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The design of a building is a collaborative process among experts from multiple disciplines. Using Building Information Modeling (BIM), a model is developed through multiple refinement stages to satisfy various design and engineering requirements. Such refinements of geometric and semantic information are described as levels of development (LOD). Thus far, there is no method to explicitly define an LOD's requirements nor to precisely specify the uncertainties involved. Furthermore, despite the insufficient information in the early design stages, a BIM model appears precise and certain, which can lead to false assumptions and model evaluations, for example, in the case of energy efficiency calculations or structural analyses. Hence, this paper presents a multi-LOD meta-model to explicitly describe an LOD's requirements, incorporating the potential fuzziness of both, geometric and semantic information of individual elements. The explicitly defined fuzziness can be taken into account when applying simulations or analyses for assessing the performance of different building design variants. To support the continuous elaboration of a building from the conceptual to the detailed design stages, the multi-LOD model makes it possible to ensure the consistency of the geometric and semantic information as well as the topological coherence across the different LODs. The feasibility of the approach is demonstrated by its prototypical implementation as a web-server and user-interface, providing a means for managing and checking the exchange requirements both at the meta-level and for concrete building model instances. The paper is concluded with a case study of a real-world construction project that demonstrates the use of the meta-model to support model analysis and the decision-making process. [ABSTRACT FROM AUTHOR]

Abstract 3D point cloud data obtained from laser scans, images, and videos are able to provide accurate and fast records of the 3D geometries of construction-related objects. Thus, the construction industry has been using point cloud data for a variety of purposes including 3D model reconstruction, geometry quality inspection, construction progress tracking, etc. Although a number of studies have been reported on applying point cloud data for the construction industry in the recent decades, there has not been any systematic review that summaries these applications and points out the research gaps and future research directions. This paper, therefore, aims to provide a thorough review on the applications of 3D point cloud data in the construction industry and to provide recommendations on future research directions in this area. A total of 197 research papers were collected in this study through a two-fold literature search, which were published within a fifteen-year period from 2004 to 2018. Based on the collected papers, applications of 3D point cloud data in the construction industry are reviewed according to three categories including (1) 3D model reconstruction, (2) geometry quality inspection, and (3) other applications. Following the literature review, this paper discusses on the acquisition and processing of point cloud data, particularly focusing on how to properly perform data acquisition and processing to fulfill the needs of the intended construction applications. Specifically, the determination of required point cloud data quality and the determination of data acquisition parameters are discussed with regard to data acquisition, and the extraction and utilization of semantic information and the platforms for data visualization and processing are discussed with regard to data processing. Based on the review of applications and the following discussions, research gaps and future research directions are recommended including (1) application-oriented data acquisition, (2) semantic enrichment for as-is BIM, (3) geometry quality inspection in fabrication phase, and (4) real-time visualization and processing. [ABSTRACT FROM AUTHOR]

Graphical abstract Highlights • New method for generating and using BIM for energy retrofitting of old buildings. • The proposed method comprises 3 interrelated tasks: Anamnesis, Diagnosis, Therapy. • Templates help to fill in modeling gaps in the needed system identification cycle. • A variation model enables the use of templates for retrofitting design variants. • The developed framework can be reused in other domains such as bridge retrofitting. Abstract Building Information Modeling (BIM) is rapidly advancing as an efficient new approach to cooperative building design and construction. However, BIM methodology is still mainly developed and applied for new building projects. The strong societal needs to improve the quality and the overall performance of the existing building stock, especially with regard to energy use, are yet insufficiently supported by BIM. In this paper we propose a structured approach towards the creation of a building information model of an existing building and its use for the purpose of retrofitting or renovation, based on the standard IFC specification (ISO 16739). It implies a process we define as BIMification. This process undergoes two major stages: (1) Anamnesis, dedicated to the survey and collection of facts about the building, and (2) Diagnosis, dedicated to the analysis and interpretation of the collected facts to obtain the necessary understanding of the building and its performance and prepare for the retrofitting design. The paper outlines the broader research aim that triggered the development of the suggested approach and presents the overall concept and methodology, the ICT platform under implementation and the current state of the work. Discussed are also the scope of the approach, envisaged perspectives and further development efforts. [ABSTRACT FROM AUTHOR]

Abstract Product manufacturers have spent the last years improving productivity and process efficiency in order to face increasingly competitive markets. Today, the visibility of technological innovations has become essential to achieve the targeted market. It is now very difficult for a product manufacturer to reach customers without owning a website that is visible on search engine results pages. The goal of this paper is to build information channels between a company and its customers through improving both a company's content of information on the Web and its website rank on the Internet through search engine results pages. Company information and knowledge are distributed through multiple stakeholders. The problem of building information channels between a company and customers is solved through a collaborative and distributed approach, on the one hand, and is supported by decision-making tools, on the other hand. The paper proposes an engineering model for building information channels and improving the visibility of the company on the Web. Agents are used for the implementation of the approach. The proposed model and its implementation handle the requirements, constraints, functions and solutions for improving Web visibility. The prototype tool, called CAWIS (Computer Aided Web Information Sharing), examines Web visibility in real time and evaluates the performance of the proposed content of information. CAWIS allows an exploratory and open way for building information channels and improving the visibility of product manufacturers on the Web. [ABSTRACT FROM AUTHOR]

Works dealing with Scan-to-BIM have, to date, principally focused on 'structural' components such as floors, ceilings and walls (with doors and windows). But the control of new facilities and the production of their corresponding as-is BIM models requires the identification and inspection of numerous other building components and objects, e.g. MEP components, such as plugs, switches, ducts, and signs. In this paper, we present a new 6D-based (XYZ + RGB) approach that processes dense coloured 3D points provided by terrestrial laser scanners in order to recognize the aforementioned smaller objects that are commonly located on walls. This paper focuses on the recognition of objects such as sockets, switches, signs, extinguishers and others. After segmenting the point clouds corresponding to the walls of a building, a set of candidate objects are detected independently in the colour and geometric spaces, and an original consensus procedure integrates both results in order to infer recognition. Finally, the recognized object is positioned and inserted in the as-is semantically-rich 3D model, or BIM model. The assessment of the method has been carried out in simulated scenarios under virtual scanning providing high recognition rates and precise positioning results. Experimental tests in real indoors using our MoPAD (Mobile Platform for Autonomous Digitization) platform have also yielded promising results. [ABSTRACT FROM AUTHOR]

The pervasive emergence of sensing technologies for structural health monitoring (SHM) and the digitalization ubiquitous in engineering (“Industry 4.0”) pose increasing demands on information modeling concepts in civil engineering. While in building information modeling (BIM) conventional building information (such as geometry, material, or cost) can precisely be described using current modeling standards, information about SHM systems, referred to as “monitoring-related information”, cannot be fully described on a well-defined, formal basis. In this paper, a BIM-based approach towards describing monitoring-related information is proposed, using the Industry Foundation Classes (IFC), an open BIM standard facilitating the interoperability of BIM models, as a formal basis. First, possibilities and constraints of describing monitoring-related information with the IFC schema are discussed. Then, information necessary to describe SHM systems is integrated into a semantic model serving as a technology-independent metamodel. Next, the IFC schema is extended to enable BIM-based descriptions of SHM systems in compliance with IFC modeling capabilities, which is referred to as “IFC Monitor” schema. The IFC Monitor schema is verified with test software used in the official IFC certification program. For validation, a prototype SHM system is formally described using the IFC Monitor schema. The validation aims at checking if the IFC Monitor schema is capable of precisely describing monitoring-related information. As will be shown in this paper, the description of the prototype SHM system meets the requirements of a well-defined IFC model as specified in the official IFC certification program. As a result, the IFC Monitor schema proposed in this study advances BIM-based descriptions of SHM systems in association with structural systems being monitored on a well-defined, formal basis. [ABSTRACT FROM AUTHOR]

Researchers have recently devoted considerable attention to acquiring location awareness of assets. They have explored various technologies, such as video cameras, radio signal strength indicator-based sensors, and motion sensors, in the development of tracking systems. However, each system presents unique drawbacks especially when applied in complex indoor construction environments; this paper classifies them into two categories: absolute tracking and relative tracking. By understanding the nature of problems in each tracking category, this research develops a novel tracking methodology that uses knowledge of the strengths and weaknesses of various components used in the proposed tracking system. This paper presents the development of a hybrid-tracking system that integrates Bluetooth Low Energy (BLE) technology, motion sensors, and Building Information Model (BIM). The hypothesis tested through this integration was whether such knowledge-based integration could provide a method that can correct errors found in each of the used sensing technologies and thereby improve the reliability of the tracking system. Field experimental trials were conducted in a full-scale indoor construction site to assess the performance of individual components and the integrated system. The results indicated that the addition of map knowledge from a BIM model showed the capability of correcting improbable movements. Furthermore, the knowledge-based decision making process demonstrated its capability to make positive interaction by reducing the positioning errors by 42% on average. In sum, the proposed hybrid-tracking system presented a novel method to compensate for the weakness of each system component and thus achieve a more accurate and precise tracking in dynamic and complex indoor construction sites. [ABSTRACT FROM AUTHOR]

[Display omitted] The use of Building Information Modelling (BIM) models in the design, construction and operation of buildings and infrastructure is leading to a stronger focus on the quality of the models. Models may need correction, enrichment or enhancement to meet the expectations for quality and completeness, especially if models are to be taken as legal documents, for example for regulatory approval. Past work on semantic development has looked at specific scenarios such as scanned geometry or missing classification. This paper describes an innovative unified approach to the documentation of semantic expectations by actors in the AECO (Architectural, Engineering, Construction and Operations) domain and the means to put them into effect. RASE (Requirements, Applications, Selections and Exceptions) semantic mark-up is used to make both the requirements and any supporting resources both human-readable and machine-operable. Two example models from industry, a motorway bridge and a healthcare space, are used to demonstrate applying geometric, schema and classification knowledge. This knowledge is represented in a number of different styles. This extends our understanding of the nature of the knowledge found in dictionaries, classifications and development specifications, demonstrating how this knowledge can be made operable. This bridges the gap between the application of static compliance knowledge and the accurate and efficient application of correction, enrichment and enhancement knowledge. [ABSTRACT FROM AUTHOR]

The lifecycle of the built environment is governed by complex regulations, requirements and standards. Ensuring compliance against these requirements is a complicated process, affecting the entire supply chain and often incurring significant costs, delay and uncertainty. Many of the processes, and elements within these processes, are formalised and supported by varying levels of digitisation and automation. This ranges from energy simulation, geometric checking, to building information modelling based checking. However, there are currently no unifying standards or integrating technology to tie regulatory efforts together to enable the widespread adoption of automated compliance processes. This has left many current technical approaches, while advanced and robust, isolated. However, the increasing maturity of asset datasets/information models, means that integration of data/tools is now feasible. This paper will propose and validate a new approach of solving the problem of automated compliance checking through the use of an ecosystem of compliance checking services. This work has identified a clear research gap. How automated compliance checking in the construction sector can move beyond sole reliance on BIM data, and tightly coupled integration with software tools, to provide an extensible enough system to integrate the current isolated software elements currently used within compliance checking processes. To test this approach, an architecture for an ecosystem of compliance services will be specified. To validate this architecture, a prototype version will be developed and validated against requirements derived from the weaknesses of current approaches. This validation has found that a distributed ecosystem can perform accurately and successfully, whilst providing advantages in terms of scalability and extensibility. This approach provides a route to the increased adoption of automated compliance checking, overcoming the issues of relying on one computer system/application to perform all aspects of this process. [ABSTRACT FROM AUTHOR]

Building Information Modeling (BIM) is emerging as a method of creating, sharing, exchanging and managing the building information throughout the lifecycle between all stakeholders. Radio Frequency Identification (RFID), on the other hand, has emerged as an automatic data collection and information storage technology, and has been used in different applications in the AEC/FM (Architecture, Engineering, Construction, and Facilities Management) industry. RFID tags are attached to building assets throughout their lifecycle and used to store lifecycle and context aware information taken from a BIM. Consequently, there is a need for a standard and formal definition of RFID technology components in BIM. The goal of this paper is to add the definitions for RFID components to the BIM standard and to map the data to be stored in RFID memory to the associated entries in a BIM database. The paper defines new entities, data types, and properties to be added to the BIM. Furthermore, the paper identifies the relationships between RFID tags and building elements. These predefined relationships facilitate the linkage between BIM data and RFID data. Eventually, the data that are required to be saved on RFID tags can be automatically selected using the defined relationships in a BIM. A real-world case study has been implemented to validate the proposed method using available BIM software. [ABSTRACT FROM AUTHOR]

Timber construction is associated with a low carbon footprint and offers a high degree of sustainability. However, it poses challenges considering sound insulation. Acoustic analyses, which could require major expensive and time consuming changes in the building design, are typically performed once the design is already in the detailed stage. By using building information modelling (BIM), it is possible to shift the planning of the building physics, including acoustic analysis, to earlier phases. To make this possible, building models must include all the information necessary to perform acoustic analyses. One important part of acoustic analysis is identifying junctions between elements and map them to the junction types in standards. Until now, this investigation involves tedious manual processing for extracting multiple topological dependencies between different elements. Hence, this paper presents a framework for a seamless workflow between building models and acoustic analysis tools, based on an analysis of data models. The framework extracts and analyzes the element types, their geometry, and the connections of the individual elements in relation to each other. Through topological reasoning, along with a set of logical rules, the proposed framework identifies fifteen types of junctions, which can be distinguished acoustically for timber construction. The approach was evaluated in a prototypical implementation using a real-world model based on Industry Foundation Classes (IFC) as an example, in which the potential connection types were successfully extracted. This paper shows that junction analysis can be done with a geometric analysis to fill in missing semantic information about junctions of elements from the original data model. [ABSTRACT FROM AUTHOR]

Collaboration and communication are two essential aspects of Building Information Modeling (BIM). Current practice and international standards implement BIM collaboration on the basis of domain model federation where loosely coupled models are managed as separated files and coordinated in a mostly manual fashion. The concept has severe limitations regarding concurrency and version control, as the granularity of change tracking remains on the level of complete files and does not reach individual model objects. Due to this lack of change traceability, high manual effort for the subsequent coordination across the domains is generated. These limitations can be overcome by implementing modern approaches of digital collaboration based on object-level synchronization, widely denoted as BIM level 3. This paper presents a sound methodological basis for object-based version control by (1) representing the object networks of BIM models as formal property graph structures and (2) describing changes of the model by graph transformations. Consequently, modifications can be transmitted as graph transformation rules which are subsequently integrated on the receiving side, thus achieving object-level synchronization. The paper provides the underlying theory of describing model changes by means of graph transformations and demonstrates its benefits using the example of domain models implementing the Industry Foundation Classes (IFC) as their underlying data model. [ABSTRACT FROM AUTHOR]

Building Information Models (BIM) are comprehensive digital representations of buildings, which provide a large set of information originating from the different disciplines involved in the design, construction and operation processes. Moreover, accessing the data needed for a specific downstream application scenario is a challenging task in large-scale BIM projects. Several researchers recently proposed using formal query languages for specifying the desired information in a concise, well-defined manner. One of the main limitations of the languages introduced so far, however, is the inadequate treatment of geometric information. This is a significant drawback, as buildings are inherently spatial objects and qualitative spatial relationships accordingly play an important role in the analysis and verification of building models. In addition, the filters needed in specific data exchange scenarios for selecting the information required can be built by spatial objects and their relations. The lack of spatial functionality in BIM query languages is filled by the Query Language for Building Information Models (QL4BIM) which provides metric, directional and topological operators for defining filter expressions with qualitative spatial semantics. This paper focuses on the topological operators provided by the language. In particular, it presents a new implementation method based on the boundary representation of the operands which outperforms the previously presented octree-based approaches. The paper discusses the developed algorithms in detail and presents extensive performance tests. [ABSTRACT FROM AUTHOR]

Model View Definition (MVD) is the mainstream method for formally representing the knowledge about the data exchange of building information models (BIMs). The MVD ruleset can be used in automatically validating the compliance of the BIM data against the exchange requirements and rule constraints. At present, MVD validation is performed with the "matching-checking" process according to the data structure templates and the rule statements respectively. However, there are redundant visit of edges and nodes in a process with separated subgraph matching and value checking, and the efficiency of MVD validation on large real-world models is still a challenge. In this paper, the MVDLite algorithm is proposed for the fast validation of MVD rules. By integrating the separated templates and statements into a "rule-chain" structure, a fast round-trip searching can be performed, which remarkably speeds up the MVD validation in the experiments. Discussions on the complexity of the MVD validation algorithms and the applicable scope of the proposed algorithm are also provided, which intends to bring some new ideas to the community about the future evolution of the MVD technology. • The MVDLite algorithm is proposed for fast validation of Model View Definition rules on large models. • The algorithm performs round-trip searching on the "rule chain" for fast filtering the data nodes. • The discussions on the complexity and the applicable scope of the algorithm are presented. [ABSTRACT FROM AUTHOR]

Abstract: In this paper we present the on-going development of a framework for a domain specific, open query language for building information models. The proposed query language is intended for selecting, updating and deleting of data stored in Industry Foundation Classes models. Even though some partial solutions already have been suggested, none of them are open source, domain specific, platform independent and implemented at the same time. This paper provides an overview of existing approaches, conceptual sketches of the language in development and documents the current state of implementation as a prototype plugin developed for the open source model server platform bimserver.org. We report on the execution of example test-cases to show the general feasibility of the approach chosen. [Copyright &y& Elsevier]

As Building Information Modeling (BIM) workflows are becoming very relevant for the different stages of the project's lifecycle, more data is produced and managed across it. The information and data accumulated in BIM-based projects present an opportunity for analysis and extraction of project knowledge from the inception to the operation phase. In other industries, Machine Learning (ML) has been demonstrated to be an effective approach to automate processes and extract useful insights from different types and sources of data. The rapid development of ML applications, the growing generation of BIM-related data in projects, and the different needs for use of this data present serious challenges to adopt and effectively apply ML techniques to BIM-based projects in the Architecture, Engineering, Construction and Operations (AECO) industry. While research on the use of BIM data through ML has increased in the past decade, it is still in a nascent stage. In order to asses where the industry stands today, this paper carries out a systematic literature review (SLR) identifying and summarizing common emerging areas of application and utilization of ML within the context of BIM-generated data. Moreover, the paper identifies research gaps and trends. Based on the observed limitations, prominent future research directions are suggested, focusing on information architecture and data, applications scalability, and human information interactions. [ABSTRACT FROM AUTHOR]

Abstract: Planning the production sequence for a construction project requires the combination and transfer of information and knowledge from a large variety of areas. To support this knowledge combination and transfer, construction process visualizations, also referred to as 4D CAD, have proven to be valuable tools. Within these visualizations, signs, such as icons, indexes, or symbols, are often used to visualize contextual information related to the different construction activities. To understand the mechanisms of how these signs meaningfully convey such contextual information, this paper introduces a semiotic framework consisting of semiotic concepts, their definitions and relations. This paper also illustrates the power of the framework by applying it for analyzing the signs used in two construction process visualizations. [Copyright &y& Elsevier]

Highlights: • BIM applications in facility operation and maintenance are discussed in detail. • Potential solutions for BIM-O&M application challenges are provided. • Specific recommendations for future BIM-O&M research are provided. Abstract Building Information modeling (BIM) has the potential to advance and transform facilities Operation and Maintenance (O&M) by providing a platform for facility managers to retrieve, analyze, and process building information in a digitalized 3D environment. Currently, because of rapid developments in BIM, researchers and industry professionals need a state-of-the-art overview of BIM implementation and research in facility O&M. This paper presents a review of recent publications on the topic. It aims to evaluate and summarize the current BIM-O&M research and application developments from a facility manager's point of view, analyze research trends, and identify research gaps and promising future research directions. The scope of this research includes the academic articles, industry reports and guidelines pertaining to using BIM to improve selected facility O&M activities, including maintenance and repair, emergency management, energy management, change/relocation management, and security. The content analysis results show that research on BIM for O&M is still in its early stage and most of the current research has focused on energy management. We have identified that the interoperability in the BIM-O&M context is still a challenge and adopting the National Institute of Standards and Technology (NIST) Cyber-Physical Systems (CPS) Framework is a potential starting point to address this issue. More studies involving surveys are needed to understand the underlying O&M principles for BIM implementation – data requirements, areas of inefficiencies, the process changes. In addition, more studies on the return on investment of the innovative systems are required to justify the value of BIM-O&M applications and an improved Life Cycle Cost Analysis method is critical for such justifications. [ABSTRACT FROM AUTHOR]

Abstract: This paper presents results of the first phase of the research project “Serious Human Rescue Game” at Technische Universität Darmstadt. It presents a new serious gaming approach based on Building Information Modeling (BIM) for the exploration of the effect of building condition on human behavior during the evacuation process. In reality it is impossible to conduct rescue tests in burning buildings to study the human behavior. Therefore, the current methods of data-collecting for existing evacuation simulation models have limitations regarding the individual human factors. To overcome these limitations the research hypothesis is that the human behavior can be explored with a serious computer game: The decisions of a person during the game should be comparable to decisions during an extreme situation in the real world. To verify this hypothesis, this paper introduces a serious gaming approach for analyzing the human behavior in extreme situations. To implement a serious game, developers generally make use of 3D-modeling software to generate the game content. After this, the game logic needs to be added to the content with special software development kits for computer games. Every new game scenario has to be built manually from scratch. This is time-consuming and a great share of modeling work needs to be executed twice (e.g., 3D-modeling), at first by the architect for the parametric building model and the second time by the game designer for the 3D-game content. The key idea of the presented approach is to use the capabilities of BIM together with engineering simulations (fire, smoke) to build realistic serious game scenarios in a new and efficient way. This paper presents the first phase results of the research project mainly focusing on the conceptual design of the serious game prototype. The validation concept is also presented. The inter-operability between building information modeling applications and serious gaming platforms should allow different stakeholders to simulate building-related scenarios in a new, interactive and efficient way. [Copyright &y& Elsevier]

Abstract: Actors involved in the computer-supported design process work together towards a common goal – the design of a building. Current collaboration approaches often focus on versioned and distributed building models, which describe virtual building states on the basis of the object-oriented method. State changes (for example moving a wall or modifying its material) remain unconsidered and lead to inconsistency problems when exchanging, comparing and merging versioned building models. This paper presents a new modeling approach that combines existing state-oriented descriptions of a virtual building with additional change-oriented information by means of design steps denoted as modeling operations. A new language is defined for the formal description of modeling operations. These operations establish a standardized processing interface for existing building models, can represent design intents, enhance current models with change semantics and add to the consistency of these models. Moreover, this paper presents new concepts for intra-domain collaboration and model management that overcome current limitations when exchanging, comparing and merging versioned building models. The pilot implementation and some project scenarios in industry verify that current design processes can benefit in principle from combined state-oriented and change-oriented building information. [Copyright &y& Elsevier]

Abstract: The construction industry will have to find new ways of building to accomplish radical reductions of pollution and waste. Nano and biotechnology along with information technology have the potential to constitute a new building paradigm. The paper describes the concept of nano- to meter-scale building, which is based on this potential. The concept is not focused on the application of nanomaterials like nanosilica or carbon nanotubes, but on a new way of building, which unfolds from the nano into the meter range. It is based on bionanorobots, producing building materials using carbon extracted from CO2 in the air. Criteria and requirements regarding relevant technologies are defined and compared to the current research in the fields of bioengineering, nanorobotics, and characteristics and production of carbon nanotubes. The paper also presents a concept of a new building technology that would enable control and monitoring of construction at the nano level, as well as requirements regarding design methods and tools including the building information model that will become the only human input to the automated nano- to meter-scale building process. The paper concludes with suggestions for further research and development. [Copyright &y& Elsevier]

Abstract At early planning phases, the investigation of possible design options helps to find a suitable design for the client despite complex boundary conditions. In this context, the use of BIM models offers new prospects by representing a valuable input for simulation and analysis tasks. This paper aims at enabling a model-based management of design options. An applicable data model needs to be defined that supports the generation and exchange of design options. The developed concept avoids the use of separate models for explicit designs and thus, prevents the creation of redundant information. Furthermore, managing possible design variants within a single model increases the consistency of the provided information. Option categories to represent design options are introduced to structure the complex possibilities which might evolve when proceeding with the design process. Graph Data Models (GDM) are proposed as a transparent approach to describe and manage the resulting models as they provide a structured overview on affected elements and interdependencies. The results of the developed concept are shown by a case study focusing on high-rise buildings. Following the presented approach, architects, designers, contractors and clients are provided with a transparent description of design options which supports the decision making process from the very beginning. [ABSTRACT FROM AUTHOR]

Abstract The selection and configuration of site equipment is a fundamental part of construction preparation. Suitable site equipment supports the timely, cost-efficient and qualitative execution of the construction process. The use of planning tools based on formal knowledge management methods can both speed up the process of construction site planning and lead to better results. In this paper, we propose a rule-based knowledge inference system to support site equipment planners in a semi-automated manner using input data from building information models and working schedules. The knowledge-based system is built using the business rule management system Drools. Using a sample construction site, the feasibility of the proposed approach has been proven. [ABSTRACT FROM AUTHOR]

Abstract In recent years, exponential growth has been detected in research efforts focused on automated construction progress monitoring. Despite various data acquisition methods and approaches, the success is limited. This paper proposes a new method, where changes are constantly perceived and as-built model continuously updated during the construction process, instead of periodical scanning of the whole building under construction. It turned out that low precision 3D scanning devices, which are closely observing active workplaces, are sufficient for correct identification of the built elements. Such scanning devices are small enough to fit onto workers' protective helmets and on the applied machinery. In this way, workers capture all workplaces inside and outside of the building in real time and record partial point clouds, their locations, and time stamps. The partial point clouds are then registered and merged into a complete 4D as-built point cloud of a building under construction. Identification of as-designed BIM elements within the 4D as-built point cloud then results in the 4D as-built BIM. Finally, the comparison of the 4D as-built BIM and the 4D as-designed BIM enables identification of the differences between both models and thus the deviations from the time schedule. The differences are reported in virtual real-time, which enables more efficient project management. [ABSTRACT FROM AUTHOR]

Abstract Many software-based building processes require digital building models. Since the building stock does not have sufficient data in this regard, the demand for Scan-to-BIM processes is increasing. In this paper we present a system for the reconstruction of 'as-built' BIM content of house interiors based on the Google Tango technology. The strength of our approach is the use of low-cost mobile scanning devices and a client-server system that allows for a real-time collaborative scanning and reconstruction of indoor scenes. We developed a server application that continuously aggregates scan data of multiple scanning devices (clients) and applies the data stream to a real-time post-processing pipeline to reconstruct rooms, walls, doors and windows. The reconstruction result is then distributed to all clients, where it is visualized in real time. The collaborative workflow and real-time data processing make our system especially useful in situations that are time-critical and require concurrent collection and processing of data. One of our targeted use cases therefore is the model generation for crime scene documentation. The effectiveness of our approach was demonstrated on three test sites. Our results compare well to other state-of-art methods regarding the reconstruction of walls, but they also revealed potential for improvement regarding the detection of doors and windows in occluded and cluttered environments. [ABSTRACT FROM AUTHOR]

Abstract The design and optimisation of building structures is a complex undertaking that requires the effective collaboration of various stakeholders and involves technical and non-technical expertise. The paper investigated an integrated decision-support framework using Quality Function Deployment (QFD) in structural design optimisation. The aim of the study was to develop and test a systematic participatory model that utilises Building Information Modelling (BIM)-enabled technologies for data collection and group decision-making theory. The uncertainties associated with the decision-makers' preferences were computed using Evidential Reasoning (ER) algorithms in the QFD house of quality. An actual decision scenario was used to test the proposed framework and investigate its capabilities in the context of reinforced concrete buildings. The study demonstrated how the proposed QFD model could effectively enhance decision-making by managing the diversity of stakeholders' preferences via design integration, enhanced communication and shared domain knowledge. [ABSTRACT FROM AUTHOR]

Highlights • Automatic classification of WOs enhances and structures occupant-generated data. • Category prediction accuracy 57–86% for all problem categories and 80%+ for the top 3. • Prediction accuracy up to 90% was achieved for the most frequent subcategories. • Class prediction accuracies above 95% were consistently achieved for multiple classes. • When the problem category is known, subcategory prediction accuracy increases above 90% Abstract Occupant-generated work orders are recognized as a good potential data to support Facility Management (FM) activities, however they are unstructured and rarely contain the specific information engineers require to resolve the reported issues. Instead, this often requires multiple trips are often needed to identify the required trade, identify the problem and required parts/tools, and resolve. A key challenge is data quality: free-form (unstructured) text is collected that frequently lacks necessary detail for problem diagnosis. Machine Learning provides new opportunities within the FM domain to improve the quality of information collected through online work order reporting systems by automatically classifying WOs and prompting building occupants with appropriate FM team-developed questions in real time to gather the required specific information in structured form. This paper presents the development, comparison, and application of two sets of supervised machine learning models to perform this classification for WOs generated from occupant complaints. A set of ∼150,000 historical WOs was used for model development and textual classification using with various term and itemset frequency approaches was tested. Classifier prediction accuracies ranged from 46.6% to 81.3% for classification by detailed subcategory; this increased to between 68% (simple term frequency) to 90% (random forest) when the dataset only included the ten most common (accounting for 70% of all WOs) subcategories. Hierarchical classification decreased performance. An FM-BIM integration approach is finally presented using the resultant classifiers to provide facilities management teams with spatio-temporal visualization of the work order categories across a series of buildings to help prioritize and streamline operations and maintenance task assignments. [ABSTRACT FROM AUTHOR]

Abstract Considerable efforts have been made to reduce buildings' operational energy use over the last decades, but little attention has been paid to reduce the material transportation and construction energy. Focusing only on the operation phase forgoes the opportunity to reduce other building-related energy consumption, and even if the environmental impacts arising from construction and transportation are small as compared to the operation phases, its cumulative impact at the national level is of concern. The energy consumed by a building is divided into two parts embodied energy and operation energy. Further, the embodied energy is constituted of energy intensity of materials, energy consumed during transportation and energy consumed for construction. This paper proposes a methodology to integrate embodied energy consumption into a BIM platform and provides a seamless analysis based on available information. Plug-ins are developed to fulfill a convenient linkage between the BIM model and external databases. Simulation models are created, which can be used as templates for energy optimization during transportation and construction. By analyzing different resource combination scenarios, lower energy consumption can be achieved. [ABSTRACT FROM AUTHOR]

Abstract: The paper presents parts of the development of a spatial query language for building information models. Such a query language enables the spatial analysis of building information models and the extraction of partial models that fulfill certain spatial constraints. Among other features, it includes topological operators, i.e. operators that reflect the topological relationships between 3D spatial objects. The paper presents definitions of the semantics of the topological operators within, contain, touch, overlap, disjoint and equal in 3D space by using the 9-intersection model. It further describes a possible implementation of the topological operators by means of an octree-based algorithm. The recursive algorithm presented in this article relies on a breadth-first traversal of the operands’ octree representations and the application of rules that are based on the color of the octants under examination. Because it successively increases the discrete resolution of the spatial objects employed, the algorithm enables the user on the one hand to handle topological relationships in a fuzzy manner and on the other hand to trade-off between computational effort and the required accuracy. The article also presents detailed investigations on the runtime performance of the developed algorithm. [Copyright &y& Elsevier]

• A case study of an experiential learning-informed engineering course. • State-of-the-art living lab institutional building with advanced sensing. • Experiential-learning informed assignment help develop engineering skills. • Lessons learned are extracted for future university-level courses. Building performance – spanning energy use, greenhouse gas emissions, indoor environmental quality, etc. – is fundamental to the field of building engineering, yet it is typically taught with idealistic assumptions and traditional, teacher-centred, lecture-based methods. A promising emerging approach for university-level building engineering education is experiential learning, whereby students actively engage in complex tasks with real building data that reflect the kinds of problems graduates are likely to encounter in the workplace. To bridge the academic and employability skills and knowledge that they are developing through these tasks, students participate in reflective activities that help them to articulate the relevance and implications of the experience for lifelong learning. The objective of this paper is to assess the teaching and learning effectiveness of a data- and information-centric experiential learning approach to university-level engineering education. This paper reflects upon a particular course-based initiative informed by experiential learning theory that engaged fourth-year students in the life cycle of a new building on a university campus that was equipped with state-of-the-art building controls technologies. Students were provided access to a living lab resource with diverse artefacts from the building: drawings and building information models, guest lectures and technical tours, and live/historic data for the building. A series of assignments provided students with simulated problem scenarios to solve through the application of the building data as well as reflection prompts about their problem-solving process. The present paper details the assignments and the nature of the living lab data, students' assignment results, and students and teaching assistants' feedback on the overall teaching approach. The findings indicate a significant and continuous improvement in the reception and perceived educational value of the experiential assignments over the four-month term, suggesting living labs are a promising source of educational material for experiential learning. The paper concludes with lessons learned from the current course about experiential learning in building engineering education that can be applied more broadly to future courses in the field. [ABSTRACT FROM AUTHOR]

• Point cloud-based algorithms for automatically identifying occluded objects in 3D building information models. • Compatible input and output files with current industry practices. • Achieved over 90% recall rate and over 75% precision rate in classifying the visibility status of objects. • Validated using building information models of an academic building and an industrial facility. Virtual Reality (VR)-based construction design review applications have shown potential to enhance user performance in many research projects and experiments. Currently, visualizing occluded objects in VR is a challenge, and this function is indispensable for construction design review and coordination. This paper proposes an occlusion detection framework that semi-automatically identifies occluded objects in 3D construction models. The framework determines the visibility status of an object by converting the object to a point cloud and comparing the point cloud to the virtual laser scanning result of the original model. It exports models that are interoperable with VR development software so that visualization effects can be easily employed to occluded objects. The authors validated the framework using two building information models. The algorithm achieved a recall rate of 90.30% and a precision rate of 75.05% in a gasoline refinery facility model. It reached a higher 98.06% recall rate and a 97.53% precision rate in an academic building model. This paper contributes to the body of knowledge by proposing a semi-automatic occlusion detection framework and validating that point cloud-based algorithms are appropriate for this classification task. [ABSTRACT FROM AUTHOR]

Earthquakes can cause severe damage to structural and non-structural elements of buildings; consequently, they pose high risks to human lives. To mitigate such risks, attention has been paid to enhancing the indoor environment for increased building safety. Yet little effort has been made to assess a building occupants' evacuation behaviors in response to damage to the indoor environment. This paper addresses this issue with a novel simulation framework that couples human behaviors with changes to the indoor building environment during post-earthquake evacuation. In particular, we present a building information modelling (BIM)-based prototype that simulates seismic damage to the non-structural indoor elements and visualizes its impacts on evacuation using a color-coded heat map. The simulated damage is then used as input to an agent-based model for post-earthquake evacuation. Using a probabilistic method to assess the non-structural elements' damage states, we are able to evaluate the impact of indoor damage on the evacuation process. We performed a trial of our prototype for a hypothetical earthquake in an educational building. The results revealed how the average evacuation time would increase as the earthquake intensity increases (from 38.6 s for the no-damage scenario to 122.9 for the highest-damage scenario). The proposed prototype has the potential to be joined with other tools, such as finite-element-based simulation, to incorporate structural analysis as well. Planners and designers can explicitly use our model's output to analyze the post-earthquake evacuation with the indoor non-structural damage to assess different building design geometries that increase the chances of a suitable evacuation process. [ABSTRACT FROM AUTHOR]

In Germany, bridges have an average age of 40 years. A bridge consumes between 0.4% and 2% of its construction cost per year over its entire life cycle. This means that up to 80% of the construction cost are additionally needed for operation, inspection, maintenance, and destruction. Current practices rely either on paper-based inspections or on abstract specialist software. Every application in the inspection and maintenance sector uses its own data model for structures, inspections, defects, and maintenance. Due to this, data and properties have to be transferred manually, otherwise a converter is necessary for every data exchange between two applications. To overcome this issue, an adequate model standard for inspections, damage, and maintenance is necessary. Modern 3D models may serve as a single source of truth, which has been suggested in the Building Information Modeling (BIM) concept. Further, these models offer a clear visualization of the built infrastructure, and improve not only the planning and construction phases, but also the operation phase of construction projects. BIM is established mostly in the Architecture, Engineering, and Construction (AEC) sector to plan and construct new buildings. Currently, BIM does not cover the whole life cycle of a building, especially not inspection and maintenance. Creating damage models needs the building model first, because a defect is dependent on the building component, its properties and material. Hence, a building information model is necessary to obtain meaningful conclusions from damage information. This paper analyzes the requirements, which arise from practice, and the research that has been done in modeling damage and related information for bridges. With a look at damage categories and use cases related to inspection and maintenance, scientific literature is discussed and synthesized. Finally, research gaps and needs are identified and discussed. [ABSTRACT FROM AUTHOR]

In this paper we suggest an extension to the Industry Foundation Classes (IFC) model to integrate point cloud datasets. The proposal includes a schema extension to the core model allowing the storage of points, either as Cartesian coordinates, points in parametric space of associated building element surfaces or as discrete height fields projected as grids onto building elements. To handle the considerable amounts of data generated in the process of scanning building structures, we present intelligent compression approaches combined with the Hierarchical Data Format (HDF) as an efficient serialization and an alternative to clear text encoded ISO 10303 part 21 files. Based on prototypical implementations we show results of various serialization options and their impacts on storage efficiency. In this proposal the deepened semantic relationships have been favoured over compression ratios. Nevertheless, with various near-lossless layers of compression and binary serialization applied, a compression ratio of up to 67.7% is obtained for a building model with integrated point clouds, compared to the raw source data. The binary serialization is able to handle hundreds of millions of points, out of which specific spatial and semantic subsets can rapidly be extracted due to the containerized hierarchical storage model and association to building elements. The authors advocate the use of binary storage for sizeable point cloud scans, but also show how especially the grid discretization can result into usable points cloud segments embedded into text-based IFC models. [ABSTRACT FROM AUTHOR]

Assessing the quality of building information models (BIMs) is an important yet challenging task within the construction industry as projects are increasingly being delivered with BIM. This is particularly essential for facility management (FM) users as downstream information consumers that depend on the quality of models developed in the previous project phases. The research presented in this paper addresses this challenge by introducing a framework for information quality assessment (IQA) of BIMs for FM uses. The IQA framework is the outcome of an extensive study of two large owner organizations involving numerous BIM projects. The framework is structured based on the essential FM subjects: assets, spaces, and systems, and the model characteristics: objects, attributes, relationships, and spatial information. The framework is then operationalized through the development and evaluation of information quality (IQ) tests using BIM model checking tools across three projects with different levels of detail and complexity. The proposed IQA framework and associated tests advance the state of knowledge about BIM quality in terms of methods to represent and evaluate conformance to owner requirements. [ABSTRACT FROM AUTHOR]

Construction scheduling is a very demanding and time intensive process. Building information modeling (BIM) is becoming increasingly important for planning and scheduling, as it provides significant support for this difficult assignment. Further improvements can be achieved by applying predefined process templates for BIM-based schedules. It can reduce the planning time and thus increase the productivity. However, a manual definition of proper and application-specific process templates is very challenging. The automatic detection of recurring similar configurations of construction processes, called process patterns, would greatly support this complex task. Identified process patterns can be subsequently generalized, supporting the design of process templates. This contribution presents an overall concept for process pattern recognition in BIM-based construction schedules by applying graph-based methods. Due to the fact that graph matching algorithms are in general very time- and resource-consuming, an indexing technique based on features is used to solve this problem more efficiently. The paper focuses on the estimation of similarity in construction schedules, describing feature-based methods and similarity measure definitions in detail. Another emphasis is the preparation of schedules for the recognition of process patterns, including decomposition of schedules into smaller parts, referred to as subschedules, and normalization of features. The potential of this concept is demonstrated by two different case studies. The proper results of the evaluation show that the proposed method and similarity metrics are sufficient for the recognition of process patterns in construction schedules. [ABSTRACT FROM AUTHOR]

Oil and gas projects involve different construction disciplines such as mechanical, structural, and electrical. The current practice in these projects involves creating separate building information models for the different disciplines and compiling them into one model to check for collisions or conflicts. Due to intellectual property, contractual requirements, unfinished design, or technical issues during final model compilation, the final merged model lacks essential data for contractors such as the trade of each object in the model. Nonetheless, the model is issued to contractors who utilize it in different pre-construction planning tasks. However, due to data loss, incompleteness, or inconsistency, the model usability can become limited and the contractor has to review the model manually to extract information from it. This is a lengthy and costly task that becomes more challenging in fast-tracked projects that involve periodically issuing updated Building Information Models. One type of information that contractors need for different planning and estimation purposes is the scope of work for different construction trades in different areas of the project. In many cases, models lack explicit attributes of 3D objects that make it possible to perform an automated query of these objects by trade type. This research suggests a state of the art solution to automate the extraction of this information in such cases. In this paper, we describe a method that utilizes Resource Description Framework (RDF) encoding of BIM data together with Term Frequency-Inverse Document Frequency (TF-IDF) and entropy-based algorithms to automatically group 3D objects based on their trade. The proposed methodology is tested using three actual cases of oil and gas projects with more than four million objects in total. The results show that the proposed method can achieve a 91% purity in the generated groups. [ABSTRACT FROM AUTHOR]

With the rapid popularity of Building Information Modeling (BIM) technologies, BIM resources such as building product libraries are growing rapidly on the World Wide Web. However, numerous BIM resources are usually from heterogeneous systems or various manufacturers with ambiguous expressions and uncertain categories for product descriptions, which cannot provide effective support for information retrieval and categorization applications. Therefore, there is an increasing need for semantic annotation to reduce the ambiguity and unclearness of natural language in BIM documents. Based on Industry Foundation Classes (IFC) which is a major standard for BIM, this paper presents a concept-based automatic semantic annotation method for the documents of online BIM products. The method mainly consists of the following two stages. Firstly, with reference to the concepts and relationships explicitly defined in IFC, a word-level annotation algorithm is applied to the word-sense disambiguation. Secondly, based on latent semantic analysis technique, a document-level annotation algorithm is proposed to discover the relationships which are not explicitly defined in IFC. Finally, a prototype annotation system, named BIMTag, is developed and combined with a search engine for demonstrating the utility and effectiveness of our method. The BIMTag system is available at http://cgcad.thss.tsinghua.edu.cn/liuyushen/bimtag/ . [ABSTRACT FROM AUTHOR]

Clash management, including clash detection and resolution, is critical for construction project success. While clash detection has been automatically conducted by Building Information Modeling (BIM) tools, the clash resolution process is still being conducted manually. This process includes predicting clash change components and determining change methods. Previous studies predict clash change components based on single clash features while ignoring the interdependency between building components and clashes. This paper proposes to use a graph convolutional network (GCN) to improve clash change component prediction by considering the interdependency nature of building components. Instead of assuming each clash is independent, the GCN model uses a component dependency graph as the input to determine whether to make changes to a particular component based on both 1) its features and 2) its impacts on related components, which is transferred through the spatial dependency structure. To further decide what kind of spatial dependency is more informative for clash change component prediction, this study compares different dependency settings. We experiment on the BIM model of a real-world project and then use the Kruskal-Wallis test to compare model accuracy in different settings. The result shows that integrating dependency information into consideration can significantly improve model prediction accuracy, and the clash relation is the most critical factor for clash change component prediction. [ABSTRACT FROM AUTHOR]

• Review of the state-of-the-art of BIM and BPS integration and interoperability using a Systematic Literature Review and an expert review of relevant sources of knowledge. • Exploration of strategies for interoperability, main characteristics of information transfer pipelines and related issues reported in the literature. • Review of Research Projects funded by the European Union and Guidelines for BIM and BPS interoperability. • Discussion of the main trends emerged from the review and indication of possible future research developments. The study outlines the state-of-art on interoperability between Building Information Modeling (BIM) and Building Performance Simulation (BPS). First, the paper organises the result of a Systematic Literature Review (SLR) on the topic into three main strategies to achieve interoperability: the scripting to automate the information transfer between BIM and BPS environments, the pipelines supported by current practices, and the MVD and IFC schema extension approach. Software applications, types of files involved, building features, life cycle phases and model geometry considered by the literature along with reported interoperability issues, are also analysed. Secondly, an expert review of grey literature focusing on EU funded projects, guidelines, reports, best practices and key initiatives on the field of BIM to BPS interoperability is presented. The study wraps up by reporting on six major research trends identified by the review and highlighting future developments. The results of the review seem to indicate that effective interoperability can be achieved with the definition of a commonly accepted strategy, integrating shared guidelines for modelling, a better inclusion of energy evaluations through the whole life cycle of a building and the upgrade of software application for the accurate production of information with open format exchange files. [ABSTRACT FROM AUTHOR]

After an earthquake, Terrestrial Laser Scanning (TLS) can capture point clouds of the damaged state of building facades rapidly, remotely and accurately. A long-term research effort aims to develop applications that can reconstruct ‘as-damaged’ BIM models of reinforced concrete (RC) framed buildings based on their ‘as-built’ BIM models and scans of their ‘as-damaged’ states. This paper focuses on a crucial step: generating an initial ‘best-guess’ for the new locations of the façade structural members. The output serves as the seed for a recursive process in which the location and damage to each object is refined in turn. Locating the ‘as-built’ structural members in the ‘as-damaged’ scan is challenging because each member may have different displacement and damage. An algorithm was developed and tested for the case of reinforced concrete frames with masonry infill walls. It exploits the topology of the frames to map the original structural grid onto the damaged façade. The tests used synthetic datasets prepared from records of two earthquake-damaged buildings. In both cases, the results were sufficiently accurate to allow progress to the following step, assessment of the individual structural members. [ABSTRACT FROM AUTHOR]

Each domain industry requires the detailed specifications for sharing and exchanging building information models throughout the design, construction, and operation phases. Industry Foundation Classes (IFC) Model View Definitions (MVDs) specify required information for exchanges of building model data among building project experts. The data involves the identification of model semantics shared by two or more applications. However, since no robust standard for defining building semantics and requirements for data exchange has been agreed upon, information embedded in domain-specific MVDs are generated separately and are vague in scope, which results in a lack of consistency. In addition, the Information Delivery Manual (IDM) that includes exchange specifications needed for each exchange process of a product model is manually defined in a paper-based document. Because there is no clear logical link between the units of information in the exchange requirements of an IDM, and those of MVDs, the mapping that translates requirements of an IDM into ones of an MVD is open to various interpretation, without semantic and logical consistency. Such challenges might result in redundant requirements and rules for data exchange that are not supposed to be handled in the process of MVDs. To ameliorate this situation, this research proposes the new approach of formalizing domain knowledge and defining accurate data modules for model views. To achieve this goal, the authors employed ontological principles for generating an IDM for the precast concrete domain and for linking its MVD with formal information models. The formalized structure of domain knowledge is expected to support defining explicit data modules and developing manageable relationships among entities using semantic reasoning so that domain professionals and software vendors can identify the intents of the requirements of mapped MVDs and keep track of mapping problems. Moreover, to integrate IDM and MVD development processes, the ontology-based IDM is parsed and translated from OWL/XML to mvdXML, which automatically generates MVD documentation in the IfcDoc tool. [ABSTRACT FROM AUTHOR]

This paper presents a novel semi-automated method for the generation of 3D parametric as-built models from point clouds. Laser scanning and photogrammetry have a primary role in the survey of existing facilities, especially for the generation of accurate and detailed as-built parametric models that reflect the true condition of a building. Various studies demonstrate that point clouds have a sporadic adoption in large and complex parametric modeling projects. The lack of advanced processing algorithms able to convert point clouds into parametric objects makes the generation of accurate as-built models a challenging task for irregular elements without predefined shape. The proposed semi-automated method allows the creation of parametric models from photogrammetric and laser scanning point clouds. The method is intended as a multi-step process where NURBS curves and surfaces are used to reconstruct complex and irregular objects, without excessive simplification of the information encapsulated into huge point clouds to avoid heavy models useless for practical purposes and productive work. Different case studies derived from actual BIM-based projects are illustrated and discussed to demonstrate advantages and limitations of the method. [ABSTRACT FROM AUTHOR]

The nature of building projects necessitates building models to be designed by various parties representing disciplines in the Architecture, Engineering, Construction and Owner-operator (AECO) Industries. The federated model emerges as the most practical approach to deal with the various models, especially during design stage, construction coordination and beyond. One of the issues with the current approach is there is no real integration between the various models beyond their spatial co-location. This paper proposes a framework to enable fuller integration of otherwise disparate models into integrated models in the federated environment by enabling two critical concepts – deferred reference and an automatic object snap-in. The concepts are applied in a proposed change to an IFC schema and standardized procedure to enable the automatic snap-in mechanism. With these concepts, models could be designed and exported independently as valid, perhaps partial models and yet will remain integrated when they are inserted into the federated model. A prototype system has been developed to show the effectiveness of such integrated models. [ABSTRACT FROM AUTHOR]

Survivors trapped in void spaces formed when buildings collapse in an earthquake may be saved if search and rescue (SAR) operations are quick. A novel computational approach aims to provide building information that can guide SAR teams, thus minimizing their risk and accelerating operations. The inputs are an ‘as-built’ BIM model of the building before an earthquake and a partial ‘as-damaged’ BIM model of the exterior components after the earthquake derived from a terrestrial laser scan. A large set of possible collapse patterns is generated before the earthquake. After the event, the pattern with geometry most similar to that of the ‘as-damaged’ exterior BIM can be selected rapidly. This paper details the selection methods, which use least sum of point distances and Modal Assurance Criteria (MAC) algorithms, and illustrates their operation on a series of simulated computer models of collapsed structures, thus demonstrating the potential feasibility of the proposed approach. [ABSTRACT FROM AUTHOR]

Over the last few years, new methods that detect construction progress deviations by comparing laser scanning or image-based point clouds with 4D BIM are developed. To create complete as-built models, these methods require the visual sensors to have proper line-of-sight and field-of-view to building elements. For reporting progress deviations, they also require Building Information Modeling (BIM) and schedule Work-Breakdown-Structure (WBS) with high Level of Development (LoD). While certain logics behind sequences of construction activities can augment 4D BIM with lower LoDs to support making inferences about states of progress under limited visibility, their application in visual monitoring systems has not been explored. To address these limitations, this paper formalizes an ontology that models construction sequencing rationale such as physical relationships among components. It also presents a classification mechanism that integrates this ontology with BIM to infer states of progress for partially and fully occluded components. The ontology and classification mechanism are validated using a Charrette test and by presenting their application together with BIM and as-built data on real-world projects. The results demonstrate the effectiveness and generality of the proposed ontology. It also illustrates how the classification mechanism augments 4D BIM at lower LoDs and WBS to enable visual progress assessment for partially and fully occluded BIM elements and provide detailed operational-level progress information. [ABSTRACT FROM AUTHOR]

Building information models (BIMs) provide opportunities to serve as an information repository to store and deliver as-built information. Since a building is not always constructed exactly as the design information specifies, there will be discrepancies between a BIM created in the design phase (called as-designed BIM) and the as-built conditions. Point clouds captured by laser scans can be used as a reference to update an as-designed BIM into an as-built BIM (i.e., the BIM that captures the as-built information). Occlusions and construction progress prevent a laser scan performed at a single point in time to capture a complete view of building components. Progressively scanning a building during the construction phase and combining the progressively captured point cloud data together can provide the geometric information missing in the point cloud data captured previously. However, combining all point cloud data will result in large file sizes and might not always guarantee additional building component information. This paper provides the details of an approach developed to help engineers decide on which progressively captured point cloud data to combine in order to get more geometric information and eliminate large file sizes due to redundant point clouds. [ABSTRACT FROM AUTHOR]

• This paper compares methods to automatically classify BIM case studies by BIM use. • Unsupervised learning (LSA and LDA) and supervised learning (SVM) were used. • LDA yielded the highest F1 score, 80.75% on average. • LDA and LSA yielded high recall and low precision in most cases. • Conversely, SVM yielded high precision and low recall in most cases. This paper comparatively analyzes a method to automatically classify case studies of building information modeling (BIM) in construction projects by BIM use. It generally takes a minimum of thirty minutes to hours of collection and review and an average of four information sources to identify a project that has used BIM in a manner that is of interest. To automate and expedite the analysis tasks, this study deployed natural language processing (NLP) and commonly used unsupervised learning for text classification, namely latent semantic analysis (LSA) and latent Dirichlet allocation (LDA). The results were validated against one of representative supervised learning methods for text classification—support vector machine (SVM). When LSA and LDA detected phrases in a BIM case study that had higher similarity values to the definition of each BIM use than the threshold values, the system determined that the project had deployed BIM in the detected approach. For the classification of BIM use, the BIM uses specified by Pennsylvania State University were utilized. The approach was validated using 240 BIM case studies (512,892 features). When BIM uses were employed in a project, the project was labeled as "1"; when they were not, the project was labeled as "0." The performance was analyzed by changing parameters: namely, document segmentation , feature weighting , dimensionality reduction coefficient (k-value), the number of topics , and the number of iterations. LDA yielded the highest F1 score, 80.75% on average. LDA and LSA yielded high recall and low precision in most cases. Conversely, SVM yielded high precision and low recall in most cases and fluctuations in F1 scores. [ABSTRACT FROM AUTHOR]

Modern construction projects require sufficient planning and management of resources to become successful. Core issues are tasks that deal with maintaining the schedule, such as procuring materials, guaranteeing the supply chain, controlling the work status, and monitoring safety and quality. Timely feedback of project status aids project management by providing accurate percentages of task completions and appropriately allocating resources (workforce, equipment, material) to coordinate the next work packages. However, current methods for measuring project status or progress, especially on large infrastructure projects, are mostly based on manual assessments. Recent academic research and commercial development has focused on semi- or fully-automated approaches to collect and process images of evolving worksites. Preliminary results are promising and show capturing, analyzing, and documenting construction progress and linking to information models is possible. This article presents first an overview to vision-based sensing technology available for temporary resource tracking at infrastructure construction sites. Second, it provides the status quo of research applications by highlighting exemplary case. Third, a discussion follows on existing advantages and current limitations of vision based sensing and tracking. Open challenges that need to be addressed in future research efforts conclude this paper. [ABSTRACT FROM AUTHOR]