• Title/Summary/Keyword: 건설 데이터

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A Study on the Strategy of the Use of Big Data for Cost Estimating in Construction Management Firms based on the SWOT Analysis (SWOT분석을 통한 CM사 견적업무 빅데이터 활용전략에 관한 연구)

  • Kim, Hyeon Jin;Kim, Han Soo
    • Korean Journal of Construction Engineering and Management
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    • v.23 no.2
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    • pp.54-64
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    • 2022
  • Since the interest in big data is growing exponentially, various types of research and development in the field of big data have been conducted in the construction industry. Among various application areas, cost estimating can be a topic where the use of big data provides positive benefits. In order for firms to make efficient use of big data for estimating tasks, they need to establish a strategy based on the multifaceted analysis of internal and external environments. The objective of the study is to develop and propose a strategy of the use of big data for construction management(CM) firms' cost estimating tasks based on the SWOT analysis. Through the combined efforts of literature review, questionnaire survey, interviews and the SWOT analysis, the study suggests that CM firms need to maintain the current level of the receptive culture for the use of big data and expand incrementally information resources. It also proposes that they need to reinforce the weak areas including big data experts and practice infrastructure for improving the big data-based cost estimating.

Development of Web Crawler and Network Analysis Technology for Occurrence and Prediction of Flooding (수난 발생 및 규모 예측을 위한 웹 크롤러 및 네트워크 분석기술 개발)

  • Seo, Dongmin;Kim, Hoyong;Lee, Jeongha;Hwang, Seokhwan
    • Proceedings of the Korea Contents Association Conference
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    • 2019.05a
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    • pp.5-6
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    • 2019
  • 빅데이터 분석을 위해 활용되는 데이터로는 뉴스, 블로그, SNS, 논문, 특허 그리고 센서로부터 수집된 데이터 등 매우 다양한 유형의 데이터가 있다. 특히, 신뢰성 있는 데이터를 실시간 제공하는 웹 데이터의 활용이 점차 확산되고 있다. 그리고 빅데이터의 활용이 다양한 분야로 점차 확산되고 웹 데이터가 매년 기하급수적으로 증가하면서, 최근 웹 데이터는 재난대응 미디어로써 매우 중요한 역할을 하고 있다. 또한, 빅데이터 분석에 활용되는 원천 데이터는 네트워크 형태이며, 최근 소셜 네트워크 분석을 통한 효과적인 상품 광고, 핵심 유전자 발굴, 신약 재창출 등 다양한 영역에서 네트워크 분석 기술이 사회와 인류에게 가치 있는 정보를 제공할 수 있는 가능성을 제시하면서 네트워크 분석 기술의 중요성이 부각되고 있다. 본 논문에서는 웹에서 제공하는 뉴스와 SNS 데이터를 이용해 수난 발생 및 규모 예측을 지원하는 웹 크롤러 및 네트워크 분석기술을 제안한다.

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Development of Overseas Construction Big Issues based on Analysis of Big Data (빅 데이터 분석을 통한 해외건설 빅 이슈 개발)

  • Park, Hwanpyo;Han, Jaegoo
    • Korean Journal of Construction Engineering and Management
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    • v.19 no.3
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    • pp.89-96
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    • 2018
  • This study derived big issues in overseas construction through big data analysis. To derive big issues in overseas construction, candidate groups of big issues were identified through big data analysis targeting 53,759 issues including 39,436 issues from major portal sites, 10,387 issues from daily newspapers, and 336 issues in construction magazines from Oct. 1, 2016 to Sep. 30, 2017. The main results are as follows: First, the main issues of overseas construction for the past one year showed that markets were concentrated in Middle East Asia and most of them were low-price order plant projects, which revealed the limitations. Although orders of overseas construction were slightly upward in the first half of 2017 compared to previous year, overseas construction orders are still unstable due to uncertainties in the international affairs and drops in oil prices. Second, the interest topics based on the 8th core keywords of overseas construction among the overseas construction issues for the past one year showed that region (29.9%), corporation environment (22.0%), profitability (17.0%), organizations (15.1%), projects (5.2%), market environment (3.6%), policy and system (3.6%), and education (3.5%) in the order of interest. Third, 10 core issues that have expandability and persistence of discourse were extracted out of 30 issue candidates with regard to eight keywords. Based on the extracted issues, detailed analysis on each of the core issues in overseas construction and correlation analysis between 10 core issues were conducted.

Development of Performance Analysis System for Construction Projects Using Data Warehousing Technology (데이터 웨어하우스 기술을 활용한 건설프로젝트 성과분석 시스템 개발)

  • Yu Jung-Ho;Song Sang-Hoon;You Won-Hee;Lee Hyun-Soo
    • Korean Journal of Construction Engineering and Management
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    • v.6 no.1 s.23
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    • pp.89-98
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    • 2005
  • Recently the construction industry in Korea is facing problems such as low productivity, contraction of the domestic construction market, growing competition, and so on. To enhance the competitiveness continuously through efficiency in this business environments, construction companies need to make efforts to measure and accumulate performance data based on the strategic factors. When analysing performance of construction projects, the unique characteristics of each project should be considered properly, by which the managers can identify current status of project in various perspectives. This study proposes the performance analysis system using the concepts of balanced scorecard and data warehouse technology. The suggested system provides the management with the flexibility in analyzing performance data by applying the pre-defined key performance indicators and the function of multi-dimensional analysis.

Improvement of SOC Structure Automated Measurement Analysis Method through Probability Analysis of Time-History Data (시계열 데이터의 확률분석을 통한 SOC 구조물 자동화계측 분석기법 개선)

  • Jung-Youl Choi;Dae-Hui Ahn;Jae-Min Han;Jee-Seung Chung;Jung-Ho Kim;Bong-Chul Joo
    • The Journal of the Convergence on Culture Technology
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    • v.9 no.1
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    • pp.679-684
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    • 2023
  • Currently, large-scale and deep-depth excavation construction is being carried out in the vicinity of structures due to overdensity in urban areas in Korea. It is very important to secure the safety of retaining structures and underground structures for adjacent excavation work in urban areas. The safety of facilities is managed by introducing an automated measurement system. However, the utilization of the results of the automated measurement system is very low. Conventional evaluation techniques rely only on the maximum value of the measured data, and can overestimate abnormal behavior. In this study, we intend to improve the analysis technique for the automation measurement results. In order to identify abnormal behavior of facilities, a time-series analysis method for automated measurement data was presented. By applying a probability statistical analysis technique to a vast amount of data, highly reliable results were derived. In this study, the analysis method and evaluation method that can process the vast amount of data of facilities have been improved.

Development of Data Warehouse for Construction Material Management (건설공사 자재 관리를 위한 데이터 웨어하우스 개발)

  • Ryu, Han-Guk
    • Journal of the Korea Institute of Building Construction
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    • v.11 no.3
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    • pp.319-325
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    • 2011
  • During a construction project, construction managers must be provided with material information to help them to make decisions more efficiently without delaying the delivery of material. Construction work can be smoothly performed with the proper material supply. Construction duration depends on several material-related decisions, including the order, delivery, and allocation of material to the correct work location. Hence, it is worthwhile to introduce data warehouse techniques that generate subject-oriented and integrated data to construction material management. The data warehouse for construction material management can perform multidimensional analysis and then define KPIs (Key Performance Index) in order to provide construction managers with construction material information such as lead time, material delivery rate, material installation rate and so on. This research proposes a method of effectively facilitating large amounts of data in the operating systems during the construction management process. In other words, the proposed method can supply structured and multi-perspective material-related information using data warehouse techniques.

A Study on the Trends of Construction Safety Accident in Unstructured Text Using Topic Modeling (비정형 텍스트 기반의 토픽 모델링을 이용한 건설 안전사고 동향 분석)

  • Lee, Sang-Gyu
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.19 no.10
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    • pp.176-182
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    • 2018
  • In order to understand and track the trends of construction safety accident, this study shows the topic trends in the construction safety accident with LDA(Latent Dirichlet Allocation)-based topic modeling method for data analytics. Especially, it performs to figure out the main issue of construction safety accident with unstructured data analysis based on the topic modeling rather than a variety of structured data analysis for preventing to safety accident in construction industry. To apply this methodology, I randomly collected to 540 news article data about construction accident from January 2017 to February 2018. Based on the unstructured data with the LDA-based topic modeling, I found the 10 topics and identified key issues through 10 keyword in each 10 topics. I forecasted the topic issue related to construction safety accident based on analysis of time-series trends about the news data from January 2017 to February 2018. With this method, this research gives a hint about ways of using unstructured news article data to anticipate safety policy and research field and to respond to construction accident safety issues in the future.

Construction Progress Measurement System by tracking the Work-done Performance (내역물량 측정에 의한 건설공사진도율 산정시스템)

  • Choi Yoon-Ki
    • Korean Journal of Construction Engineering and Management
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    • v.4 no.3 s.15
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    • pp.137-145
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    • 2003
  • The project control system based on the actual values of three objects shall be operated continuously in a timely manner. For collecting/tracking accurate actual performance data, a reasonable basis of measuring work performance and its related measuring methods are needed. Therefore, this research proposes a method of developing and operating the construction progress measurement system. The problem of the conventional method is the difficulty to construct control accounts and to define the basis of measuring the performance of each control account. Therefore, this research proposes the preferable, formal methodology that produces the progress value of the smallest work unit by surveying the installed quantities and estimates percent complete of groups of works or entire project by earned value concept. This research in connection with the hereafter research of the weight value of control accounts will contribute to apply in practice and to develop the scientific construction management technique in the construction industry. Further researches how to trend and forecast the project using the measured progress value are recommended for putting the prosed system of this research to practical use.

Construction site disaster risk analysis method Using big data Considering individual work units of construction partner company (협력업체 작업 단위를 고려한 빅데이터 기반 건설현장 재해위험도 분석 방안)

  • Choi, Hochang;Lee, Jung-chul
    • Proceedings of the Korean Institute of Building Construction Conference
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    • 2023.11a
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    • pp.265-266
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    • 2023
  • Recently, many disasters have occurred due to poor management of construction site. In addition, as legal regulations on safety management at construction sites are strengthened, its importance is being further emphasized. In relation to smart safety management technology, a study was introduced to build an analysis model through various safety-related data collected within construction companies. This model derives quantitative disaster risk about the site level through information related to past disasters and near misses. However, construction work is performed separately by work group of each partner company. There is a limitation in that individual workers cannot directly experience this analysis information. In this study, we propose a method to derive the safety disaster risk of individual work units from disaster risk of the site level. We expect that this study to be helpful for smart safety management technology of construction sites.

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WBS Development for Acquisition and Analysis of public Housing Productivity Data (공동주택 생산성 데이터 수집/분석을 위한 WBS 개발)

  • Kim, Jae-Woo;Kim, Yea-Sang;Kim, Young-Suk;Kim, Sang-Bum
    • Korean Journal of Construction Engineering and Management
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    • v.9 no.5
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    • pp.86-94
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    • 2008
  • Productivity is one of key management indexes for evaluating soundness of a manufacturing organization and its efficiency. In many aspects of productivity management in the construction industry, however, intuition of an experienced field manager still plays a greater role while productivity data is not utilized efficiently for the construction management purposes, because the collection and analysis of the productivity-related information are not systematic. Lack of systematic method in collecting and analyzing the productivity data results in such problems. The existing WBS should therefore be improved to solve them. The authors developed a new WBS for productivity data collection and analysis by following the research direction that was determined by literature reviews, overseas cases, and interviews with field engineers. The new breakdown structure was then evaluated for its feasibility as a productivity analysis framework. It is expected that the productivity data collected by the WBS will be used for OLAP and mining for future productivity forecast.