• 한국건축시공학회:학술대회논문집
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• 한국건축시공학회 2017년도 춘계 학술논문 발표대회
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• pp.93-94
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• 2017

This study have derived the big issue of overseas construction through big data analysis. For identification of big issues on overseas construction, domestic online articles, 30 daily newspapers like the JoongAng Ilbo, 7 construction related articles including construction economy and 1,759 local newspapers and small media companies were analyzed from October 1st, 2015 to September 30th, 2016. 13,884 cases in total were used for big data analyses and big issue candidates were identified. The analysis result is as shown below. First, looking into major issues on overseas construction for a year, construction orders in the Middle East decreased because of the drop in oil prices. Accordingly, there were discussions on concerns and crises we may face as profitabilities worsened in overseas construction. Second, analyzing main concern based on 8 key words on overseas construction among construction issues for the last one year, it was found as following: Region (29.4%), Business environment (21.4%), Group (15.8%), Profitability (14.5%), Policy and Institution (7.8%), Market environment (4.2%), Business (project) (4.15%), and Education (3.2%). Third, among 30 issues on 8 key words, 10 key issues that are likely to spread and continue were identified. Then, a semantic network map among key words and centrality were analyzed.

• 한국지반공학회:학술대회논문집
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• 한국지반공학회 2008년도 추계 학술발표회
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• pp.1452-1455
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• 2008

In order to establish active and effective recycling plans on construction wastes, the study seeks to built unit generation data per construction waste types on each sector, prepare units data on urban construction waste generation and serve as meaningful data on the establishment of policies on construction waste recycling targeting urban regions. The significance of the study is on the establishment of construction waste recycling plan prior to generation, not as complementary measures on construction waste generated.

• Journal of Construction Engineering and Project Management
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• 제7권2호
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• pp.11-18
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• 2017

The cycle time of construction equipment for earthwork operations has a significant impact on project productivity. Elements that directly impact a haul vehicle's cycle time must be identified in order to accurately quantify the haul cycle time and implement strategies to decrease it. The objective of this research is to scientifically identify and quantify variables that have a significant impact on the cycle time of a dump truck used for earthwork. Real-time location data collected by GPS devices deployed in an active earthwork moving construction site was analyzed using statistical regression. External data including environmental components and haul road conditions were also collected periodically throughout the study duration. Several statistical analyses including a variance analysis and regression analysis were completed on the dump truck location data. Collected data was categorized by stage of the dump truck cycle. Results indicate that a dump truck's enter idle time, exit idle time, moving speed and driver visibility can significantly impact the dump truck cycle time. The contribution of this research is the identification and analysis of statistically significant correlations of variables within the cycle time.

• 한국태양에너지학회:학술대회논문집
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• 한국태양에너지학회 2008년도 추계학술발표대회 논문집
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• pp.337-340
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• 2008

As a 'Construction of Information System on GIS based and Resource Map', establish the strategic of design about construction of Spatial Data Warehouse for New & Renewable Energy For Construction of comfortable Spatial Data Warehouse, It suggested The Construction of Spatial Data Warehouse on Block(Grid) Based with Analyze into the old Data & Method of Study. For Decide the Block(Grid) Size, We need The Study of Data & Method. Also, we expect Standardize The Process of Change & Apply with Data. make the best use of New & Renewable Energy Part

• 한국BIM학회 논문집
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• 제12권1호
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• pp.72-80
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• 2022

It has become mandatory to designs by BIM in construction. It is urgent to make accurate decisions through the linkage between complex and various types of data in projects. In particular, block-chain based data sharing process (using BIM files, general construction submitted files) is essential to support reliable decision making in complex data flood systems. Prior to developing data sharing system based on block-chain, in this paper, a data linkage method is proposed so that practitioners can simultaneously utilize existing construction information and BIM data. Examples are shown based on the construction classification system and file expression, and incentive strategies are explored through a survey so that heterogeneous information can be used at the same time in overall projects.

• 한국전자거래학회지
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• 제8권1호
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• pp.121-139
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• 2003

Currently, it is not popular to use the STEP based product information in the construction drawing files, in spite of the importance and possibility of using various product data in drawing files on the CALS/EC environment. This paper aims to demonstrate a construction drawing information management system based on ISO 10303/STEP. To achieve this aim, the authors have analyzed the current construction drawing information classification hierarchy widely used for domestic and international, and examined the material data connection mechanism within CAD drawing data, and finally investigated the management systems for construction documentations and drawings in a public companies. Therefore, the expected benefit of the proposed system is that STEP drawing information management will be done standardization and the information of STEP construction drawing can be managed, shared and supported design business through materials data connection.

• 한국건축시공학회:학술대회논문집
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• 한국건축시공학회 2023년도 봄 학술논문 발표대회
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• pp.251-252
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• 2023

As technology improves with the 4th industrial revolution, smart construction is becoming a key part of safety management in the architecture and civil engineering. By using object detection technology with CCTV data, construction sites can be managed efficiently. In this study, super resolution technology based on deep learning is proposed to improve the accuracy of object detection in construction sites. As the resolution of a train set data and test set data get higher, the accuracy of object detection model gets better. Therefore, according to the scale of construction sites, different object detection models can be considered.

• 한국건축시공학회지
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• 제11권2호
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• pp.100-107
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• 2011

건설공사의 공사기간은 건설프로젝트의 성공적인 완수를 위하여 중요한 부분을 차지하기 때문에 공사기간에 영향을 미치는 요인들을 체계적으로 관리하는 것이 필요하다. 최근에는 건설 제도적 변화로 건설공사의 공사기간에 대한 관심이 증대되고 있다. 그러나 건설 프로젝트의 공사기간에 미치는 영향요인은 매우 다양하며, 각 요인들 중 어떤 요인이 어느 정도 작업의 생산성에 영향을 미치는지에 대한 데이터의 체계적인 활용이 부족하다. 또한 특정 프로젝트, 특정 작업, 특정 협력업체 등에 영향을 미치는 요인이 무엇인지 또는 전체 프로젝트에 공통적으로 영향을 미치는 요인이 무엇인지를 인식하는 것조차 어려운 경우가 많다. 그러나 데이터 웨어하우스 기술의 다차원 분석을 활용함으로써 다양한 각도에서의 공사기간 영향요인이 미치는 생산성을 파악할 수 있다. 이에 본 연구는 건설공사에서 발생하는 다양한 영향요인에 따른 작업 생산성 데이터를 다차원적으로 분석하고 의사결정에 활용할 수 있는 데이터 마이닝 기술을 적용하여 기존 생산성 데이터들을 효과적으로 활용하는 방법을 제시한다.

• 한국건축시공학회:학술대회논문집
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• 한국건축시공학회 2018년도 추계 학술논문 발표대회
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• pp.100-101
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• 2018

Environmental problems caused by air pollution have been considered as serious critical issues in global perspectives. Controlling greenhouse gases has become one of the major environmental problems in construction fields as well. However, similar studies were mainly focused on suggestion of various methodologies for measuring CO₂ emissions of construction equipment and calculating emissions. This study aims to analyze the correlation between the CO₂ emissions and RPMs of equipment by the construction process based on row data collected from construction equipment actually operated in job sites. This study allows site personnels to determine the amount of emitted CO₂ under particular construction equipment under specific conditions during the targeted construction operations. The research findings expect to be used as fundamental informations for establishing environment-friendly construction operation planning.

• 건설안전기술
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• 통권36호
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• pp.73-81
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• 2006

Construction fall accidents have been investigated by many researchers. Construction workers are prone to fall when elevations of the construction site is high. And falls are the most fatal accidents: it can be directly linked to the death. Construction fall accidents might be reduced by predetermining several areas which are highly probable to have fall accidents and by controlling such areas until the completion of the building construction. In this paper, a fall prevention system is suggested which can identify the areas where the focus on fall protection is perhaps most needed from the process characteristics. Main methodologies for this research are summarized as follows: 1. A data base on elements and types of falls is constructed from the data analysis of last 10 years fall accidents history. 2. Guideline is derived by identifying the highly probable areas of fall accidents with respect to the specific construction process. 3. Developed system is verified by applying the system to construction sites. 4. Finally a fall prevention system is suggested by utilizing the fall accidents data.