• Title/Summary/Keyword: 공간 빅 데이터

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A Study on the Architecture Design of Road and Facility Operation Management System for 3D Spatial Data Processing (3차원 공간데이터 처리를 위한 차로 및 시설물 운영 관리 시스템 아키텍처 설계 연구)

  • KIM, Duck-Ho;KIM, Sung-Jin;LEE, Jung-Uck
    • Journal of the Korean Association of Geographic Information Studies
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    • v.24 no.4
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    • pp.136-147
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    • 2021
  • Autonomous driving-related technologies are developing step by step by applying the degree of driving. It is essential that operational management technology for roads where autonomous vehicles move should also develop in line with autonomous driving technology. However, in the case of road operation management, it is currently managed using only two-dimensional information, showing limitations in the systematic operation management of lane and facility information and maintenance. This study proposed a plan to construct an operation management system architecture capable of 3D spatial information-based operation management by designing a convergence database that can process real-time big data with high-definition road map data. Through this study, when using a high-definition road map based operation management system for lane and facility maintenance in the future, it is possible to visualize and manage facilities, edit and analyze data of multiple users, link various GIS S/W and efficiently process large scale of real-time data.

An Analysis of the Public Data for Making the Ambient Intelligent Service (공간지능화서비스 구현을 위한 공공데이터 분석)

  • Kim, Mi-Yun;Seo, Dong-Jo
    • Journal of Digital Convergence
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    • v.12 no.12
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    • pp.313-321
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    • 2014
  • In current society, the digital era that makes enormous amount of data, and the diversified city, the smart space, which has characteristics of creating, collecting and representing data, is appeared. After 2012, in the social media environment called hyper-connected society with wide-spread smart phone, people started to get interested in public data and big data by generalized mobile device and SNS. At first, development of forming platform of data was focused, but now, many different idea from diverse area have been suggested about data analysis and usage to visualize the space intellectualization service. To focus on the visualization process to increase the usage of this public data for ordinary people more than specialized people, this research grasps the present condition of open data and public data service from the current public data portal and considers the applicability of them. As the result of research, the analysis and application of data to ordinary people decrease the use of paper documents, and this research will help to develop the application which is fast and accurate about individual behavior and demand to utilize public data service in intellectual space.

Comparison of Machine Learning Techniques in Urban Weather Prediction using Air Quality Sensor Data (실외공기측정기 자료를 이용한 도심 기상 예측 기계학습 모형 비교)

  • Jong-Chan Park;Heon Jin Park
    • The Journal of Bigdata
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    • v.6 no.2
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    • pp.39-49
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    • 2021
  • Recently, large and diverse weather data are being collected by sensors from various sources. Efforts to predict the concentration of fine dust through machine learning are being made everywhere, and this study intends to compare PM10 and PM2.5 prediction models using data from 840 outdoor air meters installed throughout the city. Information can be provided in real time by predicting the concentration of fine dust after 5 minutes, and can be the basis for model development after 10 minutes, 30 minutes, and 1 hour. Data preprocessing was performed, such as noise removal and missing value replacement, and a derived variable that considers temporal and spatial variables was created. The parameters of the model were selected through the response surface method. XGBoost, Random Forest, and Deep Learning (Multilayer Perceptron) are used as predictive models to check the difference between fine dust concentration and predicted values, and to compare the performance between models.

Hadoop-based Large Data Management and Analysis for Parking Enforcement System (주정차 단속 시스템을 위한 하둡 기반 대용량 데이터 관리 및 분석)

  • Baek, Na-Eun;Song, Youngho;Shin, Jaehwan;Chang, Jae-Woo
    • Proceedings of the Korea Information Processing Society Conference
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    • 2017.04a
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    • pp.429-432
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    • 2017
  • 자동차 보급률 증가로 인해 교통 혼잡, 불법 주정차 등의 사회적 문제가 발생하고 있다. 특히 불법 주정차는 교통 혼잡, 주차 공간 부족 등 부가적인 문제를 발생시키고 있다. 따라서 각 지방자치단체에서는 불법 주정차 문제를 해결하기 위한 방안을 연구하고 있다. 그러나 이러한 방안은 초기 비용 발생 및 인력 부족 등의 한계가 있다. 한편, 정보통신의 발달에 따라 공공 업무에도 대량의 공공데이터를 효율적으로 처리하기 위한 연구가 진행되고 있다. 하지만 이러한 연구 또한 빅데이터 처리 플랫폼 부족 및 분석 시스템이 미흡한 한계가 존재한다. 따라서 본 논문에서는 불법 주정차 데이터와 같은 공공 데이터를 효율적으로 처리하기 위해, 주정차 단속 시스템을 위한 하둡 기반 대용량 데이터 관리 및 분석 시스템을 제안한다. 제안하는 시스템은 첫째, 주차단속을 수행할 때 주차단속 데이터를 하이브(Hive)를 통해 저장하고, 단속된 차량의 차주를 검색하여 단속임을 알리거나 과태료를 부과한다. 둘째, 웹 인터페이스를 통해 수집된 주차단속 데이터에 대한 다양한 분석을 수행하고, 분석된 데이터에 대한 R을 이용한 시각화를 제공한다.

Spatial Clustering Analysis based on Text Mining of Location-Based Social Media Data (위치기반 소셜 미디어 데이터의 텍스트 마이닝 기반 공간적 클러스터링 분석 연구)

  • Park, Woo Jin;Yu, Ki Yun
    • Journal of Korean Society for Geospatial Information Science
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    • v.23 no.2
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    • pp.89-96
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    • 2015
  • Location-based social media data have high potential to be used in various area such as big data, location based services and so on. In this study, we applied a series of analysis methodology to figure out how the important keywords in location-based social media are spatially distributed by analyzing text information. For this purpose, we collected tweet data with geo-tag in Gangnam district and its environs in Seoul for a month of August 2013. From this tweet data, principle keywords are extracted. Among these, keywords of three categories such as food, entertainment and work and study are selected and classified by category. The spatial clustering is conducted to the tweet data which contains keywords in each category. Clusters of each category are compared with buildings and benchmark POIs in the same position. As a result of comparison, clusters of food category showed high consistency with commercial areas of large scale. Clusters of entertainment category corresponded with theaters and sports complex. Clusters of work and study showed high consistency with areas where private institutes and office buildings are concentrated.

A Visitor Study of The Exhibition of Using Big Data Analysis which reflects viewing experiences

  • Kang, Ji-Su;Rhee, Bo-A
    • Journal of the Korea Society of Computer and Information
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    • v.27 no.2
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    • pp.81-89
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    • 2022
  • This study aims to analyze the images of Instagram posts and to draw implcations regarding the exhibition of . This study collects and crawl 24,295 images from Instagram posts as a dataset. We use the Google Cloud Vision API for labeling the images and a total of 212,567 clusters of labels are finally classified into 9 categories using Word2Vec. The categories of museum spaces, photo zone, architecture category are dominant along with people category. In conclusion, visitors curate their experiences and memories of physical places and spaces while they are experiencing with the exhibition. This result reproves the results of previous studies which emphasize a sense of social presence and place making. The convergent approach of art management and art technology used in this study help museum professionals have an insight on big data based visitor research on a practical level.

Spatial clustering of pedestrian traffic accidents in Daegu (대구광역시 교통약자 보행자 교통사고 공간 군집 분석)

  • Hwang, Yeongeun;Park, Seonghee;Choi, Hwabeen;Yoon, Sanghoo
    • Journal of Digital Convergence
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    • v.20 no.3
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    • pp.75-83
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    • 2022
  • Korea, which has the highest pedestrian fatality rate among OECD countries, is making efforts to improve the safe walking environment by enacting laws focusing on pedestrian. Spatial clustering was conducted with scan statistics after examining the social network data related to traffic accidents for children and seniors. The word cloud was used to examine people's recognition Campaigns for children and literature survey for seniors were in main concern. Naedang and Yongsan are the regions with the highest relative risk of weak pedestrian for children and seniors. On the contrary, Bongmu and Beomeo are the lowest relative risk region. Naedang-dong and Yongsan-dong of Daegu Metropolitan City were identified as vulnerable areas for pedestrian safety due to the high risk of pedestrian accidents for children and the elderly. This means that the scan statistics are effective in searching for traffic accident risk areas.

A Study on Stowage Automation Algorithm for Cargo Stowage Optimization of Vehicle Carriers (차량 운반선의 화물 적재 최적화를 위한 적재 자동화 알고리즘 연구)

  • JI Yeon Kim;Young-Jin Kang;Jeong, Seok Chan;Hoon Lee
    • The Journal of Bigdata
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    • v.7 no.2
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    • pp.129-137
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    • 2022
  • With the development of the 4th industry, the logistics industry is evolving into a smart logistics system. However, ship work that transports vehicles is progressing slowly due to various problems. In this paper, we propose an stowage automation algorithm that can be used for cargo loading of vehicle carriers that shortens loading and unloading work time. The stowage automation algorithm returns the shortest distance by searching for a loading space and a movable path in the ship in consideration of the structure of the ship. The algorithm identifies walls, ramps and vehicles that have already been shipped, and can work even with randomly placed. In particular, it is expected to contribute to developing a smart logistics system for vehicle carriers by referring to the ship's master plan to search for vehicle loading and unloading space in each port and predict the shortest movable path.

A Study on the Contemporary Definition of 'GARDEN' - Keyword Analysis used Literature Research and Big Data - ('정원'의 시대적 정의에 관한 연구 - 문헌연구와 빅데이터를 활용한 키워드 분석을 중심으로-)

  • Woo, Kyungsook;Suh, Joo Hwan
    • Journal of the Korean Institute of Landscape Architecture
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    • v.44 no.5
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    • pp.1-11
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    • 2016
  • There has been an increasingly high interest in gardens and garden design in Korea recently. However, the usage of the term 'garden' is extremely varied and complex, and there has been very little academic research made on the meaning of garden. Therefore, this research attempts to investigate the ideas of current gardens and to elucidate their changing patterns by means of extensive literature research and big data analysis. The notion of garden in the past was broad including not only private space such as Madang(마당) and Teul(뜰), but also even field and grass land as public outdoor space. Yet, the meaning has become smaller to merely private space due to the change of dwelling systems due to high industrial development of the 20th century. Furthermore, the introduction of urban parks as an interactive space between nature and humans, the similar spatial function of gardens, has blurred the boundary between garden and park, which created confusion in understanding the concept of a garden. After all, garden is a subject for humans. The meanings of garden need to be recognized from various points of view since garden itself is a creation by the sum of diverse fields such as natural and social sciences as well as culturology. This discussion on the meaning of garden in the present day will give a conceptual foundation for future research on gardens and garden design. Also, the big data analysis employed here as a research method can help other similar research topics, particularly semantics in landscape architecture.

Influence of Big Data Based Majib Apps' Service Quality on Use Satisfaction and Reuse Intention of Majib Apps - Moderating Effect of Review Informativity - (빅데이터 기반 맛집 어플리케이션의 서비스품질이 앱 이용만족과 재이용의도에 미치는 영향 - 사용후기 정보성의 조절효과 -)

  • Lee, Shin-Woo;Jeon, Hyeon-Mo
    • Culinary science and hospitality research
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    • v.22 no.5
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    • pp.64-81
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    • 2016
  • The study, based on existing studies, explored influencing relationship, suggesting app service quality and user reviews as previous elements to affect use satisfaction about users' comments based on big data and reuse intention. The study includes a comparative analysis of existing studies. Based on such analysis results, the authors looked into app service quality elements perceived by gourmet restaurant app users and the role of user reviews, and suggested practical implications that can help the development and operation of gourmet restaurant app contents. The study subjects were male and female consumers who over 20 years old throughout Korea who had not a searched smartphone gourmet restaurant app in the three months preceding the survey. The subjects were selected from consumers who search the restaurantsby using restaurant apps like Mango plate, Dining code, Hot place, and selecting restaurants. Among them, consumers with experience using restaurants were finally selected for the survey. According to the results, reliability, informativity, and system capability, among service quality, had positive influences on app use satisfaction, while design and mobility had no effect. App use satisfaction had positive influences on app reuse intention. User comment informativity played a controlling role. The study explored the importance of app service quality and user review informativity as elements that affect continued use of gourmet restaurant apps by dining-out consumers.