Journal articles: 'BIM Cloud'

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Du, Jing, Rui Liu, and Raja R. A. Issa. "BIM Cloud Score: Benchmarking BIM Performance." Journal of Construction Engineering and Management 140, no. 11 (November 2014): 04014054. http://dx.doi.org/10.1061/(asce)co.1943-7862.0000891.

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Qin, Guocheng, Yin Zhou, Kaixin Hu, Daguang Han, and Chunli Ying. "Automated Reconstruction of Parametric BIM for Bridge Based on Terrestrial Laser Scanning Data." Advances in Civil Engineering 2021 (January 7, 2021): 1–17. http://dx.doi.org/10.1155/2021/8899323.

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Building information modeling (BIM) in industrialized bridge construction is usually performed based on initial design information. Differences exist between the model of the structure and its actual geometric dimensions and features due to the manufacturing, transportation, hoisting, assembly, and load bearing of the structure. These variations affect the construction project handover and facility management. The solutions available at present entail the use of point clouds to reconstruct BIM. However, these solutions still encounter problems, such as the inability to obtain the actual geometric features of a bridge quickly and accurately. Moreover, the created BIM is nonparametric and cannot be dynamically adjusted. This paper proposes a fully automatic method of reconstructing parameterized BIM by using point clouds to address the abovementioned problems. An algorithm for bridge point cloud segmentation is developed; the algorithm can separate the bridge point cloud from the entire scanning scene and segment the unit structure point cloud. Another algorithm for extracting the geometric features of the bridge point cloud is also proposed; this algorithm is effective for partially missing point clouds. The feasibility of the proposed method is evaluated and verified using theoretical and actual bridge point clouds, respectively. The reconstruction quality of BIM is also evaluated visually and quantitatively, and the results show that the reconstructed BIM is accurate and reliable.

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Qin, Guocheng, Yin Zhou, Kaixin Hu, Daguang Han, and Chunli Ying. "Automated Reconstruction of Parametric BIM for Bridge Based on Terrestrial Laser Scanning Data." Advances in Civil Engineering 2021 (January 7, 2021): 1–17. http://dx.doi.org/10.1155/2021/8899323.

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Building information modeling (BIM) in industrialized bridge construction is usually performed based on initial design information. Differences exist between the model of the structure and its actual geometric dimensions and features due to the manufacturing, transportation, hoisting, assembly, and load bearing of the structure. These variations affect the construction project handover and facility management. The solutions available at present entail the use of point clouds to reconstruct BIM. However, these solutions still encounter problems, such as the inability to obtain the actual geometric features of a bridge quickly and accurately. Moreover, the created BIM is nonparametric and cannot be dynamically adjusted. This paper proposes a fully automatic method of reconstructing parameterized BIM by using point clouds to address the abovementioned problems. An algorithm for bridge point cloud segmentation is developed; the algorithm can separate the bridge point cloud from the entire scanning scene and segment the unit structure point cloud. Another algorithm for extracting the geometric features of the bridge point cloud is also proposed; this algorithm is effective for partially missing point clouds. The feasibility of the proposed method is evaluated and verified using theoretical and actual bridge point clouds, respectively. The reconstruction quality of BIM is also evaluated visually and quantitatively, and the results show that the reconstructed BIM is accurate and reliable.

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Zheng, Rongyue, Jianlin Jiang, Xiaohan Hao, Wei Ren, Feng Xiong, and Yi Ren. "bcBIM: A Blockchain-Based Big Data Model for BIM Modification Audit and Provenance in Mobile Cloud." Mathematical Problems in Engineering 2019 (March 18, 2019): 1–13. http://dx.doi.org/10.1155/2019/5349538.

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Building Information Modeling (BIM) is envisioned as an indispensable opportunity in the architecture, engineering, and construction (AEC) industries as a revolutionary technology and process. Smart construction relies on BIM for manipulating information flow, data flow, and management flow. Currently, BIM model has been explored mainly for information construction and utilization, but rare works pay efforts to information security, e.g., critical model audit and sensitive model exposure. Moreover, few BIM systems are proposed to chase after upcoming computing paradigms, such as mobile cloud computing, big data, blockchain, and Internet of Things. In this paper, we make the first attempt to propose a novel BIM system model called bcBIM to tackle information security in mobile cloud architectures. More specifically, bcBIM is proposed to facilitate BIM data audit for historical modifications by blockchain in mobile cloud with big data sharing. The proposed bcBIM model can guide the architecture design for further BIM information management system, especially for integrating BIM cloud as a service for further big data sharing. We propose a method of BIM data organization based on blockchains and discuss it based on private and public blockchain. It guarantees to trace, authenticate, and prevent tampering with BIM historical data. At the same time, it can generate a unified format to support future open sharing, data audit, and data provenance.

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Logothetis, S., E. Karachaliou, E. Valari, and E. Stylianidis. "OPEN SOURCE CLOUD-BASED TECHNOLOGIES FOR BIM." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-2 (May 30, 2018): 607–14. http://dx.doi.org/10.5194/isprs-archives-xlii-2-607-2018.

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This paper presents a Cloud-based open source system for storing and processing data from a 3D survey approach. More specifically, we provide an online service for viewing, storing and analysing BIM. Cloud technologies were used to develop a web interface as a BIM data centre, which can handle large BIM data using a server. The server can be accessed by many users through various electronic devices anytime and anywhere so they can view online 3D models using browsers. Nowadays, the Cloud computing is engaged progressively in facilitating BIM-based collaboration between the multiple stakeholders and disciplinary groups for complicated Architectural, Engineering and Construction (AEC) projects. Besides, the development of Open Source Software (OSS) has been rapidly growing and their use tends to be united. Although BIM and Cloud technologies are extensively known and used, there is a lack of integrated open source Cloud-based platforms able to support all stages of BIM processes. The present research aims to create an open source Cloud-based BIM system that is able to handle geospatial data. In this effort, only open source tools will be used; from the starting point of creating the 3D model with FreeCAD to its online presentation through BIMserver. Python plug-ins will be developed to link the two software which will be distributed and freely available to a large community of professional for their use. The research work will be completed by benchmarking four Cloud-based BIM systems: Autodesk BIM 360, BIMserver, Graphisoft BIMcloud and Onuma System, which present remarkable results.

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Yoon, Su-Won, Byung-Kon Kim, Jong-Moon Choi, and Soon-Wook Kwon. "A Prototype BIM Server based viewer for Cloud Computing BIM Services." Journal of The Korean Society of Civil Engineers 33, no. 4 (July 30, 2013): 1719–30. http://dx.doi.org/10.12652/ksce.2013.33.4.1719.

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Bi, Zhen Bo, and Hui Qin Wang. "BIM Application Research Based on Cloud Computing." Applied Mechanics and Materials 170-173 (May 2012): 3565–69. http://dx.doi.org/10.4028/www.scientific.net/amm.170-173.3565.

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Applications based on CC (cloud computing) has the potential efficient and low-cost advantages, while there are the lack of computing power, the limited range of applications and the higher cost of BIM (Building Information Model) applications in the traditional desktop mode. According to BIM application features and the actual situation, the paper starts from the concept of CC and discusses the advantages of BIM applications using CC. The system framework, the key technologies and the implementation methods of the BIM application platform based on CC have been put forward on the basis of the above discussion.

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Voříšek, Jan, Bořek Patzák, Edita Dvořáková, and Daniel Rypl. "AUTOMATED BIM ENTITY RECONSTRUCTION FROM UNSTRUCTURED 3D POINTCLOUDS." Acta Polytechnica CTU Proceedings 30 (April 22, 2021): 126–30. http://dx.doi.org/10.14311/app.2021.30.0126.

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Laser scanning is used widely in architecture and construction to document existing buildings by providing accurate data for creating a 3D model. The output is a set of data points in space, so-called point cloud. While point clouds can be directly rendered and inspected, they do not hold any semantics. Typically, engineers manually obtain floor plans, structural models, or the whole BIM model, which is a very time-consuming task for large building projects. In this contribution, we present the design and concept of a PointCloud2BIM library [1]. It provides a set of algorithms for automated or user assisted detection of fundamental entities from scanned point cloud data sets, such as floors, rooms, walls, and openings, and identification of the mutual relationships between them. The entity detection is based on a reasonable degree of human interaction (i.e., expected wall thickness). The results reside in a platform-agnostic JSON database allowing future integration into any existing BIM software.

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Ham, Namhyuk, Baek-Il Bae, and Ok-Kyung Yuh. "Phased Reverse Engineering Framework for Sustainable Cultural Heritage Archives Using Laser Scanning and BIM: The Case of the Hwanggungwoo (Seoul, Korea)." Sustainability 12, no. 19 (October 1, 2020): 8108. http://dx.doi.org/10.3390/su12198108.

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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.

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Gülch, E., and L. Obrock. "AUTOMATED SEMANTIC MODELLING OF BUILDING INTERIORS FROM IMAGES AND DERIVED POINT CLOUDS BASED ON DEEP LEARNING METHODS." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIII-B2-2020 (August 12, 2020): 421–26. http://dx.doi.org/10.5194/isprs-archives-xliii-b2-2020-421-2020.

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Abstract. In this paper, we present an improved approach of enriching photogrammetric point clouds with semantic information extracted from images to enable a later automation of BIM modelling. Based on the DeepLabv3+ architecture, we use Semantic Segmentation of images to extract building components and objects of interiors. During the photogrammetric reconstruction, we project the segmented categories into the point cloud. Any interpolations that occur during this process are corrected automatically and we achieve a mIoU of 51.9 % in the classified point cloud. Based on the semantic information, we align the point cloud, correct the scale and extract further information. Our investigation confirms that utilizing photogrammetry and Deep Learning to generate a semantically enriched point cloud of interiors achieves good results. The combined extraction of geometric and semantic information yields a high potential for automated BIM model reconstruction.

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Bonduel, M., M. Bassier, M. Vergauwen, P. Pauwels, and R. Klein. "SCAN-TO-BIM OUTPUT VALIDATION: TOWARDS A STANDARDIZED GEOMETRIC QUALITY ASSESSMENT OF BUILDING INFORMATION MODELS BASED ON POINT CLOUDS." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-2/W8 (November 13, 2017): 45–52. http://dx.doi.org/10.5194/isprs-archives-xlii-2-w8-45-2017.

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The use of Building Information Modeling (BIM) for existing buildings based on point clouds is increasing. Standardized geometric quality assessment of the BIMs is needed to make them more reliable and thus reusable for future users. First, available literature on the subject is studied. Next, an initial proposal for a standardized geometric quality assessment is presented. Finally, this method is tested and evaluated with a case study. The number of specifications on BIM relating to existing buildings is limited. The Levels of Accuracy (LOA) specification of the USIBD provides definitions and suggestions regarding geometric model accuracy, but lacks a standardized assessment method. A deviation analysis is found to be dependent on (1) the used mathematical model, (2) the density of the point clouds and (3) the order of comparison. Results of the analysis can be graphical and numerical. An analysis on macro (building) and micro (BIM object) scale is necessary. On macro scale, the complete model is compared to the original point cloud and vice versa to get an overview of the general model quality. The graphical results show occluded zones and non-modeled objects respectively. Colored point clouds are derived from this analysis and integrated in the BIM. On micro scale, the relevant surface parts are extracted per BIM object and compared to the complete point cloud. Occluded zones are extracted based on a maximum deviation. What remains is classified according to the LOA specification. The numerical results are integrated in the BIM with the use of object parameters.

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Badenko, Vladimir, Dmitry Volgin, and Sergey Lytkin. "Deformation monitoring using laser scanned point clouds and BIM." MATEC Web of Conferences 245 (2018): 01002. http://dx.doi.org/10.1051/matecconf/201824501002.

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Laser scanning is an essential method for monitoring of the operation of buildings or structures. It involves creating as-is BIM from point clouds obtained from laser scanning. In this article we present our workflow for the generation of information model from 3D point clouds of concrete tetrapod blocks on navigable structure C-1. Point cloud processing method for making informational model for long term monitoring is described. As a result of the research BIM model with each tetrapod was created for deformational monitoring in the comparison with next year model. Finally, we identify and discuss technology gaps that need to be addressed in future research.

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Martín-Lerones, Pedro, David Olmedo, Ana López-Vidal, Jaime Gómez-García-Bermejo, and Eduardo Zalama. "BIM Supported Surveying and Imaging Combination for Heritage Conservation." Remote Sensing 13, no. 8 (April 19, 2021): 1584. http://dx.doi.org/10.3390/rs13081584.

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As the basis for analysis and management of heritage assets, 3D laser scanning and photogrammetric 3D reconstruction have been probed as adequate techniques for point cloud data acquisition. The European Directive 2014/24/EU imposes BIM Level 2 for government centrally procured projects as a collaborative process of producing federated discipline-specific models. Although BIM software resources are intensified and increasingly growing, distinct specifications for heritage (H-BIM) are essential to driving particular processes and tools to efficiency shifting from point clouds to meaningful information ready to be exchanged using non-proprietary formats, such as Industry Foundation Classes (IFC). This paper details a procedure for processing enriched 3D point clouds into the REVIT software package due to its worldwide popularity and how closely it integrates with the BIM concept. The procedure will be additionally supported by a tailored plug-in to make high-quality 3D digital survey datasets usable together with 2D imaging, enhancing the capability to depict contextualized important graphical data to properly planning conservation actions. As a practical example, a 2D/3D enhanced combination is worked to accurately include into a BIM project, the length, orientation, and width of a big crack on the walls of the Castle of Torrelobatón (Spain) as a representative heritage building.

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Capocchiano, F., and R. Ravanelli. "AN ORIGINAL ALGORITHM FOR BIM GENERATION FROM INDOOR SURVEY POINT CLOUDS." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-2/W13 (June 5, 2019): 769–76. http://dx.doi.org/10.5194/isprs-archives-xlii-2-w13-769-2019.

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Abstract. Nowadays, it is essential to find new strategies, able to perform the first step of the scan-to-BIM process, by retrieving the geometrical information contained in point clouds that are so easily collected through laser scanners and range cameras. This paper presents a new algorithm for the automatic extraction of the layout and the height of a small indoor environment from its point cloud. In particular, the algorithm was tested on a point cloud of 600000 vertices, selected from the dataset of the ISPRS benchmark on indoor modelling. The preliminary results are encouraging: the 3D shape (layout and height) of the investigated room is effectively reconstructed.

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Barazzetti, Luigi, Fabrizio Banfi, Raffaella Brumana, Gaia Gusmeroli, Mattia Previtali, and Giuseppe Schiantarelli. "Cloud-to-BIM-to-FEM: Structural simulation with accurate historic BIM from laser scans." Simulation Modelling Practice and Theory 57 (September 2015): 71–87. http://dx.doi.org/10.1016/j.simpat.2015.06.004.

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Macher, H., T. Landes, and P. Grussenmeyer. "Point clouds segmentation as base for as-built BIM creation." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences II-5/W3 (August 11, 2015): 191–97. http://dx.doi.org/10.5194/isprsannals-ii-5-w3-191-2015.

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In this paper, a three steps segmentation approach is proposed in order to create 3D models from point clouds acquired by TLS inside buildings. The three scales of segmentation are floors, rooms and planes composing the rooms. First, floor segmentation is performed based on analysis of point distribution along Z axis. Then, for each floor, room segmentation is achieved considering a slice of point cloud at ceiling level. Finally, planes are segmented for each room, and planes corresponding to ceilings and floors are identified. Results of each step are analysed and potential improvements are proposed. Based on segmented point clouds, the creation of as-built BIM is considered in a future work section. Not only the classification of planes into several categories is proposed, but the potential use of point clouds acquired outside buildings is also considered.

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Li, Sai, Zhongjian Zhang, Gang Mei, Daming Lin, Jin Yu, Renke Qiu, Xingju Su, Xuechun Lin, and Chonghua Lou. "UTILIZATION OF BIM IN THE CONSTRUCTION OF A SUBMARINE TUNNEL: A CASE STUDY IN XIAMEN CITY, CHINA." JOURNAL OF CIVIL ENGINEERING AND MANAGEMENT 27, no. 1 (January 11, 2021): 14–26. http://dx.doi.org/10.3846/jcem.2021.14098.

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Building information modeling (BIM) is an emerging technology that can effectively solve the problems of information dispersion, complex personnel management, and lack of construction supervision, which often occur during the construction of tunnel engineering. Taking the construction of Haicang Tunnel in Xiamen, China as a case study, the utilization of BIM technology in the design stage, the construction simulation and operation are demonstrated during the full-life cycle of the project. During the construction of Haicang Tunnel, the technologies of BIM 3D, BIM 4D, BIM 5D, and Cloud Platform are used to make the construction process controllable and to facilitate the implementation and deployment of construction plans. BIM 3D is a visualization method to show the detailed model in the construction. The design is optimized by the navigation collision function of BIM 3D. BIM 4D adds the time schedule into BIM 3D model to show the construction schedule. BIM 5D adds the cost into BIM 4D model to show the construction consumption. The methods of BIM 4D and BIM 5D can assist the engineering management in allocating resources and funds in the project. Cloud Platform is used to effectively implement information management.

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Li, Sai, Zhongjian Zhang, Gang Mei, Daming Lin, Jin Yu, Renke Qiu, Xingju Su, Xuechun Lin, and Chonghua Lou. "UTILIZATION OF BIM IN THE CONSTRUCTION OF A SUBMARINE TUNNEL: A CASE STUDY IN XIAMEN CITY, CHINA." JOURNAL OF CIVIL ENGINEERING AND MANAGEMENT 27, no. 1 (January 11, 2021): 14–26. http://dx.doi.org/10.3846/jcem.2021.14098.

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Building information modeling (BIM) is an emerging technology that can effectively solve the problems of information dispersion, complex personnel management, and lack of construction supervision, which often occur during the construction of tunnel engineering. Taking the construction of Haicang Tunnel in Xiamen, China as a case study, the utilization of BIM technology in the design stage, the construction simulation and operation are demonstrated during the full-life cycle of the project. During the construction of Haicang Tunnel, the technologies of BIM 3D, BIM 4D, BIM 5D, and Cloud Platform are used to make the construction process controllable and to facilitate the implementation and deployment of construction plans. BIM 3D is a visualization method to show the detailed model in the construction. The design is optimized by the navigation collision function of BIM 3D. BIM 4D adds the time schedule into BIM 3D model to show the construction schedule. BIM 5D adds the cost into BIM 4D model to show the construction consumption. The methods of BIM 4D and BIM 5D can assist the engineering management in allocating resources and funds in the project. Cloud Platform is used to effectively implement information management.

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Bassier, Maarten, and Maarten Vergauwen. "Topology Reconstruction of BIM Wall Objects from Point Cloud Data." Remote Sensing 12, no. 11 (June 2, 2020): 1800. http://dx.doi.org/10.3390/rs12111800.

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The processing of remote sensing measurements to Building Information Modeling (BIM) is a popular subject in current literature. An important step in the process is the enrichment of the geometry with the topology of the wall observations to create a logical model. However, this remains an unsolved task as methods struggle to deal with the noise, incompleteness and the complexity of point cloud data of building scenes. Current methods impose severe abstractions such as Manhattan-world assumptions and single-story procedures to overcome these obstacles, but as a result, a general data processing approach is still missing. In this paper, we propose a method that solves these shortcomings and creates a logical BIM model in an unsupervised manner. More specifically, we propose a connection evaluation framework that takes as input a set of preprocessed point clouds of a building’s wall observations and compute the best fit topology between them. We transcend the current state of the art by processing point clouds of both straight, curved and polyline-based walls. Also, we consider multiple connection types in a novel reasoning framework that decides which operations are best fit to reconstruct the topology of the walls. The geometry and topology produced by our method is directly usable by BIM processes as it is structured conform the IFC data structure. The experimental results conducted on the Stanford 2D-3D-Semantics dataset (2D-3D-S) show that the proposed method is a promising framework to reconstruct complex multi-story wall elements in an unsupervised manner.

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Lee, Kyuhyup, Joonghwan Shin, Soonwook Kwon, Chung-Suk Cho, and Suwan Chung. "BIM Environment Based Virtual Desktop Infrastructure (VDI) Resource Optimization System for Small to Medium-Sized Architectural Design Firms." Applied Sciences 11, no. 13 (July 2, 2021): 6160. http://dx.doi.org/10.3390/app11136160.

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The recent fourth industrial revolution and the era of post-COVID-19 have ushered in a series of technologies including a 5G network and online systems, such as cloud computing technology. In other industries, extensive studies on cloud platforms utilizing such technologies were conducted. Although the cloud environment has taken on greater importance in the construction sector as well, it was used only for servers, failing to fully reflect the characteristics of the cloud system. In particular, compared to large architectural design firms, it is challenging for small to medium-sized design firms to establish a virtual cloud computing environment, which requires high capital investment. Targeting small to medium-sized architectural design firms in Korea, this study was conducted to introduce the VDI system, one of the cloud computing technologies that was recently used in other industries, to the BIM environment for initial application, operation, and management. Specifically, after an analysis was carried out to see if the VDI system utilized in other industries may resolve the hindrance faced with the BIM environment in the construction industry, the KBimVdi system was created based on an algorithm for estimating server scales by analyzing the VDI system suitable for the BIM work environment. This was followed by a validation of the KBimVdi system based on selected projects carried out by small to medium-sized architectural firms where BIM was used for design work.

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Leoni, C., S. Ferrarese, W. Wahbeh, and C. Nardinocchi. "EXTRACTION OF MAIN LEVELS OF A BUILDING FROM A LARGE POINT CLOUD." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-5/W2 (September 20, 2019): 41–47. http://dx.doi.org/10.5194/isprs-archives-xlii-5-w2-41-2019.

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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.

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Bassier, M., L. Mattheuwsen, and M. Vergauwen. "BIM RECONSTRUCTION: AUTOMATED PROCEDURAL MODELING FROM POINT CLOUD DATA." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-2/W17 (November 29, 2019): 53–60. http://dx.doi.org/10.5194/isprs-archives-xlii-2-w17-53-2019.

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Abstract. The reconstruction of Building Information Modeling objects for as-built modeling is currently the subject of ongoing research. A popular method is to extract structure information from point cloud data to create a set of parametric objects. This requires the interpretation of the point cloud data which currently is a manual and labor intensive procedure. Automated processes have to cope with excessive occlusions and clutter in the data sets. To create an as-built BIM, it is vital to reconstruct the building’s structure i.e. wall geometry prior to the reconstruction of other objects.In this work, a novel method is presented to automatically reconstruct as-built BIM for generic buildings. We presented an unsupervised method that procedurally models the geometry of the walls based on point cloud data. A bottom-up process is defined where consecutively higher level information is extracted from the point cloud data using pre-trained machine learning models. Prior to the reconstruction, the data is segmented, classified and clustered to retrieve all the available observations of the walls. The resulting geometry is processed by the reconstruction algorithm. First, the necessary information is extracted from the observations for the creation of parametric solid objects. Subsequently, the final walls are created by updating their topology. The method is tested on a variety of scenes and shows promising results to reliably and accurately create as-built models. The accuracy of the generated geometry is similar to the precision of expert modelers. A key advantage is that that the algorithm creates Revit and Rhino native objects which makes the geometry directly applicable to a wide range of applications.

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Ding, Lieyun, and Xun Xu. "Application of Cloud Storage on BIM Life-Cycle Management." International Journal of Advanced Robotic Systems 11, no. 8 (January 2014): 129. http://dx.doi.org/10.5772/58443.

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Juan, Du, and Qin Zheng. "Cloud and Open BIM-Based Building Information Interoperability Research." Journal of Service Science and Management 07, no. 02 (2014): 47–56. http://dx.doi.org/10.4236/jssm.2014.72005.

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Onungwa, Ihuoma, Nnezi Olugu-Uduma, and Dennis R. Shelden. "Cloud BIM Technology as a Means of Collaboration and Project Integration in Smart Cities." SAGE Open 11, no. 3 (July 2021): 215824402110332. http://dx.doi.org/10.1177/21582440211033250.

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Building Information Modeling (BIM) was created to address the Architecture, Engineering, and Construction (AEC) industry’s lack of collaboration among consultants. Advances in cloud BIM have led to the easy exchange of data and real-time collaboration among consultants from conceptual design to the detailed construction drawing stage and through the project life cycle. This is critical in the development of smart cities. Cloud BIM also facilitates visualization of the city and data exchange for internet of things (IoT). Smart city development involves incorporating data from sensors and hardware attached to existing infrastructure. This article studies cloud BIM technology as a means of project integration in smart city development. To do this, a case study of digital modeling for the development of a smart city was done. Benefits include seamless communication, monitoring real-time progress, and visualization of files. Problems encountered include governance problems, problems preserving work sets, the integrity of drawings, and difficulty specifying coordinates on-site.

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Diara, Filippo, and Fulvio Rinaudo. "ARK-BIM: Open-Source Cloud-Based HBIM Platform for Archaeology." Applied Sciences 11, no. 18 (September 21, 2021): 8770. http://dx.doi.org/10.3390/app11188770.

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In recent years, Historic Building Information Modelling (HBIM) methodology has strengthened the documentation and interpretation of archaeological contexts and is regarded as a breakthrough in relation to established methodologies and analyses. Change is also taking place regarding web and cloud-based solutions, and this work acknowledges the importance of cloud-based and web HBIM solutions applied to Cultural Heritage assets and archaeology. More than ever, online platforms are becoming useful services to ease data exchange and validation between collaborators and stakeholders, establishing multidisciplinary approaches. Despite the presence of different cloud-based platforms, Heritage asset documentation can hardly be managed by environments or software developed for architecture and construction design. For this reason, this project is strongly founded on four pillars: online documentation, collaboration, communication and accessibility. Cognisant of these needs, the paper is aimed at the development of a custom HBIM cloud platform for archaeology, on the basis of the BIMData open-source online environment. This platform, called ARK-BIM, can be considered a modular solution leaning on HTML, JavaScript, VueJS, XEOKIT and open-source languages.

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Baik, A. "FROM POINT CLOUD TO EXISTING BIM FOR MODELLING AND SIMULATION PURPOSES." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-5/W2 (September 20, 2019): 15–19. http://dx.doi.org/10.5194/isprs-archives-xlii-5-w2-15-2019.

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Abstract. Many BIM experts agree that employing BIM for new construction is an easy task. However, applying BIM to existing construction will be difficult but is more suitable for heritage buildings cases. These heritage buildings have unique façades and architectural vocabulary, which are of special interest. Furthermore, studying these architecture heritages require some advanced tools in order to understand and analyse their structure, components, and design. Relying only on traditional methods is not adequate, especially for architectural engineers and experts who need digital representations of architectural heritage in order to draw a complete image of any aspect of the project. Moreover, lots of these heritage architectural elements are not documented or provided in the digital architectural libraries, which in turn requires advanced and easy access methods and tools that can extract basic information professionally and explain the essence of heritage. BIM has emerged as an efficient solution that could possibly help in analysing architectural heritage through effective learning processes. Existing BIM is characterised by their ability to create and operate within a digital database of any existing by 3-D laser through scanning the building and transforming it into point-cloud as digital data, so that engineers and experts can work on existing and buildings via the BIM software. As with many heritage buildings in the world, many of the heritage buildings in the Historic district of Jeddah city, Saudi Arabia, face serious issues in terms of conservation, restoration, documentation, managing, recording, and monitoring of these valuable heritage buildings. Therefore, this paper will examine and evaluate the use of BIM in modelling and for simulation purposes, (e.g. structure and energy simulation) with regard to one of the existing heritage buildings in the Historic district of Jeddah.

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Qin, Guocheng, Ling Wang, YiMei Hou, HaoRan Gui, and YingHao Jian. "Construction and application of factory digital twin model based on BIM and point cloud." E3S Web of Conferences 293 (2021): 02031. http://dx.doi.org/10.1051/e3sconf/202129302031.

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The digital twin model of the factory is the basis for the construction of a digital factory, and the professional system of the factory is complex. The traditional BIM model is not completely consistent with the actual position of the corresponding component, and it is difficult to directly replace the digital twin model. In response to this situation, relying on a certain factory project, the point cloud is used to eliminate the positional deviation between the BIM model and the factory during the construction phase, improve the efficiency and accuracy and reliability of model adjustment and optimization, and , realize the conversion from BIM model to digital twin model. A novel algorithm is developed to quickly detect and evaluate the construction quality of the local structure of the factory, so as to input the initial deformation data of the structure into the corresponding model and feed back to the construction party for improvement. The results show that the digital twin model, which is highly consistent with the actual location of the factory components, not only lays a solid foundation for the construction of a digital factory, but also further deepens the integration and application of BIM and point clouds.

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Motawa, Ibrahim. "Spoken dialogue BIM systems – an application of big data in construction." Facilities 35, no. 13/14 (October 3, 2017): 787–800. http://dx.doi.org/10.1108/f-01-2016-0001.

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Purpose With the rapid development in the internet technologies, the applications of big data in construction have seen considerable attention. Currently, there are many input/output modes of capturing construction knowledge related to all construction stages. On the other hand, building information modelling (BIM) systems have been developed to help in storing various structured data of buildings. However, these systems cannot fully capture the knowledge and unstructured data used in the operation of building systems in a usable format that uses the intelligent capabilities of BIM systems. Therefore, this research aims to adopt the concept of big data and develop a spoken dialogue BIM system to capture buildings operation knowledge, particularly for building maintenance and refurbishment. Design/methodology/approach The proposed system integrates cloud-based spoken dialogue system and case-based reasoning BIM system. Findings The system acts as an interactive expert agent that seeks answers from the user for questions specific to building maintenance problems and helps searching for solutions from previously stored knowledge cases. The practices of monitoring and maintaining buildings performance can be more efficient by the retrieval of relevant solutions from the captured knowledge to new problems when maintaining buildings components. The developed system enables easier capture and search for solutions to new problems with a more comprehensive retrieval of information. Originality/value Capturing multi-modes data into BIM systems using the cloud-based spoken dialogue systems will help construction teams use the high volume of data generated over building lifecycle and search for the most suitable solutions for maintenance problems. This new area of research also contributes to the current BIM systems by advancing their capabilities to instantly capture and retrieve knowledge of operations instead of only information.

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Barazzetti, Luigi, Mattia Previtali, and Marco Scaioni. "Roads Detection and Parametrization in Integrated BIM-GIS Using LiDAR." Infrastructures 5, no. 7 (July 1, 2020): 55. http://dx.doi.org/10.3390/infrastructures5070055.

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Building Information Modeling (BIM) has a crucial role in smart road applications, not only limited to the design and construction stages, but also to traffic monitoring, autonomous vehicle navigation, road condition assessment, and real-time data delivery to drivers, among others. Point clouds collected through LiDAR are a powerful solution to capture as-built conditions, notwithstanding the lack of commercial tools able to automatically reconstruct road geometry in a BIM environment. This paper illustrates a two-step procedure in which roads are automatically detected and classified, providing GIS layers with basic road geometry that are turned into parametric BIM objects. The proposed system is an integrated BIM-GIS with a structure based on multiple proposals, in which a single project file can handle different versions of the model using a variable level of detail. The model is also refined by adding parametric elements for buildings and vegetation. Input data for the integrated BIM-GIS can also be existing cartographic layers or outputs generated with algorithms able to handle LiDAR data. This makes the generation of the BIM-GIS more flexible and not limited to the use of specific algorithms for point cloud processing.

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Yoon, S., J. Jung, and J. Heo. "PRACTICAL IMPLEMENTATION OF SEMI-AUTOMATED AS-BUILT BIM CREATION FOR COMPLEX INDOOR ENVIRONMENTS." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-4/W5 (May 11, 2015): 143–46. http://dx.doi.org/10.5194/isprsarchives-xl-4-w5-143-2015.

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In recent days, for efficient management and operation of existing buildings, the importance of as-built BIM is emphasized in AEC/FM domain. However, fully automated as-built BIM creation is a tough issue since newly-constructed buildings are becoming more complex. To manage this problem, our research group has developed a semi-automated approach, focusing on productive 3D as-built BIM creation for complex indoor environments. In order to test its feasibility for a variety of complex indoor environments, we applied the developed approach to model the ‘Charlotte stairs’ in Lotte World Mall, Korea. The approach includes 4 main phases: data acquisition, data pre-processing, geometric drawing, and as-built BIM creation. In the data acquisition phase, due to its complex structure, we moved the scanner location several times to obtain the entire point clouds of the test site. After which, data pre-processing phase entailing point-cloud registration, noise removal, and coordinate transformation was followed. The 3D geometric drawing was created using the RANSAC-based plane detection and boundary tracing methods. Finally, in order to create a semantically-rich BIM, the geometric drawing was imported into the commercial BIM software. The final as-built BIM confirmed that the feasibility of the proposed approach in the complex indoor environment.

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Hichri, N., C. Stefani, L. De Luca, P. Veron, and G. Hamon. "FROM POINT CLOUD TO BIM: A SURVEY OF EXISTING APPROACHES." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-5/W2 (July 22, 2013): 343–48. http://dx.doi.org/10.5194/isprsarchives-xl-5-w2-343-2013.

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Redmond, Alan, Alan Hore, Mustafa Alshawi, and Roger West. "Exploring how information exchanges can be enhanced through Cloud BIM." Automation in Construction 24 (July 2012): 175–83. http://dx.doi.org/10.1016/j.autcon.2012.02.003.

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Liu, Rui, Jing Du, Raja R. A. Issa, and Brittany Giel. "BIM Cloud Score: Building Information Model and Modeling Performance Benchmarking." Journal of Construction Engineering and Management 143, no. 4 (April 2017): 04016109. http://dx.doi.org/10.1061/(asce)co.1943-7862.0001251.

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Li, Yan, Xiong Gao, Xiaowei Liu, Ruijue Zhang, and Yansheng Wu. "Green Construction Evaluation System Based on BIM Distributed Cloud Service." IOP Conference Series: Earth and Environmental Science 760, no. 1 (April 1, 2021): 012055. http://dx.doi.org/10.1088/1755-1315/760/1/012055.

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Zheng, Rongyue, Jianlin Jiang, Xiaohan Hao, Wei Ren, Feng Xiong, and Tianqing Zhu. "CaACBIM: A Context-aware Access Control Model for BIM." Information 10, no. 2 (February 1, 2019): 47. http://dx.doi.org/10.3390/info10020047.

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A building information model (BIM) is of upmost importance with a full life-time cycle in architecture engineering and construction industry. Smart construction relies on BIM to manipulate information flow, data flow, and management flow. Currently, BIM has been explored mainly for information construction and utilization, but there exist few works concerning information security, e.g., audits of critical models and exposure of sensitive models. Moreover, few BIM systems have been proposed to make use of new computing paradigms, such as mobile cloud computing, blockchain and Internet of Things. In this paper, we propose a Context-aware Access Control (CaAC) model for BIM systems on mobile cloud architectures. BIM data can be confidentially accessed according to contexts in a fine-grained manner. We describe functions of CaAC formally by illustrating location-aware access control and time-aware access control. CaAC model can outperform role-based access control for preventing BIM data leakage by distinguishing contexts. In addition, grouping algorithms are also presented for flexibility, in which basic model (user grouping based on user role permissions) and advanced model (user grouping based on user requests) are differentiated. Compared with the traditional role-based access control model, security and feasibility of CaAC are remarkably improved by distinguishing an identical role with multiple contexts. The average efficiency is improved by 2 n / ( 2 n - p - q ) , and time complexity is O ( n ) .

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Gankhuyag, Uuganbayar, and Ji-Hyeong Han. "Automatic 2D Floorplan CAD Generation from 3D Point Clouds." Applied Sciences 10, no. 8 (April 19, 2020): 2817. http://dx.doi.org/10.3390/app10082817.

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In the architecture, engineering, and construction (AEC) industry, creating an indoor model of existing buildings has been a challenging task since the introduction of building information modeling (BIM). Because the process of BIM is primarily manual and implies a high possibility of error, the automated creation of indoor models remains an ongoing research. In this paper, we propose a fully automated method to generate 2D floorplan computer-aided designs (CADs) from 3D point clouds. The proposed method consists of two main parts. The first is to detect planes in buildings, such as walls, floors, and ceilings, from unstructured 3D point clouds and to classify them based on the Manhattan-World (MW) assumption. The second is to generate 3D BIM in the industry foundation classes (IFC) format and a 2D floorplan CAD using the proposed line-detection algorithm. We experimented the proposed method on 3D point cloud data from a university building, residential houses, and apartments and evaluated the geometric quality of a wall reconstruction. We also offer the source code for the proposed method on GitHub.

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Jun, Jin-Woo, Sang-Heon Lee, and Shin-Jo Eom. "Analysis of Applying the Mobile BIM Application based on Cloud Computing." Transactions of the Society of CAD/CAM Engineers 17, no. 5 (October 1, 2012): 342–52. http://dx.doi.org/10.7315/cadcam.2012.342.

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Yaagoubi, Reda, and Yehia Miky. "Developing a combined Light Detecting And Ranging (LiDAR) and Building Information Modeling (BIM) approach for documentation and deformation assessment of Historical Buildings." MATEC Web of Conferences 149 (2018): 02011. http://dx.doi.org/10.1051/matecconf/201814902011.

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Cultural heritage plays a fundamental role in preserving the collective memory of a nation. However, it is noted that many historical buildings suffer from serious deformation that may lead to deterioration or loss. In this paper, we propose an approach for documentation and deformation assessment of historical buildings based on the combination of Terrestrial Light Detecting And Ranging (LiDAR) technology and Building Information Models (BIM). In order to digitally archive the current state of a historical building, classical surveying techniques (Traversing, Levelling and GPS) are integrated with Terrestrial Laser scanner (TLS). A Leica Scan Station C10 is used to accomplish the 3D point cloud acquisition. In addition, Leica GNSS Viva GS15 receivers, a Leica Total Station TCR 1201+ and a Leica Runner 24 are used for classical surveying. The result is a 3D point cloud with high resolution, which is referenced according to the local geodetic reference system Ain el Abd UTM 37N. This point cloud is then used to create a 3D BIM that represents the ideal condition of the building. This BIM also contains some important architectural components of the historical building. To detect and assess the deformation of building’s parts that require an urgent intervention, a comparison between the 3D point cloud and the 3D BIM is performed. To achieve this goal, the main parts of the building in the BIM model (such as ceilings and walls) are compared with the corresponding segments of the 3D point cloud according to the normal vectors of each part. A case study that corresponds to a historical building in Jeddah Historical City named ’Robat Banajah’ is presented to illustrate the proposed approach. This building was built to serve pilgrims that want to perform the fifth pillar of Islam. Then, it was endowed (waqf) as a charity housing for widows and disabled. The results of assessing deformations of the case study show that some rooms are in a degraded condition requiring urgent restoration (distortions reach up to 22 cm), while other building parts are in a non-critical condition.

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Amano, Kinjiro, Eric C. W. Lou, and Rodger Edwards. "Integration of point cloud data and hyperspectral imaging as a data gathering methodology for refurbishment projects using building information modelling (BIM)." Journal of Facilities Management 17, no. 1 (February 4, 2019): 57–75. http://dx.doi.org/10.1108/jfm-11-2017-0064.

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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.

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Andriasyan, Mesrop, Juan Moyano, Juan Enrique Nieto-Julián, and Daniel Antón. "From Point Cloud Data to Building Information Modelling: An Automatic Parametric Workflow for Heritage." Remote Sensing 12, no. 7 (March 29, 2020): 1094. http://dx.doi.org/10.3390/rs12071094.

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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.

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Bassier, Maarten, Meisam Yousefzadeh, and Maarten Vergauwen. "Comparison of 2D and 3D wall reconstruction algorithms from point cloud data for as-built BIM." Journal of Information Technology in Construction 25 (March 2, 2020): 173–92. http://dx.doi.org/10.36680/j.itcon.2020.011.

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As-built Building Information Models (BIMs) are becoming increasingly popular in the Architectural, Engineering, Construction, Owner and Operator (AECOO) industry. These models reflect the state of the building up to as-built conditions. The production of these models for existing buildings with no prior BIM includes the segmentation and classification of point cloud data and the reconstruction of the BIM objects. The automation of this process is a must since the manual Scan-to-BIM procedure is both time-consuming and error prone. However, the automated reconstruction from point cloud data is still ongoing research with both 2D and 3D approaches being proposed. There currently is a gap in the literature concerning the quality assessment of the created entities. In this research, we present the empirical comparison of both strategies with respect to existing specifications. A 3D and a 2D reconstruction method are implemented and tested on a real life test case. The experiments focus on the reconstruction of the wall geometry from unstructured point clouds as it forms the basis of the model. Both presented approaches are unsupervised methods that segment, classify and create generic wall elements. The first method operates on the 3D point cloud itself and consists of a general approach for the segmentation and classification and a class-specific reconstruction algorithm for the wall geometry. The point cloud is first segmented into planar clusters, after which a Random Forests classifier is used with geometric and contextual features for the semantic labelling. The final wall geometry is created based on the 3D point clusters representing the walls. The second method is an efficient Manhattan-world scene reconstruction algorithm that simultaneously segments and classifies the point cloud based on point feature histograms. The wall reconstruction is considered an instance of image segmentation by representing the data as 2D raster images. Both methods have promising results towards the reconstruction of wall geometry of multi-story buildings. The experiments report that over 80% of the walls were correctly segmented by both methods. Furthermore, the reconstructed geometry is conform Level-of-Accuracy 20 for 88% of the data by the first method and for 55% by the second method despite the Manhattan-world scene assumption. The empirical comparison showcases the fundamental differences in both strategies and will support the further development of these methods.

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Wanigarathna, Nadeeshani, Keith Jones, Adrian Bell, and Georgios Kapogiannis. "Building information modelling to support maintenance management of healthcare built assets." Facilities 37, no. 7/8 (May 7, 2019): 415–34. http://dx.doi.org/10.1108/f-01-2018-0012.

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Purpose This paper aims to investigate how digital capabilities associated with building information modelling (BIM) can integrate a wide range of information to improve built asset management (BAM) decision-making during the in-use phase of hospital buildings. Design/methodology/approach A comprehensive document analysis and a participatory case study was undertaken with a regional NHS hospital to review the type of information that can be used to better inform BAM decision-making to develop a conceptual framework to improve information use during the health-care BAM process, test how the conceptual framework can be applied within a BAM division of a health-care organisation and develop a cloud-based BIM application. Findings BIM has the potential to facilitate better informed BAM decision-making by integrating a wide range of information related to the physical condition of built assets, resources available for BAM and the built asset’s contribution to health-care provision within an organisation. However, interdepartmental information sharing requires a significant level of time and cost investment and changes to information gathering and storing practices within the whole organisation. Originality/value This research demonstrated that the implementation of BIM during the in-use phase of hospital buildings is different to that in the design and construction phases. At the in-use phase, BIM needs to integrate and communicate information within and between the estates, facilities division and other departments of the organisation. This poses a significant change management task for the organisation’s information management systems. Thus, a strategically driven top-down organisational approach is needed to implement BIM for the in-use phase of hospital buildings.

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Wang, C., Y. Dai, N. El-Sheimy, C. Wen, G. Retscher, Z. Kang, and A. Lingua. "PROGRESS ON ISPRS BENCHMARK ON MULTISENSORY INDOOR MAPPING AND POSITIONING." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-2/W13 (June 5, 2019): 1709–13. http://dx.doi.org/10.5194/isprs-archives-xlii-2-w13-1709-2019.

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Abstract. This paper presents the design of the benchmark dataset on multisensory indoor mapping and position (MIMAP) which is sponsored by ISPRS scientific initiatives. The benchmark dataset including point clouds captured by indoor mobile laser scanning system (IMLS) in indoor environments of various complexity. The benchmark aims to stimulate and promote research in the following three fields: (1) SLAM-based indoor point cloud generation; (2) automated BIM feature extraction from point clouds, with an emphasis on the elements, such as floors, walls, ceilings, doors, windows, stairs, lamps, switches, air outlets, that are involved in building management and navigation tasks ; and (3) low-cost multisensory indoor positioning, focusing on the smartphone platform solution. MIMAP provides a common framework for the evaluation and comparison of LiDAR-based SLAM, BIM feature extraction, and smartphone indoor positioning methods.

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Altohami, Abubaker Basheer Abdalwhab, Nuzul Azam Haron, Aidi Hizami Ales@Alias, and Teik Hua Law. "Investigating Approaches of Integrating BIM, IoT, and Facility Management for Renovating Existing Buildings: A Review." Sustainability 13, no. 7 (April 2, 2021): 3930. http://dx.doi.org/10.3390/su13073930.

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The importance of building information is highly attached to the ability of conventional storing to provide professional analysis. The Internet of Things (IoT) and smart devices offer a vast amount of live data stored in heterogeneous repositories, and hence the need for smart methodologies to facilitate IoT–BIM integration is very crucial. The first step to better integrating IoT and Building Information Modeling (BIM) can be performed by implementing the Service-Oriented-Architecture (SOA) to combining software and other services by replacing the sematic information that was failed to display elements of indoor conditions. The other development is to create link that able to update static models towards real-time models using SOA approach. The existing approach relies on one-way interaction; however, developing two-way communication to mimic human cognitive has become very crucial. The high-tech approach requires highly involving Cloud computations to better connect IoT devices throughout Internet infrastructure. This approach is based on the integration of Building Information Modeling (BIM) with real-time data from IoT devices aiming at improving construction and operational efficiencies and to provide high-fidelity BIM models for numerous applications. The paper discusses challenges, limitations, and barriers that face BIM–IoT integration and simultaneously solves interoperability issues and Cloud computing. The paper provides a comprehensive review that explores and identifies common emerging areas of application and common design patterns of the traditional BIM-IoT integration followed by devising better methodologies to integrate IoT in BIM.

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Chien, Szu-cheng, Tzu-chun Chuang, Huei-Sheng Yu, Yi Han, Boon Hee Soong, and King Jet Tseng. "Implementation of Cloud BIM-based Platform Towards High-performance Building Services." Procedia Environmental Sciences 38 (2017): 436–44. http://dx.doi.org/10.1016/j.proenv.2017.03.129.

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Arif, Farrukh, and Waleed Ahmed Khan. "A Real-Time Productivity Tracking Framework Using Survey-Cloud-BIM Integration." Arabian Journal for Science and Engineering 45, no. 10 (August 9, 2020): 8699–710. http://dx.doi.org/10.1007/s13369-020-04844-5.

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Maalek, Reza, Derek D. Lichti, and Janaka Y. Ruwanpura. "Automatic Recognition of Common Structural Elements from Point Clouds for Automated Progress Monitoring and Dimensional Quality Control in Reinforced Concrete Construction." Remote Sensing 11, no. 9 (May 8, 2019): 1102. http://dx.doi.org/10.3390/rs11091102.

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This manuscript provides a robust framework for the extraction of common structural components, such as columns, from terrestrial laser scanning point clouds acquired at regular rectangular concrete construction projects. The proposed framework utilizes geometric primitive as well as relationship-based reasoning between objects to semantically label point clouds. The framework then compares the extracted objects to the planned building information model (BIM) to automatically identify the as-built schedule and dimensional discrepancies. A novel method was also developed to remove redundant points of a newly acquired scan to detect changes between consecutive scans independent of the planned BIM. Five sets of point cloud data were acquired from the same construction site at different time intervals to assess the effectiveness of the proposed framework. In all datasets, the framework successfully extracted 132 out of 133 columns and achieved an accuracy of 98.79% for removing redundant surfaces. The framework successfully determined the progress of concrete work at each epoch in both activity and project levels through earned value analysis. It was also shown that the dimensions of 127 out of the 132 columns and all the slabs complied with those in the planned BIM.

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Tran, H., and K. Khoshelham. "BUILDING CHANGE DETECTION THROUGH COMPARISON OF A LIDAR SCAN WITH A BUILDING INFORMATION MODEL." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-2/W13 (June 5, 2019): 889–93. http://dx.doi.org/10.5194/isprs-archives-xlii-2-w13-889-2019.

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Abstract. Building Information Models (BIMs) are of paramount importance in lifecycle management of buildings as they enable collaboration among various stakeholders at different phases of a construction project, from planning to maintenance and operation. However, there is usually inconsistency between the as-is condition of the building and its existing BIM, because BIMs are generally not updated to reflect changes in the environment. Monitoring the changes during a building’s lifecycle and keeping the BIM up-to-date is useful for a variety of applications. Yet this process often involves manual surveying inspections, which are very time-consuming, error-prone, and laborious. In this paper, we present an automated approach for building change detection through a comparison between the BIM and a point cloud of the building indoor environment. The approach is based on point classification and surface coverage to identify discrepancies between the BIM and the point cloud. Experiments on a synthetic dataset and an ISPRS Benchmark dataset show the potential of the proposed approach not only for change detection and identifying discrepancies, but also for locating the removed and new structures of the building in comparison with the BIM. The results are useful for updating the BIM to represent the as-is condition of the building and for temporal analysis of changes during a building’s lifecycle.

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Liu, H., M. Hou, A. Li, and L. Xie. "AN AUTOMATIC EXTRACTION METHOD FOR THE PARAMETERS OF MULTI-LOD BIM MODELS FOR TYPICAL COMPONENTS OF WOODEN ARCHITECTURAL HERITAGE." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-2/W15 (August 23, 2019): 679–85. http://dx.doi.org/10.5194/isprs-archives-xlii-2-w15-679-2019.

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Abstract. A demand-oriented Building Information Model (BIM) model built using high-fidelity point cloud data can better protect architectural heritage. The multi-level detail (mutli-LoD) parametric model emphasizes the different protection requirements of typical components and the automatic extraction of corresponding parameters of high-fidelity point clouds, which are two related key issues. Taking the typical Chinese wooden architectural heritage as an example, according to different requirements, the multi-LoD principle of typical components is proposed. On this basis, the automatic extraction method of the above parameters is developed, and the key parameters of the method are recommended. In order to solve the above problems, taking the three typical Dou-Gong used in Liao Dynasty and Song Dynasty, including Zhutou Puzuo, Bujian Puzuo and Zhuanjiao Puzuo, as an example, briefly introduced the standardization characteristics of the typical components of the "Yingzao Fashi". Subsequently, the corresponding multiple LoD principles are recommended according to different requirements. Based on this and high-fidelity point cloud data, an automatic extraction method for multi-LoD BIM model parameters for typical components of wooden architectural heritage is proposed.

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Journal articles on the topic 'BIM Cloud'

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