• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.8
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• pp.535-544
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• 2018

As the spread of mobile devices equipped with various sensors and high-quality wireless network communications functionsexpands, the amount of spatio-temporal data generated from mobile devices in various service fields is rapidly increasing. In conventional research into processing a large amount of real-time spatio-temporal streams, it is very difficult to apply a Hadoop-based spatial big data system, designed to be a batch processing platform, to a real-time service for spatio-temporal data streams. This paper extends the MapReduce online framework to support real-time query processing for continuous-input, spatio-temporal data streams, and proposes a load management method to distribute overloads for efficient query processing. The proposed scheme shows a dynamic load balancing method for the nodes based on the inflow rate and the load factor of the input data based on the space partition. Experiments show that it is possible to support efficient query processing by distributing the spatial data stream in the corresponding area to the shared resources when load management in a specific area is required.

• Land and Housing Review
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• v.13 no.2
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• pp.81-90
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• 2022

This study is based on social needs for green healing spaces assumed to enhance mental health in a city. This study proposes development directions through the analysis of modern social recognition factors for neighborhood gardens. As a research method, web information data was collected using Textom among big data tools. Text Mining was conducted to extract elements and analyze their relationship through keyword analysis, network analysis, and cluster analysis. As a result, first, the healing space and the healing environment were creating an eco-friendly healthy environment in a space close to the neighborhood within the city. Second, neighborhood gardens included projects and activities that involved government, local administration, and citizens by linking facilities as well as living culture and urban environments. These gardens have been reinforced through green welfare and service programs. In conclusion, friendly gardens in the neighborhood for the purpose of public interest, which are beneficial to mental health, are green infrastructures as a healing environment that can produce positive effects.

• Spatial Information Research
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• v.20 no.2
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• pp.137-153
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• 2012

Until now, many indexing methods that can reduce update cost have been proposed for managing massive moving objects. Because indexing methods for moving objects have to be updated periodically for managing moving objects that change their location data frequently. However these kinds indexing methods occur big load that exceed system capacity when the number of moving objects increase dramatically. In this paper, we propose the update frequency reducing method to combine MapReduce and existing indices. We use the update request grouping method for each moving object by using MapReduce. We decide to update by comparing the latest data and the oldest data in grouping data. We reduce update frequency by updating the latest data only. When update is delayed, for the data should not be lost and updated periodically, we store the data in a certain period of time in the hash table that keep previous update data. By the performance evaluation, we can prove that the proposed method reduces the update frequency by comparison with methods that are not applied the proposed method.

• The Journal of Society for e-Business Studies
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• v.26 no.2
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• pp.61-81
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• 2021

In the era of untact, the "Chabak" using cars as accommodation spaces is attracting attention as a new form of travel. Due to the advantages, including low costs, convenience, and safety, as well as the characteristics of the vehicle enabling independent travel, the demand for Chabak is continuously increasing. Despite the rapid growth of the market and related industries, little academic has investigated this trend. To establish itself as a new type of travel culture and to sustain the growth of related industries, it is essential to understand the public perception of Chabak. Therefore, based on the marketing mix theory and big data analysis, this study analyzes the public perception of Chabak. The results showed that Chabak has established itself as a consumer-led travel culture, contributing to the aftermarket growth of the automobile industry. Additionally, consumers were found to be increasingly inclined to enjoy travel economically and wisely, and actively share information through social media. This initial study on the new travel trend of Chabak is significant in that it employs big data analysis on a theoretical basis.

• Journal of Digital Convergence
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• v.19 no.8
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• pp.33-42
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• 2021

As smartphone-based tourism platforms have become active, policy establishment and service enhancement using review data are being made in various fields. In the case of the preceding studies using tourism review data, most of the studies centered on domestic tourists were conducted, and in the case of foreign tourist studies, studies were conducted only on data collected in some languages and text mining techniques. In this study, 3,515 review data written by foreigners were collected by designating the "Daegu attractions" keyword through the online review site. And LDA-based topic modeling was performed to derive tourism topics. The spatial approach through global and local spatial autocorrelation analysis for each topic can be said to be different from previous studies. As a result of the analysis, it was confirmed that there is a global spatial autocorrelation, and that tourist destinations mainly visited by foreigners are concentrated locally. In addition, hot spots have been drawn around Jung-gu in most of the topics. Based on the analysis results, it is expected to be used as a basic research for spatial analysis based on local government foreign tourism policy establishment and topic modeling. And The limitations of this study were also presented.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.1
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• pp.1-16
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• 2020

With the advent of the fourth industrial revolution era, there has been a growing interest in deep learning using big data, and studies using deep learning have been actively conducted in various fields. In the transportation sector, there are many advantages to using deep learning in research as much as using deep traffic big data. In this study, a short -term travel speed prediction model using LSTM, a deep learning technique, was constructed to predict the travel speed. The LSTM model suitable for time series prediction was selected considering that the travel speed data, which is used for prediction, is time series data. In order to predict the travel speed more precisely, we constructed a model that reflects both temporal and spatial effects. The model is a short-term prediction model that predicts after one hour. For the analysis data, the 5minute travel speed collected from the Seoul Transportation Information Center was used, and the analysis section was selected as a part of Gangnam where traffic was congested.

• Proceedings of the Korea Water Resources Association Conference
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• 2019.05a
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• pp.118-118
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• 2019

현재 홍수예보는 정형데이터인 유량 및 수위 등을 활용하여 이뤄지고 있다. 하지만 실제 사람들이 체감하는 홍수에 대한 위험도는 홍수예보 발령과는 달라 홍수예보가 이뤄지지 않은 지역에서 인명사고가 발생하기도 한다. 이는 수위 측정이 이뤄지지 않는 소규모 하천이나 사람들의 유동성이 큰 도심지역에서 빈번하게 발생한다. 이를 보완하기 위해서는 사람들의 체감 정도 및 인구의 유동성을 고려한 비정형데이터를 활용해야 한다. 특히 소셜 네트워크 서비스(Social Network Commuinty, SNS)를 사용하는 사람들이 많아지면서 기존에 사용되어 왔던 정형데이터 센서 이외의 데이터를 제공한다. 또한 개개인이 작성하는 글은 실시간으로 활용이 가능하여 인구의 유동성 및 시 공간적 데이터를 얻기에 유용하여 활용성이 매우 높은 비정형데이터이다. 따라서 본 연구에서는 SNS 데이터를 추출하고 이를 분석하여 2018년에 발생했던 강우사상과의 패턴을 비교하여 홍수예보에서의 활용성을 분석하였다. 홍수와 관련한 키워드를 중심으로 시 공간적 정보 및 추출이 가능한 웹 크롤러(Web Crawler) 프로그램을 작성하였으며 이를 토대로 데이터를 수집하였다. 수집한 데이터와 실제 홍수사상을 비교 분석을 한 결과 강우량 및 수위와 해당 지역에 대한 데이터의 양이 유사한 패턴을 보인 것으로 확인되었다. 실시간으로 데이터를 수집하고 이를 분석하여 리드타임을 충분히 확보한다면 홍수예측에 활용 가능할 것이라 생각된다. 본 연구는 한국건설기술연구원 19주요-대4-시드사업인 '커뮤니티 빅데이터 패턴 해석을 통한 수난(水難) 발생 및 규모 예측 기술 개발(20190126-001) '로 수행되었습니다.

• Journal of the Korean Society for information Management
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• v.31 no.2
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• pp.7-40
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• 2014

This study proposes to identify digital library services applying cutting-edge technologies, and attempt to investigate the applicability of these technologies and services to domestic libraries. To this end, we reviewed main research which discusses next generation digital libraries, and examined thoroughly main technologies which can be applied to future libraries. As a result, the core technologies, concepts, and tools of the next generation of digital library are: cloud services, space for infinite creating (makerspace), big data, augmented reality, context-aware technologies, Google-glass, a revolutionary display technology, open linked-content-offering method, and so on. Specific cases of libraries already utilizing these technologies are also discussed.

• Journal of the Architectural Institute of Korea Planning & Design
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• v.36 no.5
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• pp.53-58
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• 2020

The purpose of this study is to build a database of Spatial information Bigdata of cities using satellite images and spatial information, and to examine the correlations with the surface temperature. Using architectural structure and usage in building information, DEM and Slope topographical information for constructed with 300 × 300 mesh grids for Busan. The satellite image is used to prepare the Normalized Difference Built-up Index (NDBI), Normalized Difference Vegetation Index (NDVI), Bare Soil Index (BI), and Land Surface Temperature (LST). In addition, the building area in the grid was calculated and the building ratio was constructed to build the urban environment DB. In architectural structure, positive correlation was found in masonry and concrete structures. On the terrain, negative correlations were observed between DEM and slope. NDBI and BI were positively correlated, and NDVI was negatively correlated. The higher the Building ratio, the higher the surface temperature. It was found that the urban environment DB could be used as a basic data for urban environment analysis, and it was possible to quantitatively grasp the impact on the architecture and urban environment by adding local meteorological factors. This result is expected to be used as basic data for future urban environment planning and disaster prevention data construction.

• Proceedings of the Korea Contents Association Conference
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• 2019.05a
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• pp.389-390
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• 2019

본 연구의 목적은 현대 빅데이터 시대에서 급격히 발전하고 있는 사회적 배경아래, 현대 디자인 문화가 내포된 건축사상을 바탕으로, 중국의 4개 현대 상업건축 사례에 대한 디자인 문화 표현 특징에 대해 분석을 진행하였다. 현대 상업건축 실내 공간의 문화성은 주로 다섯 가지 측면에서 나타난다. 전통, 지역, 대중, 기술, 생태, 이것을 복합적으로 통합하여, 상업건축의 지속가능성과 다양성을 촉진한다.