• 한국환경과학회지
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• 제23권3호
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• pp.493-502
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• 2014

EnergyPlus is a whole building energy simulation program that engineers, architects, and researchers use to model energy and water use in buildings. Modeling the performance of a building with EnergyPlus enables building professionals to optimize the building design to use less energy and water. This program provides energy analysis of building and needs weather data for simulation. Weather data is available for over 2,000 locations in a file format that can be read by EnergyPlus. However, only five locations are avaliable in Korea. This study intends to use AWS data for having high spatial resolution to simulate building energy. The result of this study shows the possibility of using AWS data for energy simulation of building.

• 전자통신동향분석
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• 제39권4호
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• pp.32-41
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• 2024

Building energy management plays a crucial role in improving energy efficiency and optimizing energy usage. To achieve this, it is important to monitor and analyze energy-related data from buildings in real time using sensors to understand energy consumption patterns and establish optimal operational strategies. Because of the uncertainties in building energy-related data, there are challenges in analyzing these data and formulating operational strategies based on them. Artificial intelligence (AI) technology can help overcome these challenges. This paper investigates past and current research trends in AI technology and examines its future prospects for building energy management. By performing prediction and analysis based on energy consumption or supply data, the future energy demands of buildings can be forecasted and energy consumption can be optimized. Additionally, data related to the surrounding environment, occupancy, and other building energy-related factors can be collected and analyzed using sensors to establish operational strategies aimed at further reducing energy consumption and increasing efficiency. These technologies will contribute to cost savings and help minimize environmental impacts for building owners and operators, ultimately facilitating sustainable building operations.

• 대한건축학회논문집:구조계
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• 제34권3호
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• pp.95-102
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• 2018

In order to understand interaction between building users' occupant performance and building maintenance performance of maintenance management personnel, actual data from maintenance activities of buildings were analyzed. Also, using building defect customer complaint data reported by building user, satisfaction data on building maintenance services of building users and service response time of maintenance management personnel, a method for evaluating interaction of buildings with the same purpose and same size was proposed. Throughout analysis, average number of occurrences per unit area per year for the mechanical complaints in complex building were presented. In addition, using building users' satisfaction with facility management services, attitude of responding to business obstacles, number of occurrences per unit area per year of mechanical complaints and complaint processing speed, interaction was comprehensively identified and compared.

• KIEAE Journal
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• 제12권2호
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• pp.77-82
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• 2012

Data mining is to discover problems in the large amounts of data. Also, data mining trying to find the cause of the problem and the structure. Building energy consumption patterns, the amount of data is infinite. Also, the patterns have a lot of direct and indirect effects. Discussion is needed about the correlation. This work looking for the cause of energy consumption. As a result, energy management can find out the issue. Building energy analysis utilizing data mining techniques to predict energy consumption. And the results are as follows: 1) Using data mining technique, We classified complicated data to several patterns and gained meaningful informations from them. 2) Using cluster analysis, We classified building energy consumption data of residents and analyzed characters of patterns.

• 한국건축시공학회:학술대회논문집
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• 한국건축시공학회 2011년도 춘계 학술논문 발표대회 1부
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• pp.137-140
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• 2011

A systemic building maintenance management is necessary to supply an convenience and safety environment by maintain the origin features for a building's life. However, the exist maintenance management system has some problems such as interoperability of information or standardization of data. In those reasons, a critical information for maintenance a building may be lost and changed. In addition, the data could be crashed or lost on a process of re-input or re-produce. This paper purpose the interoperability in exchanging data between design/construction and operation phases. In addition, this model will enhance the efficiency of building maintenance tasks through information quality improvement and data reproduction prevention.

• 대한원격탐사학회지
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• 제23권3호
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• pp.199-209
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• 2007

Traditionally, aerial images have been used as main sources for compiling topographic maps. In recent years, lidar data has been exploited as another type of mapping data. Regarding their performances, aerial imagery has the ability to delineate object boundaries but omits much of these boundaries during feature extraction. Lidar provides direct information about heights of object surfaces but have limitations with respect to boundary localization. Considering the characteristics of the sensors, this paper proposes an approach to extracting buildings from lidar and aerial imagery, which is based on the complementary characteristics of optical and range sensors. For detecting building regions, relationships among elevation contours are represented into directional graphs and searched for the contours corresponding to external boundaries of buildings. For generating building models, a wing model is proposed to assemble roof surface patches into a complete building model. Then, building models are projected and checked with features in aerial images. Experimental results show that the proposed approach provides an efficient and accurate way to extract building models.

• 대기
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• 제29권4호
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• pp.417-427
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• 2019

The purpose of this study is to build urban canopy model (Met Office Reading Urban Surface Exchange Scheme, MORUSES) based to Unified Model (UM) by using urban building information data in Seoul, and then to compare the improving urban canopy model simulation result with that of Seoul Automatic Weather Station (AWS) observation site data. UM-MORUSES is based on building information database in London, we performed a sensitivity experiment of UM-MOURSES model using urban building information database in Seoul. Geographic Information System (GIS) analysis of 1.5 km resolution Seoul building data is applied instead of London building information data. Frontal-area index and planar-area index of Seoul are used to calculate building height. The height of the highest building in Seoul is 40m, showing high in Yeoido-gu, Gangnam-gu and Jamsil-gu areas. The street aspect ratio is high in Gangnam-gu, and the repetition rate of buildings is lower in Eunpyeong-gu and Gangbuk-gu. UM-MORUSES model is improved to consider the building geometry parameter in Seoul. It is noticed that the Root Mean Square Error (RMSE) of wind speed is decreases from 0.8 to 0.6 m s^-1 by 25 number AWS in Seoul. The surface air temperature forecast tends to underestimate in pre-improvement model, while it is improved at night time by UM-MORUSES model. This study shows that the post-improvement UM-MORUSES model can provide detailed Seoul building information data and accurate surface air temperature and wind speed in urban region.

• 한국CDE학회논문집
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• 제21권1호
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• pp.31-41
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• 2016

Building Information Modeling (BIM) has been adopted in variety domain of construction industry. In this circumstances, interest of BIM model quality has been increased. In many countries, automated building code checking system by Industry Foundation Classes (IFC) has been developed and studied to use web based building permission systems. IFC is international standard of BIM format. However, the data structure of IFC does not include all of objects and properties about national building codes. In this paper, we developed the information specification between IFC data structure and national building code to increase interoperability. First, we drew the criteria from literature review to analyze the building code. And then, we analyzed building code and sorted objects and properties for automated building code checking. After that we made mapping table between the sorted data and IFC specification. Using the mapping table, we developed pre-specification about building codes information that does not exist in IFC specification. And the defined information can be used to develop the BIM modeling guide and national building permission system. The pre-specification support increasing the interoperability between user and automated building code checking system. Increasing thee interoperability makes improvement accuracy and reliability about result of automated building code checking.

• 한국측량학회지
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• 제26권3호
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• pp.275-284
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• 2008

수치지도의 효율적 갱신방안이 필요한 이유는 수치지도가 지자체 및 여러 지리정보시스템의 기본도로 활용되고 있어 수치지도의 수정갱신 이슈가 공간정보 활용 극대화의 열쇠가 되기 때문이다. 이에 본 연구에서는 수치지도의 건물레이어를 중심으로 그 속성정보를 효율적으로 갱신하기 위해 건축물대장과 연계하는 방안을 제시하였다. 이를 위해 가장 필수적인 사항은 두 자료의 건물간 연계가 일대일로 이루어져야 한다는 점으로, 본 연구에서는 건축물대장과 수치지도의 건물도형에 새주소사업의 건물번호를 공통으로 부여하여 일대일로 연계함으로서 ID 기반의 건물레이어 속성정보의 수정갱신 모델을 수립하였다.

• 대한설비공학회:학술대회논문집
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• 대한설비공학회 2008년도 동계학술발표대회 논문집
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• pp.440-445
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• 2008

In this paper, new methodology is proposed to estimate the cooling load using areas of building group and predicted weather data. Only three parameters such as maximum, minimum temperature and building area are necessary to obtain hourly distribution of cooling load for the next day. The maximum and minimum temperature that are used for input parameters can be obtained from forecasted weather data. The areas of building group are used for setting several parameters that are used for estimate cooling loads. Benchmarking building(research building) is selected to validate the performance of the proposed method, and the estimated cooling loads in hourly bases are calculated and compared with the measured data for benchmarking building. The estimated results show fairly good agreement with the measured data for benchmarking building.