• Korean Journal of Computational Design and Engineering
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• v.15 no.6
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• pp.467-475
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• 2010

Due to the needs of design optimization and productivity for modernized Korean traditional house, standardization of Korean traditional building components is proceeding by BIM (Building Information Modeling). Currently, most of BIM software support object-based parametric modeling. By means of parameterized Korean traditional building components, the shape and assembly relation can be controlled. Although IFC(ISO/PAS 16739), which is an international standard in the AEC field, has been developed for information exchange among BIM software, IFC and other existing common data formats cannot be exchangeable parametric information. For the exchangeable parametric information within IFC, the authors defined meta-data by using Pset(Property-Set). The authors analyzed results about interoperability test in Revit $Architecture^{TM}$, $ArchiCAD^{TM}$ and Digital $Project^{TM}$. In order to solve found problems, the authors developed a translator to improve interoperability among BIM software.

• Journal of KIBIM
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• v.5 no.3
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• pp.1-10
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• 2015

We have researched a character of BIM(Building Information Modeling) and GIS(Geographic Information System) data for integrated utilization of urban spatial data and building data for $CO_2$ reduction. We consider literature on integrated utilization of BIM and GIS and measure method of $CO_2$ in urban spatial unit. Among them without distortion of standard data structure, derive method how to install between BIM and GIS standard data. Rhino & Grasshopper is utilization tools of DB platform. The compatibility with existing BIM and GIS data format, graphic and numeric results can be output at the same time. And using the existing ARCHSIM, it can be easily combined for building energy analysis program. Based on BIM and GIS data to run an energy analysis target on Majang-dong, it could be poly synthetically derived the value information and graphic information.

• Journal of KIBIM
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• v.9 no.4
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• pp.1-9
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• 2019

Visualized information platforms through building information modeling (BIM) such as virtual reality (VR) and augmented reality (AR) improves the efficiency of architectural information exchange. Despite that, less effort has been directed to evaluate the effectiveness of different BIM visualization platforms for architectural design review. This study fills these gaps and compares three BIM visualization tools for reviewing diverse architectural review factors and technology acceptance degree. Three main BIM visualization tools, which are desktop-based, virtual reality-based and augmented reality-based, were employed and different architectural review factors and user's technology acceptance degree was measured. As a result, VR and AR environment showed better visual presentation than desktop environment during design review. In terms of the technology acceptance level, VR and AR environments have received higher ratings compared to desktop environments. The detailed findings provide guidelines for participants and researchers involved in design review process to selectively adopt VR and AR system to various architectural design review components.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2015.05a
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• pp.259-260
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• 2015

In this paper, for deriving core function requirements of facility maintenance using BIM(Building Information Modeling) customized surveys were conducted with 30 facility managers during 6 momths from July 2014. As a result, 19 core function requirements for efficient facility maintenance are drawn. The core of Building facility management function is that opinions of facilities maintenance managers should be fully reflected than that of BIM experts. In the future, the development of maintenance programs based on BIM should be made fully by reflecting the opinions of building facility managers on the basis of this questionnaire survey results.

• Journal of Korean Institute of Architectural Sustainable Environment and Building Systems
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• v.12 no.6
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• pp.543-556
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• 2018

Zero energy building was attended for energy consumption minimization by the energy saving technology about building heating and cooling energy consumption and the renewable energy production facility. So the government has supported the zero energy building supply for decreasing green gas emissions. The study about inventory of zero energy building has many proceeding. That inventory need the information of material and equipment. So information of material and equipment about zero energy building must be included for the zero energy building realization. Actually the database of zero energy building inventory construction through the inventory established studies has difficult because the database need many information. In this study, author proposed the test methods and performance reference for upload at inventory. It was constructed to material - module - package. Also the author analyzed the construction of the technical package for zero energy building. The author separated performance category to the energy performance for energy analysis and other performance for confirmed the durability, stability and etc. This performance category proposed the table. The test methods of material and equipment in the passive package and active package proposed to the international standard and korea standard basically korea standard. Also the performance reference was proposed to korea legal standard and various standard by this study results. And the authors proposed the table of performance value, test methods, performance reference. By result of this study, the test methods and performance reference will be used the basic data for inventory of zero energy building.

• International conference on construction engineering and project management
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• 2013.01a
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• pp.437-443
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• 2013

Recently, sustainable building design, a growing field within architectural design, has been emerged in the construction industry as the practice of designing, constructing, and operating facilities in such a manner that their environmental impact, which has become a great concern of construction professionals, can be minimized. A number of different green rating systems have been developed to help assess that a building project is designed and built using strategies intended to minimize or eliminate its impact on the environment. In the United States, the widely accepted national standards for sustainable building design are known as the LEED (Leadership in Energy and Environmental Design) Green Building Rating System. The assessment of sustainability using the LEED green rating system is a challenging and time-consuming work due to its complicated process. In effect, the LEED green rating system awards points for satisfying specified green building criteria into five major categories: sustainable sites, water efficiency, energy and atmosphere, materials and resources, and indoor environmental quality; and sustainability of a project is rated by accumulating scores (100 points maximum) from these five major categories. The sustainability rating process could be accelerated and facilitated by using computer technology such as BIM (Building Information Modeling), an innovative new approach to building design, engineering, and construction management that has been widely used in the construction industry. BIM is defined as a model-based technology linked with a database of project information, which can be accessed, manipulated, and retrieved for construction estimating, scheduling, project management, as well as sustainability rating. This paper will present a framework representing the building knowledge contained in the LEED green building criteria. The proposed building knowledge framework will be implemented into a BIM platform (e.g. Autodesk Revit Architecture) in which sustainability rating of a building design can be automatically performed. The development of the automated sustainability rating system and the results of its implementation will be discussed.

• KIEAE Journal
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• v.11 no.2
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• pp.113-122
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• 2011

About 30% of the total annual energy consumption on the earth is used in the architectural activities, including construction, maintenance management, and demonstration of a building. Also, 40% of the natural resource consumption, 50% of $CO_2$ emissions, and 20%~50% of industrial waste emissions are produced from a building. Unfortunately, the percentage of its energy consumption is staidly increasing year by year, about 8% every year, and it recently causes a sustainable architectural concept to come to the fore globally. Indeed, the importance of the sustainable architecture is increasingly becoming a worldwide trend. BIM(Building Information Modeling) is considered a new paradigm and a powerful method in building design, construction and maintenance. BIM has characteristics similar to a building's systems. All of the components in a model have a parametric relationship to each other. Understanding and capitalizing on these interrelationships typically takes numerous iterations that span multiple projects. Optimizing the integrated strategies and technologies for a high-performance, sustainable design requires a continual look at understanding how they work together to deliver the best potential. Throughout all of these concepts, we are going to be using a variety of tools that revolve around a BIM model. Some of the tools will require a heavier use of BIM than others, but all of them will utilize the model geometry you've created as part of your design. This study presents importance and validity of energy performance analyzation in the pre-design phase for the sustainable architecture with the support of Building Information Modeling (BIM) technology.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.3
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• pp.341-348
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• 2020

The ability to extract useful information from an image, such as the human eye, is an interface technology essential for AI computer implementation. The building recognition technology has a lower recognition rate than other image recognition technologies due to the various building shapes, the ambient noise images according to the season, and the distortion by angle and distance. The computer vision based building recognition algorithms presented so far has limitations in discernment and expandability due to manual definition of building characteristics. This paper introduces the deep learning CNN (Convolutional Neural Network) model, and proposes new method to improve the recognition rate even by changes of building images caused by season, illumination, angle and perspective. This paper introduces the partial images that characterize the building, such as windows or wall images, and executes the training with whole building images. Experimental results show that the building recognition rate is improved by about 14% compared to the general CNN model.

• Korean Journal of Computational Design and Engineering
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• v.21 no.3
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• pp.313-324
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• 2016

As building information modeling (BIM) is expanding its influence in various fields of architecture, engineering, construction and facility management (AEC-FM) industry, BIM-based automated code compliance checking has become possible prospects. For the automated code compliance checking, requirements in building code need to be processed into explicit representation that enables automated reasoning. This paper aims to develop high-level methods that translate verb phrases into explicit representation. The high-level methods represent conditions, properties, and related actions of the building objects and clarify the core content of the constraints. The authors analyze building permit requirements in Korea Building Code and establish a standardized process of deriving the high-level methods. As a result, 60 kinds of the high-level methods were derived. In addition, method classification, analysis, and application are introduced. This study will contribute to the representation of explicit building code sentences and establishment of the automated building permit system of Korea.

• Journal of Information Processing Systems
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• v.18 no.4
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• pp.587-598
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• 2022

To increase building change recognition accuracy, we present a deep learning-based building change detection using remote sensing images. In the proposed approach, by merging pixel-level and object-level information of multitemporal remote sensing images, we create the difference image (DI), and the frequency-domain significance technique is used to generate the DI saliency map. The fuzzy C-means clustering technique pre-classifies the coarse change detection map by defining the DI saliency map threshold. We then extract the neighborhood features of the unchanged pixels and the changed (buildings) from pixel-level and object-level feature images, which are then used as valid deep neural network (DNN) training samples. The trained DNNs are then utilized to identify changes in DI. The suggested strategy was evaluated and compared to current detection methods using two datasets. The results suggest that our proposed technique can detect more building change information and improve change detection accuracy.