scholarly journals From Point Cloud Data to Building Information Modelling: An Automatic Parametric Workflow for Heritage

2020 ◽  
Vol 12 (7) ◽  
pp. 1094 ◽  
Author(s):  
Mesrop Andriasyan ◽  
Juan Moyano ◽  
Juan Enrique Nieto-Julián ◽  
Daniel Antón
Keyword(s):  
Point Cloud ◽  
Laser Scanning ◽  
Accuracy Assessment ◽  
Parametric Modelling ◽  
Point Cloud Data ◽  
Building Information Modelling ◽  
Historical Interpretation ◽  
Information Modelling ◽  
Cloud Data ◽  
Building Information

Building Information Modelling (BIM) is a globally adapted methodology by government organisations and builders who conceive the integration of the organisation, planning, development and the digital construction model into a single project. In the case of a heritage building, the Historic Building Information Modelling (HBIM) approach is able to cover the comprehensive restoration of the building. In contrast to BIM applied to new buildings, HBIM can address different models which represent either periods of historical interpretation, restoration phases or records of heritage assets over time. Great efforts are currently being made to automatically reconstitute the geometry of cultural heritage elements from data acquisition techniques such as Terrestrial Laser Scanning (TLS) or Structure From Motion (SfM) into BIM (Scan-to-BIM). Hence, this work advances on the parametric modelling from remote sensing point cloud data, which is carried out under the Rhino+Grasshopper-ArchiCAD combination. This workflow enables the automatic conversion of TLS and SFM point cloud data into textured 3D meshes and thus BIM objects to be included in the HBIM project. The accuracy assessment of this workflow yields a standard deviation value of 68.28 pixels, which is lower than other author’s precision but suffices for the automatic HBIM of the case study in this research.

scholarly journals Extracting features from laser scanning point cloud

2018 ◽  
Vol 44 ◽  
pp. 00013 ◽  
Author(s):  
Vladimir Badenko ◽  
Alexander Fedotov ◽  
Dmitry Zotov
Keyword(s):  
Point Cloud ◽  
Laser Scanning ◽  
Historical Buildings ◽  
Historical Building ◽  
Building Information Modelling ◽  
Historic Building ◽  
Technology Application ◽  
Information Modelling ◽  
Hybrid Technology ◽  
Building Information

Analyses of gaps in processing of raw laser scanning data and results of bridging the gaps discovered on the basis of usage of laser scanning data for historic building information modelling are presented. Some results of the development of a unified hybrid technology for the processing, storage, access and visualization of combined laser scanning and photography data about historical buildings are analyzed. The first result of the technology application to historical building of St. Petersburg Polytechnic University shows the robustness of the approaches proposed.

scholarly journals Phased Reverse Engineering Framework for Sustainable Cultural Heritage Archives Using Laser Scanning and BIM: The Case of the Hwanggungwoo (Seoul, Korea)

2020 ◽  
Vol 12 (19) ◽  
pp. 8108
Author(s):  
Namhyuk Ham ◽  
Baek-Il Bae ◽  
Ok-Kyung Yuh
Keyword(s):  
Cultural Heritage ◽  
Reverse Engineering ◽  
Point Cloud ◽  
Laser Scanning ◽  
Information Model ◽  
Point Cloud Data ◽  
Building Information Model ◽  
Cloud Data ◽  
Building Information

This study proposed a phased reverse engineering framework to construct cultural heritage archives using laser scanning and a building information model (BIM). This framework includes acquisition of point cloud data through laser scanning. Unlike previous studies, in this study, a standard for authoring BIM data was established through comparative analysis of existing archives and point cloud data, and a method of building valuable BIM data as an information model was proposed. From a short-term perspective, additional archives such as member lists and drawings can be extracted from BIM data built as an information model. In addition, from a long-term perspective, a scenario for using the cultural heritage archive consisting of historical records, point cloud data, and BIM data was presented. These scenarios were verified through a case study. In particular, through the BIM data building and management method, relatively very light BIM data (499 MB) could be built based on point cloud data (more than 917 MB), which is a large amount of data.

scholarly journals A Framework for Automated Acquisition and Processing of As-Built Data with Autonomous Unmanned Aerial Vehicles

Sensors ◽  
2019 ◽  
Vol 19 (20) ◽  
pp. 4513 ◽  
Author(s):  
Henk Freimuth ◽  
Markus König
Keyword(s):  
Point Cloud ◽  
Point Cloud Data ◽  
Building Information Modelling ◽  
Planning And Scheduling ◽  
Robot Operating System ◽  
Cloud Data ◽  
Deterministic Routing ◽  
Stereo Cameras ◽  
Building Information ◽  
Aerial Vehicle

Planning and scheduling in construction heavily depend on current information about the state of construction processes. However, the acquisition process for visual data requires human personnel to take photographs of construction objects. We propose using unmanned aerial vehicle (UAVs) for automated creation of images and point cloud data of particular construction objects. The method extracts locations of objects that require inspection from Four Dimensional Building Information Modelling (4D-BIM). With this information at hand viable flight missions around the known structures of the construction site are computed. During flight, the UAV uses stereo cameras to detect and avoid any obstacles that are not known to the model, for example moving humans or machinery. The combination of pre-computed waypoint missions and reactive avoidance ensures deterministic routing from takeoff to landing and operational safety for humans and machines. During flight, an additional software component compares the captured point cloud data with the model data, enabling automatic per-object completion checking or reconstruction. The prototype is developed in the Robot Operating System (ROS) and evaluated in Software-In-The-Loop (SITL) simulations for the sake of being executable on real UAVs.

scholarly journals DEVELOPING VERIFICATION SYSTEMS FOR BUILDING INFORMATION MODELS OF HERITAGE BUILDINGS WITH HETEROGENEOUS DATASETS

2017 ◽  
Vol XLII-2/W5 ◽  
pp. 125-128 ◽  
Author(s):  
L. Chow ◽  
S. Fai
Keyword(s):  
Point Cloud ◽  
Laser Scanning ◽  
Terrestrial Laser Scanning ◽  
Point Cloud Data ◽  
Cloud Data ◽  
Interior Spaces ◽  
Information Models ◽  
Heterogeneous Datasets ◽  
Building Information ◽  
Building Information Models

The digitization and abstraction of existing buildings into building information models requires the translation of heterogeneous datasets that may include CAD, technical reports, historic texts, archival drawings, terrestrial laser scanning, and photogrammetry into model elements. In this paper, we discuss a project undertaken by the Carleton Immersive Media Studio (CIMS) that explored the synthesis of heterogeneous datasets for the development of a building information model (BIM) for one of Canada’s most significant heritage assets – the Centre Block of the Parliament Hill National Historic Site. The scope of the project included the development of an as-found model of the century-old, six-story building in anticipation of specific model uses for an extensive rehabilitation program. The as-found Centre Block model was developed in Revit using primarily point cloud data from terrestrial laser scanning. The data was captured by CIMS in partnership with Heritage Conservation Services (HCS), Public Services and Procurement Canada (PSPC), using a Leica C10 and P40 (exterior and large interior spaces) and a Faro Focus (small to mid-sized interior spaces). Secondary sources such as archival drawings, photographs, and technical reports were referenced in cases where point cloud data was not available. As a result of working with heterogeneous data sets, a verification system was introduced in order to communicate to model users/viewers the source of information for each building element within the model.

scholarly journals Point clouds for use in building information models (BIM)

2021 ◽  
Vol 64 (04) ◽  
pp. 594-613
Author(s):  
Robert Klinc ◽  
Uroš Jotanović ◽  
Klemen Kregar
Keyword(s):  
Point Cloud ◽  
Laser Scanning ◽  
User Interaction ◽  
Point Clouds ◽  
Point Cloud Data ◽  
Material World ◽  
Cloud Data ◽  
Digital World ◽  
Starting Point ◽  
Building Information

The use of point clouds in extracting data for building information modelling (BIM) has become common recently. Managers of older buildings are working to centralise information. Documentation about mechanical installations, plumbing, electricity, and previous interventions is often stored on scattered media, frequently still on paper. In the transformation of the material world into the digital world, the point cloud is the starting point, containing information about the material world obtained by various means such as photogrammetry, terrestrial or aerial laser scanning. Manual BIM modelling for management, maintenance and future use is a time-consuming and error-prone process. We would like to automate this process and avoid these errors. Recently, there have been developed an increasing number of stand-alone programmes and add-ons that provide automated, fast, and more accurate modelling based on point cloud data. In this paper we present an investigation into the possibilities for automating the creation of BIM models from point cloud data. The result is a semi-automated process for modelling individual BIM elements, which we have tested on specific examples of modelling individual elements (walls, pipes, and columns). We note that despite the automation of the process, a high level of user interaction is still required to produce good quality models.

scholarly journals BUILDING INFORMATION MODELLING OF A MULTI STOREY BUILDING USING TERRESTRIAL LASER SCANNER AND VISUALISATION USING POTREE: AN OPEN SOURCE POINT CLOUD RENDERER

2019 ◽  
Vol XLII-2/W17 ◽  
pp. 421-426
Author(s):  
A. Yeshwanth Kumar ◽  
M. A. Noufia ◽  
K. A. Shahira ◽  
A. M. Ramiya
Keyword(s):  
Open Source ◽  
Web Application ◽  
Point Cloud ◽  
Laser Scanner ◽  
Terrestrial Laser Scanner ◽  
Point Cloud Data ◽  
Building Information Modelling ◽  
Cloud Data ◽  
Building Information ◽  
Storey Building

Abstract. With the rapid development in infrastructure, the need to document man-made structures is in increasing demand and inevitable. Such a process of digital documentation of buildings is called Building Information Modelling (BIM). Conventional techniques of BIM involve manual drafting & modelling using computer aided design, drafting & modelling software. Although these techniques are more accurate, given the increase in the size and complexity of modern structures, it would be tedious and time consuming for such manual work. It is in this context LiDAR shows great potential to simplify this task. Laser scanning enables rapid mapping of a building with a high degree of spatial accuracy. Since the spatial point sampling distance of any LiDAR scanner is usually in the order of centimetres or millimetres, this has potential not only to generate high density scans of the building but also to identify even the smallest defects in a structure. This facilitates using LiDAR to study the serviceability of a building. In this project, the feasibility of using a terrestrial laser scanner (TLS) to scan a multi-storey building was investigated. Additionally, the reliability of Potree for visualising point cloud data was tested. Potree is an open-source WebGL based point cloud renderer. Potree enables us to render point clouds and visualise in a portable web application. This application is also capable of making measurements of high accuracy on the 3D model of the library. This could serve to be of great utility in surveying applications. The object of study was chosen as a six-storey building, each floor having differing layouts. Two of these storeys were below ground surface level which also proved to be a test for the reliability of TLS in challenging terrain. The building has a towering height and large footprint which made it a perfect candidate for this project. A total of 54 scans (44 interior scans and 10 exterior scans of the library) were acquired with each subsequent scan station not more than 10m apart from the previous one. This data was brought to the lab for further processing. The processing was carried out using open-source software packages (LAStools, CloudCompare, etc). After processing, the complete point cloud data had 483,292,994 points. In order to make the data easier to handle, spatial sub-sampling of the data was done after which the final point cloud had 87,789,548 points. Finally, this sub-sampled point cloud was published using the open source Potree Converter into an interactive web application.

scholarly journals Integration of point cloud data and hyperspectral imaging as a data gathering methodology for refurbishment projects using building information modelling (BIM)

2019 ◽  
Vol 17 (1) ◽  
pp. 57-75 ◽  
Author(s):  
Kinjiro Amano ◽  
Eric C.W. Lou ◽  
Rodger Edwards
Keyword(s):  
Hyperspectral Imaging ◽  
Point Cloud ◽  
Laser Scanning ◽  
Spatial Information ◽  
Data Gathering ◽  
Facilities Management ◽  
Building Information Modelling ◽  
Content Type ◽  
Cloud Data ◽  
Building Information

Purpose Building information modelling (BIM) is a digital representation of the physical and functional characteristics of a building. Its use offers a range of benefits in terms of achieving the efficient design, construction, operation and maintenance of buildings. Applying BIM at the outset of a new build project should be relatively easy. However, it is often problematic to apply BIM techniques to an existing building, for example, as part of a refurbishment project or as a tool supporting the facilities management strategy, because of inadequacies in the previous management of the dataset that characterises the facility in question. These inadequacies may include information on as built geometry and materials of construction. By the application of automated retrospective data gathering for use in BIM, such problems should be largely overcome and significant benefits in terms of efficiency gains and cost savings should be achieved. Design/methodology/approach Laser scanning can be used to collect geometrical and spatial information in the form of a 3D point cloud, and this technique is already used. However, as a point cloud representation does not contain any semantic information or geometrical context, such point cloud data must refer to external sources of data, such as building specification and construction materials, to be in used in BIM. Findings Hyperspectral imaging techniques can be applied to provide both spectral and spatial information of scenes as a set of high-resolution images. Integrating of a 3D point cloud into hyperspectral images would enable accurate identification and classification of surface materials and would also convert the 3D representation to BIM. Originality/value This integrated approach has been applied in other areas, for example, in crop management. The transfer of this approach to facilities management and construction would improve the efficiency and automation of the data transition from building pathology to BIM. In this study, the technological feasibility and advantages of the integration of laser scanning and hyperspectral imaging (the latter not having previously been used in the construction context in its own right) is discussed, and an example of the use of a new integration technique is presented, applied for the first time in the context of buildings.

scholarly journals Lidar-equipped uav for building information modelling

2014 ◽  
Vol XL-5 ◽  
pp. 523-527 ◽  
Author(s):  
D. Roca ◽  
J. Armesto ◽  
S. Lagüela ◽  
L. Díaz-Vilariño
Keyword(s):  
Point Cloud ◽  
Electronic Devices ◽  
3D Models ◽  
Sensor Technology ◽  
Point Cloud Data ◽  
Building Information Modelling ◽  
Cloud Data ◽  
Building Information ◽  
Innovative Solution ◽  
Capture Point

The trend to minimize electronic devices in the last decades accounts for Unmanned Airborne Vehicles (UAVs) as well as for sensor technologies and imaging devices, resulting in a strong revolution in the surveying and mapping industries. However, only within the last few years the LIDAR sensor technology has achieved sufficiently reduction in terms of size and weight to be considered for UAV platforms. This paper presents an innovative solution to capture point cloud data from a Lidar-equipped UAV and further perform the 3D modelling of the whole envelope of buildings in BIM format. A mini-UAV platform is used (weigh less than 5 kg and up to 1.5 kg of sensor payload), and data from two different acquisition methodologies is processed and compared with the aim at finding the optimal configuration for the generation of 3D models of buildings for energy studies

Sign in / Sign up

Export Citation Format

Share Document