• 한국인터넷방송통신학회논문지
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• 제16권6호
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• pp.225-230
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• 2016

최근 네트워크와 인터넷의 발전으로 웹상에 대용량의 데이터가 생겨났으며, 이를 처리하기 위해 빅데이터 기술이라는 패러다임이 생겨났다. 빅데이터 기술은 기존의 정형 데이터뿐만 아니라 소셜 데이터 등 다양한 비정형 데이터를 이용해 다각적이고 정확한 분석을 목표로 연구되고 있다. 그러나 소셜 데이터는 전문성과 객관성을 가지고 있다고 보기는 힘들고 정보의 조작 및 은폐, 왜곡 등의 문제성이 제기되고 있다. 따라서, 본 논문에서는 신뢰성 빅데이터 플랫폼에 대하여 제안하며, 세부 관리자와 모듈에 대하여 설명한다. 본 논문에서 제안하는 신뢰성 빅데이터 플랫폼은 데이터 정제 관리자, 데이터 분석 관리자, 상호 신뢰 관리자, 시각화 관리자, 검색 관리자로 구성되어진다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권3호
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• pp.974-992
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• 2021

Recently, the healthcare field has undergone rapid changes owing to the accumulation of health big data and the development of machine learning. Data mining research in the field of healthcare has different characteristics from those of other data analyses, such as the structural complexity of the medical data, requirement for medical expertise, and security of personal medical information. Various methods have been implemented to address these issues, including the machine learning model and cloud platform. However, the machine learning model presents the problem of opaque result interpretation, and the cloud platform requires more in-depth research on security and efficiency. To address these issues, this paper presents a recent technology for Internet-of-Things-based (IoT-based) health big data processing. We present a cloud-based IoT health platform and health big data processing technology that reduces the medical data management costs and enhances safety. We also present a data mining technology for health-risk prediction, which is the core of healthcare. Finally, we propose a study using explainable artificial intelligence that enhances the reliability and transparency of the decision-making system, which is called the black box model owing to its lack of transparency.

• 대한산업공학회지
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• 제42권2호
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• pp.112-121
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• 2016

This paper focuses on competencies of data scientists and behavioral intention that affect big data analysis performance. This experiment examined nine core factors required by data scientists. In order to investigate this, we conducted a survey to gather data from 103 data scientists who participated in big data competition at Kaggle platform and used factor analysis and PLS-SEM for the analysis methods. The results show that some key competency factors have influential effect on the big data analysis performance. This study is to provide a new theoretical basis needed for relevant research by analyzing the structural relationship between the individual competencies and performance, and practically to identify the priorities of the core competencies that data scientists must have.

• Journal of information and communication convergence engineering
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• 제21권3호
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• pp.216-224
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• 2023

Smart lighting systems have become increasingly popular in several public sectors because of trends toward urbanization and intelligent technologies. In this study, we designed and implemented a web application platform to explore and monitor data acquired from lighting devices at Thammasat University (Rangsit Campus, Thailand). The platform provides a convenient interface for administrative and operative staff to monitor, control, and collect data from sensors installed on campus in real time for creating geographically specific big data. Platform development focuses on both back- and front-end applications to allow a seamless process for recording and displaying data from interconnected devices. Responsible persons can interact with devices and acquire data effortlessly, minimizing workforce and human error. The collected data were analyzed using an exploratory data analysis process. Missing data behavior caused by system outages was also investigated.

• International journal of advanced smart convergence
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• 제8권1호
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• pp.82-86
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• 2019

We aim to use public data different from the remote BEMS energy diagnostics technology and already established and then switch the conventional operation environment to a big-data-based integrated management environment to operate and build a building energy management environment of maximized efficiency. In Step 1, various network management environments of the system integrated with a big data platform and the BEMS management system are used to collect logs created in various types of data by means of the big data platform. In Step 2, the collected data are stored in the HDFS (Hadoop Distributed File System) to manage the data in real time about internal and external changes on the basis of integration analysis, for example, relations and interrelation for automatic efficient management.

• Spatial Information Research
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• 제21권5호
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• pp.43-51
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• 2013

본 연구에서는 최근 이슈가 되고 있는 공간빅데이터에 대한 개념과 효과적으로 공간빅데이터체계를 구축하기 위한 방안을 제시하였다. 공간빅데이터는 3V(volume, variety, velocity)로 정의되고 있는 빅데이터를 6V(volume, variety, velocity, value, veracity, visualization)의 빅데이터로 진화시키는 기반이라 할 수 있다. 공간빅데이터를 효과적으로 구축하기 위해서는 공간빅데이터체계 구축으로 추진되어야 하며, 공간빅데이터체계는 국가공간정보기반, 융합플랫폼, 서비스제공자, 생산요소제공자로서의 역할을 수행해야 한다. 이러한 공간빅데이터체계의 구성요소는 인프라(하드웨어), 기술(소프트웨어), 공간빅데이터(데이터), 인력, 법 제도 등이며, 공간빅데이터체계 구축을 위한 목표로 공간기반 정책수립 지원, 공간빅데이터 플랫폼 기반 산업활성화, 공간 빅데이터 융합기반 조성, 공간관련 사회현안의 적극적 해결로 제시하였다. 그리고 목표에 대한 추진전략은 범정부적 협력체계 구축, 신산업 창출 및 활용 활성화, 성과활용 중심의 공간빅데이터 플랫폼 구축, 공간빅데이터 관련 기술경쟁력 확보로 제시하였다.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2017년도 춘계학술발표대회
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• pp.661-664
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• 2017

Recently, during disasters occurrence, dealing with emergencies has been handled well by the early transmission of disaster relating notifications on social media networks (e.g., Twitter or Facebook). Intuitively, with their characteristics (e.g., real-time, mobility) and big communities whose users could be regarded as volunteers, social networks are proved to be a crucial role for disasters response. However, the amount of data transmitted during disasters is an obstacle for filtering informative messages; because the messages are diversity, large and very noise. This large volume of data could be seen as Social Big Data (SBD). In this paper, we proposed a big data platform for collecting and analyzing disasters' data from SBD. Firstly, we designed a collecting module; which could rapidly extract disasters' information from the Twitter; by big data frameworks supporting streaming data on distributed system; such as Kafka and Spark. Secondly, we developed an analyzing module which learned from SBD to distinguish the useful information from the irrelevant one. Finally, we also designed a real-time visualization on the web interface for displaying the results of analysis phase. To show the viability of our platform, we conducted experiments of the collecting and analyzing phases in 10 days for both real-time and historical tweets, which were about disasters happened in South Korea. The results prove that our big data platform could be applied to disaster information based systems, by providing a huge relevant data; which can be used for inferring affected regions and victims in disaster situations, from 21.000 collected tweets.

• 디지털산업정보학회논문지
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• 제14권4호
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• pp.57-68
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• 2018

This paper presents a smart firefighting appliances monitoring system based on big data analytics platform using GS1 for Smart City. Typical firefighting appliances are fire hydrant, fire extinguisher, fire alarm, sprinkler, fire engine, etc. for the fire of classes A/B/C/D/E. Among them, the dry chemical fire extinguisher have been widely supplied and 6 millions ones were replaced for the aging ones over 10 years in the past year. However, only 5% of them have been collected for recycling of chemical materials included the heavy metals of environment pollution. Therefore, we considered the trace of firefighting appliances from production to disposal for the public open service. In the paper, we suggest 1) a smart firefighting appliances system using GS1, 2) a big data analytics platform and 3) a public open service and visualization with the analyzed information, for fire extinguishers from production to disposal. It can give the information and the visualized diagrams with the analyzed data through the public open service and the free Apps.

• 정보보호학회논문지
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• 제23권4호
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• pp.721-728
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• 2013

빅데이터는 오늘날 가장 각광받고 있는 데이터 수집 및 분석기술의 경향으로, 대량의 비정형 데이터 분석을 요구하는 다양한 분야에 접목되어 효용성을 인정받고 있다. 네트워크 트래픽 분석 역시 대량의 비정형 데이터를 다루는 분야로, 빅데이터 접목시 그 효과가 극대화될 수 있다. 따라서 본 논문에서는 고도의 보안이 요구되는 군 C4I망과 같은 내부망 환경의 침해사고 및 이상행위를 실시간으로 탐지하기 위한 빅데이터 기반의 네트워크 트래픽 분석 플랫폼(RENTAP)을 소개한다. 빅데이터 분석 지원을 위해 최근 각광받고 있는 오픈소스 솔루션들을 대상으로 비교 분석을 수행하였으며, 선정된 솔루션을 기반으로 고안된 최종 설계에 대해서 설명한다.

• 산업경영시스템학회지
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• 제41권3호
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• pp.176-185
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• 2018

With the recent development of manufacturing technology and the diversification of consumer needs, not only the process and quality control of production have become more complicated but also the kinds of information that manufacturing facilities provide the user about process have been diversified. Therefore the importance of big data analysis also has been raised. However, most small and medium enterprises (SMEs) lack the systematic infrastructure of big data management and analysis. In particular, due to the nature of domestic manufacturing companies that rely on foreign manufacturers for most of their manufacturing facilities, the need for their own data analysis and manufacturing support applications is increasing and research has been conducted in Korea. This study proposes integrated analysis platform for process and quality analysis, considering manufacturing big data database (DB) and data characteristics. The platform is implemented in two versions, Web and C/S, to enhance accessibility which perform template based quality analysis and real-time monitoring. The user can upload data from their local PC or DB and run analysis by combining single analysis module in template in a way they want since the platform is not optimized for a particular manufacturing process. Also Java and R are used as the development language for ease of system supplementation. It is expected that the platform will be available at a low price and evolve the ability of quality analysis in SMEs.