As-built Building Information Modeling Research Articles

Automatic Indoor as-Built Building Information Models Generation by Using Low-Cost RGB-D Sensors

To generate indoor as-built building information models (AB BIMs) automatically and economically is a great technological challenge. Many approaches have been developed to address this problem in recent years, but it is far from being settled, particularly for the point cloud segmentation and the extraction of the relationship among different elements due to the complicated indoor environment. This is even more difficult for the low-quality point cloud generated by low-cost scanning equipment. This paper proposes an automatic as-built BIMs generation framework that transforms the noisy 3D point cloud produced by a low-cost RGB-D sensor (about 708 USD for data collection equipment, 379 USD for the Structure sensor and 329 USD for iPad) to the as-built BIMs, without any manual intervention. The experiment results show that the proposed method has competitive robustness and accuracy, compared to the high-quality Terrestrial Lidar System (TLS), with the element extraction accuracy of 100%, mean dimension reconstruction accuracy of 98.6% and mean area reconstruction accuracy of 93.6%. Also, the proposed framework makes the BIM generation workflows more efficient in both data collection and data processing. In the experiments, the time consumption of data collection for a typical room, with an area of 45–67 , is reduced to 4–6 min with an RGB-D sensor from 50–60 min with TLS. The processing time to generate BIM models is about half minutes automatically, from around 10 min with a conventional semi-manual method.

Multicriteria analysis and information modelling in management of built environment

Building Information Modelling (BIM) proves to be the most urgent trend in construction for the last years. Still the major part of this issue is dedicated only to the first stages of building lifecycle: design and construction. This article goal is to provide a critical overview on recent achievements in BIM application for the different steps of building lifecycle as well as ongoing digitalization of facility management. The paper explores the importance of applying mathematical modelling and multicriteria analysis such as Analytical Hierarchy Process (AHP) and fuzzy logic in management of built environment and provides recent examples of such applications consequently exploring its potential. Method of analysis in this article is horizontal analysis of publication activity in related research topic. Different levels of digital built environment are considered: from building (BIM) to the whole city (GIS). The result of the research reveal that emergence of scan-to-BIM technology brings benefits not only for the buildings which are designed with BIM models (current situation in the market) but for the buildings which are already built (as-built BIM).

As-Built BIM for a Fifteenth-Century Chinese Brick Structure at Various LoDs

Building information modeling (BIM) has received significant research attention in the field of built heritage. As-built BIM refers to a BIM representation of the “as-is” conditions of built heritage at the time of a survey. Determining the level of development (LoD) is crucial for as-built BIM owing to its relevance to model effects and modeling efforts. This study addresses this issue from the viewpoint of a brick structure based on a case study of a fifteenth-century ruin in Nanjing, China. Three LoDs are proposed based on the combined use of a commercial platform and auxiliary tools: A host model linked with raster images composed using orthoimage and relief maps (LoD 1), an as-built volume with semantic skins (LoD 2), and a brick-by-brick model with custom industry foundation class parameters at local areas (LoD 3). The results reveal that LoD 1 caters to an efficient web-based workflow for brick-damage annotations; as-built dimensions can be extracted from LoD 2; and LoD 3 enables attributes, such as damage types, to be attached at the brick level. In future studies, the detection of brick shapes is expected to automate the process of as-built surface mapping.

A scan to as-built building information modeling workflow: a case study in Malaysia

Purpose Three dimensional (3 D) laser scanner surveying is widely used in many fields, such as agriculture, mining and heritage documentation and can be of great benefit for as-built documentation in construction and facility management domains. However, there is lack of applied research and use cases integrating 3 D laser scanner surveying with building information modeling (BIM) for existing facilities in Malaysia. This study aims to develop a scan to as-built BIM workflow to use 3 D laser scanner surveying and create as-built building information models of an existing complex facility in Malaysia. Design/methodology/approach A case study approach was followed to develop a scan to as-built BIM workflow through four main steps: 3 D laser scanning, data preprocessing, data registration and building information modeling. Findings This case study proposes a comprehensive scan to as-built BIM workflow which illustrates all the required steps to create a precise 3 D as-built building information model from scans. This workflow was successfully implemented to the Eco-Home facility at the Universiti Teknologi Malaysia. Originality/value Scan to as-built BIM is a digital alternative to manual and tedious process of documentation of as-built condition of a facility and provides a detail process using laser scans to create as-built building information models of facilities.

EXTRACTION OF MAIN LEVELS OF A BUILDING FROM A LARGE POINT CLOUD

Abstract. Horizontal levels are references entities, the base of man-made environments. Their creation is the first step for various applications including the BIM (Building Information Modelling). BIM is an emerging methodology, widely used for new constructions, and increasingly applied to existing buildings (scan-to-BIM). The as-built BIM process is still mainly manual or semi-automatic and therefore is highly time-consuming. The automation of the as-built BIM is a challenging topic among the research community. This study is part of an ongoing research into the scan-to-BIM process regarding the extraction of the principal structure of a building. More specifically, here we present a strategy to automatically detect the building levels from a large point cloud obtained with a terrestrial laser scanner survey. The identification of the horizontal planes is the first indispensable step to produce an as-built BIM model. Our algorithm, developed in C++, is based on plane extraction by means of the RANSAC algorithm followed by the minimization of the quadrate sum of points-plane distance. Moreover, this paper will take an in-depth look at the influence of data resolution in the accuracy of plane extraction and at the necessary accuracy for the construction of a BIM model. A laser scanner survey of a three floors building composed by 36 scan stations has produced a point cloud of about 550 million points. The estimated plane parameters at different data resolution are analysed in terms of distance from the full points cloud resolution.

COMBINATION OF THERMAL AND GEOMETRIC INFORMATION FOR BIM ENRICHMENT

Abstract. In the context of building renovation, infrared (IR) cameras are widely used to perform the energy audit of buildings. They allow analysing precisely the energetic performances of existing buildings and thermal analyses represent a key step for the reduction of energy consumption. They are also used to assess the thermal comfort of people living or working in a building. Building Information Models (BIM) are widespread to plan the rehabilitation of existing buildings and laser scanning is now commonly used to capture the geometry of buildings for as-built BIM creation. The combination of thermographic and geometric data presents a high number and variety of applications (Lagüela and Díaz-Vilariño, 2016). However, geometric and thermal information are generally acquired separately by different building stakeholders and thermal analyses are performed with independence of geometry. In this paper, the combination of thermal and geometric information is investigated for indoor of buildings. The aim of the project is to create 3D thermographic point clouds based on data acquired by a laser scanner and a thermal camera. Based on these point clouds, BIM models might be enriched with thermal information through the scan-to-BIM process.

From Semantic Segmentation to Semantic Registration: Derivative-Free Optimization–Based Approach for Automatic Generation of Semantically Rich As-Built Building Information Models from 3D Point Clouds

AbstractDevelopment of semantically rich as-built building information models (BIMs) presents an ongoing challenge for the global BIM and computing engineering communities. A plethora of approaches...

Implementing BIM and Finite Element Analysis in a Structural Integrity Investigation of Curtain Walls

ABSTRACT Evaluating the structural integrity of curtain walls during the life cycle of a building project can assist architects in developing better designs, help contractors establish better installation methods, and allow facility managers make informed maintenance decisions. This paper presents an effort to develop a process which combines three types of technologies: 3D laser scanning, Building Information Modeling (BIM), and Finite Element Analysis (FEA), to evaluate the structural integrity of a curtain wall. In a case study, a 3D laser scanner was used to scan the curtain wall, the resulting set of point clouds was used to create an actual as-built BIM model. This “as-is” BIM model is different than a construction as-built BIM model in that the former model captures existing deformations developed during construction, installation, and maintenance phases. Then further analysis was completed using simulation with FEA using the BIM model to potentially predict any future structural issues. Wind loads on the building façade and their effect on unintentional stresses built into the glass panel were studied. The final results inform of deformities in the curtain wall and show the amount of wind load the structure can support before there is a risk of structural damage. The contribution of this study is that the harmonious three-step technique quickens the entire process of identifying the risks to a building element. An additional use for these common software packages would be beneficial to all the stakeholders involved in the life cycle of the building, especially those concerned with the facilities management and the building life cycle.

Automatic Generation of Semantically Rich As‐Built Building Information Models Using 2D Images: A Derivative‐Free Optimization Approach

AbstractOver the past decade a considerable number of studies have focused on generating semantically rich as‐built building information models (BIMs). However, the prevailing methods rely on laborious manual segmentation or automatic but error‐prone segmentation. In addition, the methods failed to make good use of existing semantics sources. This article presents a novel segmentation‐free derivative‐free optimization (DFO) approach that translates the generation of as‐built BIMs from 2D images into an optimization problem of fitting BIM components regarding architectural and topological constraints. The semantics of the BIMs are subsequently enriched by linking the fitted components with existing semantics sources. The approach was prototyped in two experiments using an outdoor and an indoor case, respectively. The results showed that in the outdoor case 12 out of 13 BIM components were correctly generated within 1.5 hours, and in the indoor case all target BIM components were correctly generated with a root‐mean‐square deviation (RMSD) of 3.9 cm in about 2.5 hours. The main computational novelties of this study are: (1) to translate the automatic as‐built BIM generation from 2D images as an optimization problem; (2) to develop an effective and segmentation‐free approach that is fundamentally different from prevailing methods; and (3) to exploit online open BIM component information for semantic enrichment, which, to a certain extent, alleviates the dilemma between information inadequacy and information overload in BIM development.

Occupant perceptions of building information model-based energy visualizations in eco-feedback systems

While technology advancements are improving the energy efficiency of buildings, occupant behavior remains a critical factor in ensuring the effectiveness of such enhancements. To this end, numerous eco-feedback systems have been developed to reduce building energy use through influencing occupants' behaviors during building operations. Information representation is a critical component in eco-feedback systems, affecting the users' interpretation, engagement, and motivation to reduce energy consumption. Many studies have focused on using different charts and technical units or abstract and artistic visualizations to represent energy consumption. However, the effectiveness of such techniques varies across studies. Recent research emphasizes the need to integrate information representation strategies that balance numeric and aesthetic appeal. Concurrently, studies have called for increased adoption of a Building Information Model (BIM) during a building's operations phase to improve facility management. In this paper, we introduce a new eco-feedback information representation method that combines numeric and aesthetic appeal through leveraging spatial and color-coding techniques in BIM. The BIM-integrated energy visualization approach developed in this paper uses the Revit Application Program Interface (API) and allows users to visualize and compare energy consumption values in 2D and 3D views of a multi-family building through a color-coding scheme in an as-built BIM. The method is validated through a user survey that quantitatively and qualitatively assesses the proposed 2D and 3D BIM eco-feedback compared to more traditional bar chart based eco-feedback. Our findings suggest that 2D spatial, color-coded eco-feedback provides the optimal information representation, as it is easy to understand, while evoking engaging and motivating responses from users. This study advances our understanding of eco-feedback information representation while expanding BIM applications during building operations. These are important steps to address the human dimension of energy efficiency in the built environment.

Method for visualizing energy use in building information models

While technology advancements are increasingly improving the energy efficiency of buildings, occupant behavior remains a critical factor in ensuring the effectiveness of such enhancements. To this end, numerous eco-feedback systems have been developed to reduce building energy use through adjusting occupants’ behaviors. The information represented in an eco-feedback system affects the users’ engagement, motivation, and interpretation. In this paper, we introduce a new information representation method in which a building information model (BIM) is integrated with energy use information to enhance visual representation of energy use. The BIM-integrated energy visualization approach developed in this paper allows users to visualize energy consumption values of each building room through a color-coding scheme in an as-built BIM. Colors correspond to the levels of energy consumption in individual rooms compared to other rooms in a building, which enables a visually intuitive normative comparison for building eco-feedback systems. This representation may lead to increased user engagement in and improved interpretation of eco-feedback systems.

From Point Clouds to Building Information Models: 3D Semi-Automatic Reconstruction of Indoors of Existing Buildings

The creation of as-built Building Information Models requires the acquisition of the as-is state of existing buildings. Laser scanners are widely used to achieve this goal since they permit to collect information about object geometry in form of point clouds and provide a large amount of accurate data in a very fast way and with a high level of details. Unfortunately, the scan-to-BIM (Building Information Model) process remains currently largely a manual process which is time consuming and error-prone. In this paper, a semi-automatic approach is presented for the 3D reconstruction of indoors of existing buildings from point clouds. Several segmentations are performed so that point clouds corresponding to grounds, ceilings and walls are extracted. Based on these point clouds, walls and slabs of buildings are reconstructed and described in the IFC format in order to be integrated into BIM software. The assessment of the approach is proposed thanks to two datasets. The evaluation items are the degree of automation, the transferability of the approach and the geometric quality of results of the 3D reconstruction. Additionally, quality indexes are introduced to inspect the results in order to be able to detect potential errors of reconstruction.

AUTOMATED CLASSIFICATION OF HERITAGE BUILDINGS FOR AS-BUILT BIM USING MACHINE LEARNING TECHNIQUES

Abstract. Semantically rich three dimensional models such as Building Information Models (BIMs) are increasingly used in digital heritage. They provide the required information to varying stakeholders during the different stages of the historic buildings life cyle which is crucial in the conservation process. The creation of as-built BIM models is based on point cloud data. However, manually interpreting this data is labour intensive and often leads to misinterpretations. By automatically classifying the point cloud, the information can be proccesed more effeciently. A key aspect in this automated scan-to-BIM process is the classification of building objects. In this research we look to automatically recognise elements in existing buildings to create compact semantic information models. Our algorithm efficiently extracts the main structural components such as floors, ceilings, roofs, walls and beams despite the presence of significant clutter and occlusions. More specifically, Support Vector Machines (SVM) are proposed for the classification. The algorithm is evaluated using real data of a variety of existing buildings. The results prove that the used classifier recognizes the objects with both high precision and recall. As a result, entire data sets are reliably labelled at once. The approach enables experts to better document and process heritage assets.

Deconstruction waste management through 3d reconstruction and bim: a case study

The construction industry is responsible for 50% of the solid waste generated worldwide. Governments around the world formulate legislation and regulations concerning recycling and re-using building materials, aiming to reduce waste and environmental impact. Researchers have also been developing strategies and models of waste management for construction and demolition of buildings. The application of Building Information Modeling (BIM) is an example of this. BIM is emergent technology commonly used to maximize the efficiency of design, construction and maintenance throughout the entire lifecycle. The uses of BIM on deconstruction or demolition are not common; especially the fixtures and fittings of buildings are not considered in BIM models. The development of BIM is based on two-dimensional drawings or sketches, which may not be accurately converted to 3D BIM models. In addition, previous researches mainly focused on construction waste management. There are few studies about the deconstruction waste management focusing on demolition. To fill this gap, this paper aims to develop a framework using a reconstructed 3D model with BIM, for the purpose of improving BIM accuracy and thus developing a deconstruction waste management system to improve demolition efficiency, effective recycling and cost savings. In particular, the developed as-built BIM will be used to identify and measure recyclable materials, as well as to develop a plan for the recycling process.

Conceptualising the FinDD API plug-in: A study of BIM-FM integration

This research paper reports upon a client driven approach to iteratively develop the FinDD application programming interface (API) plug-in. FinDD integrates building information modelling (BIM) and facilities management (FM) via the novel development and application of totems. Totems visualise rich semantic FM data in a 3D object to extend the use and application of COBie thereby minimising costs incurred by the FM team to update and maintain the as-built BIM. Participatory action research was used to develop the proof of concept and involved a study of two multi-storey, mixed-use educational buildings (with a contract value worth ≥£150 million UK Sterling) located within Birmingham, UK. The lead researcher worked for the client's estates department and was instrumental in liaising with members of the project management team, synthesising their semantic data requirements and developing the FinDD API plug-in for Autodesk Revit. Research findings reveal that whilst FinDD was positively received as a bespoke extension of COBie (that was tailored to specifically meet client needs), further development is required to mitigate software inflexibility and augment automation of semantic data transfer, storage and analysis. Future work will validate the API plug-in via user experience and integrate additional databases such as post occupancy evaluations (POE).

PARAMETRIC MODELLING OF AS-BUILT BEAM FRAMED STRUCTURE IN BIM ENVIRONMENT

Abstract. A complete documentation and conservation of a historic timber roof requires the integration of geometry modelling, attributional and dynamic information management and results of structural analysis. Recently developed as-built Building Information Modelling (BIM) technique has the potential to provide a uniform platform, which provides possibility to integrate the traditional geometry modelling, parametric elements management and structural analysis together. The main objective of the project presented in this paper is to develop a parametric modelling tool for a timber roof structure whose elements are leaning and crossing beam frame. Since Autodesk Revit, as the typical BIM software, provides the platform for parametric modelling and information management, an API plugin, able to automatically create the parametric beam elements and link them together with strict relationship, was developed. The plugin under development is introduced in the paper, which can obtain the parametric beam model via Autodesk Revit API from total station points and terrestrial laser scanning data. The results show the potential of automatizing the parametric modelling by interactive API development in BIM environment. It also integrates the separate data processing and different platforms into the uniform Revit software.

Towards automatic generation of as-built BIM: 3D building facade modeling and material recognition from images

As-built building information model (BIM) is an urgent need of the architecture, engineering, construction and facilities management (AEC/FM) community. However, its creation procedure is still labor-intensive and far from maturity. Taking advantage of prevalence of digital cameras and the development of advanced computer vision technology, the paper proposes to reconstruct a building facade and recognize its surface materials from images taken from various points of view. These can serve as initial steps towards automatic generation of as-built BIM. Specifically, 3D point clouds are generated from multiple images using structure from motion method and then segmented into planar components, which are further recognized as different structural components through knowledge based reasoning. Windows are detected through a multilayered complementary strategy by combining detection results from every semantic layer. A novel machine learning based 3D material recognition strategy is presented. Binary classifiers are trained through support vector machines. Material type at a given 3D location is predicted by all its corresponding 2D feature points. Experimental results from three existing buildings validate the proposed system.

HISTORICAL BUILDINGS MODELS AND THEIR HANDLING VIA 3D SURVEY: FROM POINTS CLOUDS TO USER-ORIENTED HBIM

This paper retraces some research activities and application of 3D survey techniques and Building Information Modelling (BIM) in the environment of Cultural Heritage. It describes the diffusion of as-built BIM approach in the last years in Heritage Assets management, the so-called Built Heritage Information Modelling/Management (BHIMM or HBIM), that is nowadays an important and sustainable perspective in documentation and administration of historic buildings and structures. <br><br> The work focuses the documentation derived from 3D survey techniques that can be understood like a significant and unavoidable knowledge base for the BIM conception and modelling, in the perspective of a coherent and complete management and valorisation of CH. It deepens potentialities, offered by 3D integrated survey techniques, to acquire productively and quite easilymany 3D information, not only geometrical but also radiometric attributes, helping the recognition, interpretation and characterization of state of conservation and degradation of architectural elements. From these data, they provide more and more high descriptive models corresponding to the geometrical complexity of buildings or aggregates in the well-known 5D (3D + time and cost dimensions). <br><br> Points clouds derived from 3D survey acquisition (aerial and terrestrial photogrammetry, LiDAR and their integration) are reality-based models that can be use in a semi-automatic way to manage, interpret, and moderately simplify geometrical shapes of historical buildings that are examples, as is well known, of non-regular and complex geometry, instead of modern constructions with simple and regular ones. In the paper, some of these issues are addressed and analyzed through some experiences regarding the creation and the managing of HBIMprojects on historical heritage at different scales, using different platforms and various workflow. The paper focuses on LiDAR data handling with the aim to manage and extract geometrical information; on development and optimization of semi-automatic process of segmentation, recognition and modelling of historical shapes of complex structures; on communication of historical heritage by virtual and augmented reality (VR/AR) in a 3D reconstruction of buildings aggregates from a LiDAR and UAV survey. The HBIM model have been implemented and optimized to be managed and browse by mobile devices for not only touristic or informative scopes, but also to ensure that HBIM platforms will become more easy and valuable tools helping all professionals of AEC involved in the documentation and valorisation process, that nowadays more and more distinguish CH policies.

HISTORICAL BUILDINGS MODELS AND THEIR HANDLING VIA 3D SURVEY: FROM POINTS CLOUDS TO USER-ORIENTED HBIM

Abstract. This paper retraces some research activities and application of 3D survey techniques and Building Information Modelling (BIM) in the environment of Cultural Heritage. It describes the diffusion of as-built BIM approach in the last years in Heritage Assets management, the so-called Built Heritage Information Modelling/Management (BHIMM or HBIM), that is nowadays an important and sustainable perspective in documentation and administration of historic buildings and structures. The work focuses the documentation derived from 3D survey techniques that can be understood like a significant and unavoidable knowledge base for the BIM conception and modelling, in the perspective of a coherent and complete management and valorisation of CH. It deepens potentialities, offered by 3D integrated survey techniques, to acquire productively and quite easilymany 3D information, not only geometrical but also radiometric attributes, helping the recognition, interpretation and characterization of state of conservation and degradation of architectural elements. From these data, they provide more and more high descriptive models corresponding to the geometrical complexity of buildings or aggregates in the well-known 5D (3D + time and cost dimensions). Points clouds derived from 3D survey acquisition (aerial and terrestrial photogrammetry, LiDAR and their integration) are reality-based models that can be use in a semi-automatic way to manage, interpret, and moderately simplify geometrical shapes of historical buildings that are examples, as is well known, of non-regular and complex geometry, instead of modern constructions with simple and regular ones. In the paper, some of these issues are addressed and analyzed through some experiences regarding the creation and the managing of HBIMprojects on historical heritage at different scales, using different platforms and various workflow. The paper focuses on LiDAR data handling with the aim to manage and extract geometrical information; on development and optimization of semi-automatic process of segmentation, recognition and modelling of historical shapes of complex structures; on communication of historical heritage by virtual and augmented reality (VR/AR) in a 3D reconstruction of buildings aggregates from a LiDAR and UAV survey. The HBIM model have been implemented and optimized to be managed and browse by mobile devices for not only touristic or informative scopes, but also to ensure that HBIM platforms will become more easy and valuable tools helping all professionals of AEC involved in the documentation and valorisation process, that nowadays more and more distinguish CH policies.

VALIDATION OF POINT CLOUDS SEGMENTATION ALGORITHMS THROUGH THEIR APPLICATION TO SEVERAL CASE STUDIES FOR INDOOR BUILDING MODELLING

Abstract. Laser scanners are widely used for the modelling of existing buildings and particularly in the creation process of as-built BIM (Building Information Modelling). However, the generation of as-built BIM from point clouds involves mainly manual steps and it is consequently time consuming and error-prone. Along the path to automation, a three steps segmentation approach has been developed. This approach is composed of two phases: a segmentation into sub-spaces namely floors and rooms and a plane segmentation combined with the identification of building elements. In order to assess and validate the developed approach, different case studies are considered. Indeed, it is essential to apply algorithms to several datasets and not to develop algorithms with a unique dataset which could influence the development with its particularities. Indoor point clouds of different types of buildings will be used as input for the developed algorithms, going from an individual house of almost one hundred square meters to larger buildings of several thousand square meters. Datasets provide various space configurations and present numerous different occluding objects as for example desks, computer equipments, home furnishings and even wine barrels. For each dataset, the results will be illustrated. The analysis of the results will provide an insight into the transferability of the developed approach for the indoor modelling of several types of buildings.