interacting with robots. First, the characteristics of existing VLEs in the construction industry, including user interface, navigation method, content, and procedure of learning were reviewed. Several drawbacks of existing environments were identified during the review. Then, the novel features of VLEs in other industries were investigated to find what can be incorporated in the VLEs for the construction industry to mitigate the drawbacks. The existing VLEs in various industries do offer novel features that can be adapted for robot-included work-site trainings and education. However, the construction industry has specific characteristics that are unique and therefore the construction industry-specific characteristics need to be considered when adapting the features of other industries’ VLEs.

Energy efficiency and Building Energy Modeling are two successful approaches to architecture, engineering, construction and operation (AECO) programs. In recent year several education initiatives focusing on buildings energy management have been carried out to provide professional profiles with specific skills in technology, architecture, engineering, economics, management and environmental science. It enables them to plan, design, evaluate or research energy supply and design strategies aimed to reduce energy consumption according to sustainability concepts. Building energy performance optimization requires an integrated design approach to explore and evaluate different strategies for building energy saving and to assist in the decision making process along the life cycle including design, operation, management and decommission phases. Moreover, BEM (Building Energy Modeling) is increasingly being included into architecture and engineering curricula, introducing new methodologies and tools for architecture design to provide interdisciplinary profiles in the professional practice. The main objective of this contribution is to report the application of BIM technologies and BEM tools into the Environmental Design Lab training course at the School of Architecture at University of Florence, where the authors are involved into a cross-disciplinary teaching program which students undertake in the fourth year of their curriculum within the 5 years degree program.