Building Object Models Research Articles

Semantic Enrichment of Non-Graphical Data of a BIM Model of a Public Building from the Perspective of the Facility Manager

Building information modeling (BIM) is undeniably the most important trend in the digitization of the construction sector in recent years. BIM models currently being built are extremely geometrically rich, that is, they are modeled at a high level of detail in terms of geometry. Thanks to object-oriented programming paradigms, BIM models include high-level relationships to ensure interactions between objects, rapid view generation, and documentation. However, these models are not always equally rich in non-graphical data. This is true for parameters at the library object level, with which building object models are saturated, but also at the project, site, building, or floor levels according to the structure of the interoperable industry foundation classes (IFC) format. The current state of knowledge also lacks a clear methodology for inputting such data. For this reason, experimental work was undertaken on semantic enrichment in non-graphical data of a public building (a public kindergarten, Secemin, Poland), which has its BIM model at a high level of geometric detail but is poor in non-graphical data. As a result of the research and development work, all levels of the IFC structure were saturated with non-graphical data and validated, and the possibilities of their use were shown from the perspective of the facility manager. Documentation from the manager was used to achieve this goal, and selected analyses and simulations were performed on the enriched model. This article contributes to the discussion on semantic enrichment from CAD3D to BIM by presenting a detailed process for entering non-graphical data into a BIM model. The presented data entry method can be used by both modelers and facility managers. Thus, this paper fills an important research gap related to semantic enrichment in non-graphical data at different levels of the IFC structure.

Information system of multi-stage analysis of the building of object models on a construction site

This study focuses on the development of a multi-stage analysis of building object models (BOM) on a construction site for modeling an “evolutionary” digital twin, by integrating building information modeling (BIM) technology and an artificial intelligence system. The concepts of photo modeling of the construction site using a group of moving cameras were outlined, as well as the possibility of integrating IoT technologies. The dynamic transition of real building structures into intermediate BIM representations of digital twins was investigated, with the prospect of enabling augmented reality technology. An artificial intelligence system combining Convolutional Neural Network (CNN) and Feed Forward Neural Network (FFNN) architectures has been developed as a comprehensive mechanism for the detection, categorization, and evaluation of BIM projects at all stages of their life cycle. The paper addresses the scaling prospects for the development of point cloud and mesh models, as well as the use of big data technology while optimizing the representation of the “evolutionary” BIM project of the digital twin of the construction site. The effectiveness of site conformance detection during the step-by-step construction of a BIM model, which shows consistency and provides a quantitative assessment of the processes occurring on the site, has been determined. The results of this research can be used to improve BIM modeling methods and concepts, in particular towards a multi-stage “evolutionary” representation of the digital twin of the construction site.

Differentiable Physics Simulation of Dynamics-Augmented Neural Objects

We present a differentiable pipeline for simulating the motion of objects that represent their geometry as a continuous density field parameterized as a deep network. This includes Neural Radiance Fields (NeRFs), and other related models. From the density field, we estimate the dynamical properties of the object, including its mass, center of mass, and inertia matrix. We then introduce a differentiable contact model based on the density field for computing normal and friction forces resulting from collisions. This allows a robot to autonomously build object models that are visually and dynamically accurate from still images and videos of objects in motion. The resulting Dynamics-Augmented Neural Objects (DANOs) are simulated with an existing differentiable simulation engine, Dojo, interacting with other standard simulation objects, such as spheres, planes, and robots specified as URDFs. A robot can use this simulation to optimize grasps and manipulation trajectories of neural objects, or to improve the neural object models through gradient-based real-to-simulation transfer. We demonstrate the pipeline to learn the coefficient of friction of a bar of soap from a real video of the soap sliding on a table. We also learn the coefficient of friction and mass of a Stanford bunny through interactions with a Panda robot arm from synthetic data, and we optimize trajectories in simulation for the Panda arm to push the bunny to a goal location.

The usage of ground laser scanning for construction and building informational modeling

The article defines ground laser scanning (GLS) as a process of total geodetic survey with the survey system, which measures the distance between the instrument and the object’s surface and records corresponding directions in horizontal and vertical planes. The components of GLS system and data obtained during the scanning are indicated. The necessity of processing the data obtained by GLS is pointed out. The main usage of laser scanning which is the obtaining of precise geometric characteristics of an object complemented with any attributive data is stated. Thus, GLS can be widely used in buildings and construction information modeling. Analyzed the range of Russian documents regulating common requirements and developing rules and the usage of information models of massive building objects for applied tasks during different object life-cycle phases as well as usage of contemporary project and survey technology, particularly GLS. The conclusion is made stating on the idea of information modeling supposes its usage containing information characterizes the building object model during the different phases of its life-cycle. In relation to stated facts the role and position of GLS in information model development of a construction site, executive and operational models of an object are pointed out.

POPULATING A LIBRARY OF REUSABLE H-BOMS: ASSESSMENT OF A FEASIBLE IMAGE BASED MODELING WORKFLOW

Abstract. The paper shows the intermediate results of a research activity aimed at populating a library of reusable Historical Building Object Models (H-BOMs) by testing a full digital workflow that takes advantages from using Structure from Motion (SfM) models and is centered on the geometrical/stylistic/materic analysis of the architectural element (portal, window, altar). The aim is to find common (invariant) and uncommon (variant) features in terms of identification of architectural parts and their relationships, geometrical rules, dimensions and proportions, construction materials and measure units, in order to model archetypal shapes from which it is possible to derive all the style variations. At this regard, a set of 14th - 16th century gothic portals of the catalan-aragonese architecture in Etnean area of Eastern Sicily has been studied and used to assess the feasibility of the identified workflow. This approach tries to answer the increasingly demand for guidelines and standards in the field of Cultural Heritage Conservation to create and manage semantic-aware 3D models able to include all the information (both geometrical and alphanumerical ones) concerning historical buildings and able to be reused in several projects.

CHALLENGES AND OPPORTUNITIES FOR THE IMPLEMENTATION OF H-BIM WITH REGARDS TO HISTORICAL INFRASTRUCTURES: A CASE STUDY OF THE PONTE GIORGINI IN CASTIGLIONE DELLA PESCAIA (GROSSETO – ITALY)

Abstract. Historical Building Information Modeling (H-BIM) has been widely documented in literature and is becoming more popular with government bodies, who are increasingly choosing to make its use mandatory in public procurements and contracts. Although the system seems to be one of the best approaches for managing data and driving the decision-making process, several difficulties arise due to the amount of effort required in the initial phases, when the data derived from a geometrical survey must be converted into parametric elements. Moreover, users must decide on a “level of geometrical simplification” a long time in advance, and this inevitably leads to a loss of geometrical data. From this perspective, our research describes a procedure to optimize the workflow of information for existing artefacts, in order to achieve a “lean” H-BIM. In this article, we will analyse two aspects: the first relates to the level of accuracy in a digital model created from the two different point clouds achieved from laser scanner and form images, while the second concerns the conversion of this information into parametric elements (Building Object Models- BOMs) that need to have specific characteristics. The case study we are presenting is the “Ponte Giorgini” (“Giorgini Bridge”) in Castiglione della Pescaia (Grosseto – Italy).

Object composite query method using IFC and LandXML based on BIM linkage model

Abstract Recently, querying Building Information Modeling (BIM) objects effectively in a linkage manner based on shape information using the LandXML schema widely utilized in civil engineering has become a necessity. However, because LandXML and Industry Foundation Classes (IFC) are civil engineering and building object models, respectively, obtaining the required objects when querying them in a linkage manner is difficult. This study proposes an effective BIM-integrated object query method using LandXML and IFC by implementing an object query method based on the BIM linkage model. Furthermore, object types and a simple query language required for object queries are defined. To validate this method, this study shows the integrated object query based on attribute value conditions, including shape. By using this object query method, we can conduct use cases such as efficient interference checks that consider civil and building objects.

Surface-Based Detection and 6-DoF Pose Estimation of 3-D Objects in Cluttered Scenes

In this paper, we propose a novel approach for both 3-D object detection and six-degree-of-freedom (6-DoF) pose estimation based on smooth 3-D surface segments and their visual signatures in cluttered scenes with objects partially occluded. It is an appearance-based approach that does not require precise geometric models of the objects. We introduce a robust and flexible strategy to build object models based on segmented smooth surfaces of RGB-D images. We next introduce a strategy to detect objects and estimate their 6-DoF poses from a single image by taking full advantage of the surface-based object models. Our approach can reconstruct objects in cluttered scenes from a single view, where different objects or multiple instances of the same object can be stacked together or physically attached and occlude one another. It detects objects and estimates their 6-DoF poses even if the objects have transparent regions. Experimental results and comparison with related work demonstrate the effectiveness of our approach.

Building object models through interactive perception and foveated vision

Autonomous robots that operate in unstructured environments must be able to seamlessly expand their knowledge base. To detect and manipulate previously unknown objects, a robot should be able to acquire new object knowledge even when no prior information about the objects or the environment is available. Additional information that is needed to identify new objects can come through motion cues induced by interactive manipulation. In the proposed system, changes in the scene are caused by a teacher manipulating the object to be learned. We propose to improve visual object learning and recognition by exploiting the advantages of foveated vision. The proposed approach first creates object hypotheses in peripheral stereo cameras. By directing its attention towards the identified object area in the foveal views, the robot can conduct a more thorough investigation of a smaller area of the scene, which is seen in higher resolution. We compare two methods for validating the hypotheses in the foveal views and experimentally show the advantages of foveated vision compared to stereo vision with a fixed field of view.

Live sequence charts to model medical information

BackgroundMedical records accumulate data concerning patient health and the natural history of disease progression. However, methods to mine information systematically in a form other than an electronic health record are not yet available. The purpose of this study was to develop an object modeling technique as a first step towards a formal database of medical records.MethodLive Sequence Charts (LSC) were used to formalize the narrative text obtained during a patient interview. LSCs utilize a visual scenario-based programming language to build object models. LSC extends the classical language of UML message sequence charts (MSC), predominantly through addition of modalities and providing executable semantics. Inter-object scenarios were defined to specify natural history event interactions and different scenarios in the narrative text.ResultA simulated medical record was specified into LSC formalism by translating the text into an object model that comprised a set of entities and events. The entities described the participating components (i.e., doctor, patient and record) and the events described the interactions between elements. A conceptual model is presented to illustrate the approach. An object model was generated from data extracted from an actual new patient interview, where the individual was eventually diagnosed as suffering from Chronic Fatigue Syndrome (CFS). This yielded a preliminary formal designated vocabulary for CFS development that provided a basis for future formalism of these records.ConclusionsTranslation of medical records into object models created the basis for a formal database of the patient narrative that temporally depicts the events preceding disease, the diagnosis and treatment approach. The LSCs object model of the medical narrative provided an intuitive, visual representation of the natural history of the patient’s disease.

Using Integrated Ontologies for Determining Objects towards Software Engineering Approach

More and more ontologies are becoming available on the web, and are increasing in number and demand. Ontologies can be beneficial for the objects identification in software engineering approach. Semantic and ontologies search engines have used to assist search and recovery of online ontologies which it is the first to find the ontologies for particular domain of interest. Considering an object oriented software engineering classic problem, is the difficulty of finding the appropriate objects for the system. The main goal of this research is to integrate the different eXtensible Markup Language based (XML-based) formats available online by using created Java–based application program to merge and modify ontologies for building object model. The author also provides the alternative option to apply off-the-shelf software as tools for the same purpose. The Java–based application program will allow the developer to choose objects (extracted from ontologies classes) and their components which are attributes, operations, and relationships. The final result of the program will be used as the sketch object diagrams of the system.

Utilizing Ontologies Using Ontology Editor for Creating Initial Unified Modeling Language (UML)Object Model

One of object oriented software developing problem is the difficulty of searching the appropriate and suitable objects for starting the system. In this work, ontologies appear in the part of supporting the object discovering in the initial of object oriented software developing. There are many researches try to demonstrate that there is a great potential between object model and ontologies. Constructing ontology from object model is called ontology engineering can be done; On the other hand, this research is aiming to support the idea of building object model from ontology is also promising and practical. Ontology classes are available online in any specific areas, which can be searched by semantic search engine. There are also many helping tools to do so; one of them which are used in this research is Protege ontology editor and Visual Paradigm. To put them together give a great outcome. This research will be shown how it works efficiently with the real case study by using ontology classes in travel/tourism domain area. It needs to combine classes, properties, and relationships from more than two ontologies in order to generate the object model. In this paper presents a simple methodology framework which explains the process of discovering objects. The results show that this framework has great value while there is possible for expansion. Reusing of existing ontologies offers a much cheaper alternative than building new ones from scratch. More ontologies are becoming available on the web, and online ontologies libraries for storing and indexing ontologies are increasing in number and demand. Semantic and Ontologies search engines have also started to appear, to facilitate search and retrieval of online ontologies.

Development of an authoring framework for the simplified customization of PDM systems

Given that the amount of product data in firms is explosively increasing, a PDM system for effective data management is considered indispensable for product development. However, considerable time and specialized human resources are needed to customize a generic PDM system for satisfying the specific requirements of individual firms. To overcome this problem, we propose the use of UML object models in a PDM authoring framework. A PDM authoring framework, which provides authoring functions for the effective customization of PDM systems, will reduce the need for the intervention of PDM specialists in the design of the object models of the PDM system. We describe how a PDM authoring framework may be designed by using UML object models, and show how model-oriented application development (MOAD), in conjunction with the PDM authoring framework, can be used to build object models into a PDM system. Furthermore, we confirm the value of the framework by evaluating its performance under several conditions.

An Approach to Building Object Models with UML in Embedded Systems

The UML-based development methods of embedded systems are use case-driven. In these methods, identifying objects that constitute the software system is critical and a hard task, since there is no crisp guidelines. In this article, we propose a systematic approach to building object models in embedded systems. After hierarchically decomposing the system into its parts, the approach consists of firstly converting the use case into a statechart that models states of the concerned system parts and secondly, identifying the objects from the statechart. The proposed approach bridges the gap between the outside behavioral system description as offered by use cases and the system structure represented by the object model.

From use cases to classes: a way of building object model with UML

In a use case-driven process, classes in the class diagram need to be identified from use cases in the use case diagram. Current object modelling approaches identify classes either from use case descriptions, or using classic categories. Both ways are inefficient when use cases can be described with many scenarios in different words. This paper represents a new approach that identifies classes based on goals of use cases without descriptions. The approach produces use case-entity diagrams as a vehicle for deriving classes from use cases and to show the involvement of classes in use cases of a system.

A representation for mammographic image processing

Mammographic image analysis is typically performed using standard, general-purpose algorithms. We note the dangers of this approach and show that an alternative physics-model-based approach can be developed to calibrate the mammographic imaging process. This enables us to obtain, at each pixel, a quantitative measure of the breast tissue. The measure we use is h int and this represents the thickness of ‘interesting’ (non-fat) tissue between the pixel and the X-ray source. The thicknesses over the image constitute what we term the h int representation, and it can most usefully be regarded as a surface that conveys information about the anatomy of the breast. The representation allows image enhancement through removing the effects of degrading factors, and also effective image normalization since all changes in the image due to variations in the imaging conditions have been removed. Furthermore, the h int representation gives us a basis upon which to build object models and to reason about breast anatomy. We use this ability to choose features that are robust to breast compression and variations in breast composition. In this paper we describe the h int representation, show how it can be computed, and then illustrate how it can be applied to a variety of mammographic image processing tasks. The breast thickness turns out to be a key parameter in the computation of h int, but it is not normally recorded. We show how the breast thickness can be estimated from an image, and examine the sensitivity of h int to this estimate. We then show how we can simulate any projective X-ray examination and can simulate the appearance of anatomical structures within the breast. We follow this with a comparison between the h int representation and conventional representations with respect to invariance to imaging conditions and the surrounding tissue. Initial results indicate that image analysis is far more robust when specific consideration is taken of the imaging process and the h int representation is used.