• Title/Summary/Keyword: 공간 빅 데이터

Search Result 306, Processing Time 0.026 seconds

Estimating Visitors on Water-friendly Space in the River Using Mobile Big Data and UAV (통신 빅데이터와 무인기 영상을 활용한 하천 친수지구 이용객 추정)

  • Kim, Seo Jun;Kim, Chang Sung;Kim, Ji Sung
    • Ecology and Resilient Infrastructure
    • /
    • v.6 no.4
    • /
    • pp.250-257
    • /
    • 2019
  • Recently, 357 water-friendly space were established near the main streams of the country through the Four Major Rivers Project, which was used as a resting and leisure space for the citizens, and the river environment and ecological health were improved. We are working hard to reduce the number of points and plan and manage the water-friendly space. In particular, attempts are being made to utilize mobile big data to make more scientific and systematic research on the number of users. However, when using mobile big data compared to the existing method of conducting field surveys, it is possible to easily identify spatial user movement patterns, but it is different from the actual amount of use, so various verifications are required to solve this problem. Therefore, this study evaluated the accuracy of estimating the number of users using mobile big data by comparing the number of visitors using mobile big data and the number of visitors using drone for Samrak ecological park located in the mouth of Nakdong River. As a result, in the river hydrophilic district, it was difficult to accurately estimating the usage pattern of each facility due to the low precision of pCELL, and it was confirmed that the usage patterns in the park could be distorted due to the signals stopped at roads and parking lots. Therefore, it is necessary to improve the number of pCELLs in the water-friendly space and to estimate the number of visitors excluding facilities such as roads and parking lots in future mobile big data processing.

The Method of Urban Decline Sensitivity Analysis Using the Big Data (빅데이터를 활용한 도시쇠퇴 민감도 분석 방안)

  • Yang, Dong-Suk
    • Proceedings of the Korea Information Processing Society Conference
    • /
    • 2015.10a
    • /
    • pp.1115-1116
    • /
    • 2015
  • 도시재생종합정보시스템에서 전국 시군구단위 도시쇠퇴 현황은 인구사회 산업경제 물리환경이라는 종합적인 지표를 활용하여 분석하고 있다. 그러나 읍면동 단위의 도시쇠퇴 분석은 신뢰성 있는 데이터 확보의 어려움으로 몇 개의 지표만을 제공하고 있는 실정이다. 도시재생 사업이 활성화되면서 좀 더 정확한 도시쇠퇴 분석이 요구되는 상황이여서 이를 해결하기 위하여 빅데이터 기술을 적용한 방안을 제시하였다. 제시된 방법으로 분석된 지구단위의 도시쇠퇴 현황은 세밀한 공간단위의 도시쇠퇴 분석은 물론 추후 도시재생 모니터링 등에 활용될 것으로 기대된다.

A Study on Design and Development for Online Search Advertisement Platform using Big Data Analysis System (빅데이터 분석 시스템을 활용한 온라인 검색 광고 플랫폼 설계 및 개발에 관한 연구)

  • Noh, Seon-Taek;Hong, Seung-Hyung;Kim, Kyung-Soo;Song, Young-Ki;Kim, Hwan-Cheol
    • Proceedings of the Korea Information Processing Society Conference
    • /
    • 2012.11a
    • /
    • pp.187-190
    • /
    • 2012
  • 온라인 검색 광고는 인터넷 사용자의 증가, 그리고 온라인 광고 수요의 규모가 커짐에 따라 광고 시장에서 보조적인 역할에서 벗어나 주도적인 위치로 변화하고 있다. 지속적인 규모성장과 수요 증가에도 불구하고 기존의 관계형 데이터베이스에 의존한 온라인 검색 광고 플랫폼은 구조적인 한계로 인해 유연한 자원 확장이나 분석속도의 보장성을 유지할 수 없다. 본 논문에서는 빅데이터 분석 시스템을 이용하여 온라인 검색 광고 플랫폼을 설계 및 구현함으로써, 데이터 저장 공간을 유연하게 확장할 수 있으며, 일정한 시간으로 수렴할 수 있는 안정적인 분석 속도를 유지하는 시스템을 제안한다.

A Time Series Analysis of Urban Park Behavior Using Big Data (빅데이터를 활용한 도시공원 이용행태 특성의 시계열 분석)

  • Woo, Kyung-Sook;Suh, Joo-Hwan
    • Journal of the Korean Institute of Landscape Architecture
    • /
    • v.48 no.1
    • /
    • pp.35-45
    • /
    • 2020
  • This study focused on the park as a space to support the behavior of urban citizens in modern society. Modern city parks are not spaces that play a specific role but are used by many people, so their function and meaning may change depending on the user's behavior. In addition, current online data may determine the selection of parks to visit or the usage of parks. Therefore, this study analyzed the change of behavior in Yeouido Park, Yeouido Hangang Park, and Yangjae Citizen's Forest from 2000 to 2018 by utilizing a time series analysis. The analysis method used Big Data techniques such as text mining and social network analysis. The summary of the study is as follows. The usage behavior of Yeouido Park has changed over time to "Ride" (Dynamic Behavior) for the first period (I), "Take" (Information Communication Service Behavior) for the second period (II), "See" (Communicative Behavior) for the third period (III), and "Eat" (Energy Source Behavior) for the fourth period (IV). In the case of Yangjae Citizens' Forest, the usage behavior has changed over time to "Walk" (Dynamic Behavior) for the first, second, and third periods (I), (II), (III) and "Play" (Dynamic Behavior) for the fourth period (IV). Looking at the factors affecting behavior, Yeouido Park was had various factors related to sports, leisure, culture, art, and spare time compared to Yangjae Citizens' Forest. The differences in Yangjae Citizens' Forest that affected its main usage behavior were various elements of natural resources. Second, the behavior of the target areas was found to be focused on certain main behaviors over time and played a role in selecting or limiting future behaviors. These results indicate that the space and facilities of the target areas had not been utilized evenly, as various behaviors have not occurred, however, a certain main behavior has appeared in the target areas. This study has great significance in that it analyzes the usage of urban parks using Big Data techniques, and determined that urban parks are transformed into play spaces where consumption progressed beyond the role of rest and walking. The behavior occurring in modern urban parks is changing in quantity and content. Therefore, through various types of discussions based on the results of the behavior collected through Big Data, we can better understand how citizens are using city parks. This study found that the behavior associated with static behavior in both parks had a great impact on other behaviors.

Application Study of Vessel Traffic Service: Dynamic Analysis of AIS for Shocheongcho Ocean Research Station (해상교통관제정보 활용 연구: 빅데이터 기반 해양 공간 선박 활동 특성 해석)

  • Park, Ju-Han;Kim, Seung-Ryong;Yang, Chan-Su
    • Proceedings of the Korean Institute of Navigation and Port Research Conference
    • /
    • 2019.05a
    • /
    • pp.206-207
    • /
    • 2019
  • 우리나라에서 해상교통관제시스템(Vessel Traffic Service, VTS) 구역을 설정하여, 관제사를 중심으로 한 VTS와 선박사이의 해상교통상황 등의 교환을 통해 항만의 안전과 항만운영의 효율을 높이고 있다. 향후, 연안으로 확대될 예정이다. 더 넓은 해역에 대해서는 해양안전종합정보시스템(GICOMS)이 있으며, 선박자동식별장치 (AIS), 장거리위치추적시스템 (LRIT) 등에서 송신하는 선박의 운항정보를 수신하여 전자해도에 표시하고 있다. 이와 같은 선박관제정보는 빅데이터로 향후 자동화된 분석과 제원체계가 요구된다. 여기서는 해상교통관제정보 기초 활용 연구로, 소청초 종합해양과학기지주변의 AIS (Automatic Identification System)정보를 사용하여 선박 활동 특성 해석을 진행하였다.

  • PDF

A Study on the Agent Based Infection Prediction Model Using Space Big Data -focusing on MERS-CoV incident in Seoul- (공간 빅데이터를 활용한 행위자 기반 전염병 확산 예측 모형 구축에 관한 연구 -서울특별시 메르스 사태를 중심으로-)

  • JEON, Sang-Eun;SHIN, Dong-Bin
    • Journal of the Korean Association of Geographic Information Studies
    • /
    • v.21 no.2
    • /
    • pp.94-106
    • /
    • 2018
  • The epidemiological model is useful for creating simulation and associated preventive measures for disease spread, and provides a detailed understanding of the spread of disease space through contact with individuals. In this study, propose an agent-based spatial model(ABM) integrated with spatial big data to simulate the spread of MERS-CoV infections in real time as a result of the interaction between individuals in space. The model described direct contact between individuals and hospitals, taking into account three factors : population, time, and space. The dynamic relationship of the population was based on the MERS-CoV case in Seoul Metropolitan Government in 2015. The model was used to predict the occurrence of MERS, compare the actual spread of MERS with the results of this model by time series, and verify the validity of the model by applying various scenarios. Testing various preventive measures using the measures proposed to select a quarantine strategy in the event of MERS-CoV outbreaks is expected to play an important role in controlling the spread of MERS-CoV.

Smartphone Usage Data Collection Application and Management Program for Big Data Analysis (빅데이터 분석을 위한 스마트폰 사용 데이터 수집 앱 및 관리 프로그램)

  • Jo, Seong-Min;Oh, Seung-Hyeon;Ahn, Ji-Woo;Lee, Myung-Suk
    • Proceedings of the Korean Society of Computer Information Conference
    • /
    • 2021.07a
    • /
    • pp.225-228
    • /
    • 2021
  • 본 연구는 스마트폰 중독과 관련된 다양한 분석을 위한 스마트폰 사용 앱과 관리자 웹을 개발하고자 한다. 연구방법으로 이전 연구에서 중요한 변수로 작용되었던 '화면 켠 횟수', '실사용시간-인지사용시간' 변수를 분석할 있도록 적용하여 스마트폰 사용시간, 사용량, 사용 앱, 화면 잠금을 해제한 횟수 등 다양한 데이터 수집이 가능한 앱을 개발한다. 관리자 웹은 수집된 데이터를 저장, 분석할 수 있는 공간으로 사용할 것이다. 앱에서 수집된 데이터는 서버에 전송한 후, 시각화 분석 기능을 제공하는 관리 프로그램으로 개발하여 스마트폰 중독 연구에 사용한다. 향후 데이터 수집과 사용 목적에 동의한 사용자를 모집하여 데이터를 수집하고 스마트폰 사용 패턴, 데이터마이닝, 중독 등과 관련된 다양한 분석을 할 것이다. 이를 통해 보다 정확하고 효과적인 스마트폰 중독 진단이 가능해질 것과 나아가 스마트폰 중독 치료방안 연구에 기여할 것으로 기대한다.

  • PDF

A Public Open Civil Complaint Data Analysis Model to Improve Spatial Welfare for Residents - A Case Study of Community Welfare Analysis in Gangdong District - (거주민 공간복지 향상을 위한 공공 개방 민원 데이터 분석 모델 - 강동구 공간복지 분석 사례를 중심으로 -)

  • Shin, Dongyoun
    • Journal of KIBIM
    • /
    • v.13 no.3
    • /
    • pp.39-47
    • /
    • 2023
  • This study aims to introduce a model for enhancing community well-being through the utilization of public open data. To objectively assess abstract notions of residential satisfaction, text data from complaints is analyzed. By leveraging accessible public data, costs related to data collection are minimized. Initially, relevant text data containing civic complaints is collected and refined by removing extraneous information. This processed data is then combined with meaningful datasets and subjected to topic modeling, a text mining technique. The insights derived are visualized using Geographic Information System (GIS) and Application Programming Interface (API) data. The efficacy of this analytical model was demonstrated in the Godeok/Gangil area. The proposed methodology allows for comprehensive analysis across time, space, and categories. This flexible approach involves incorporating specific public open data as needed, all within the overarching framework.

An Open Source Mobile Cloud Service: Geo-spatial Image Filtering Tools Using R (오픈소스 모바일 클라우드 서비스: R 기반 공간영상정보 필터링 사례)

  • Kang, Sanggoo;Lee, Kiwon
    • Spatial Information Research
    • /
    • v.22 no.5
    • /
    • pp.1-8
    • /
    • 2014
  • Globally, mobile, cloud computing or big data are the recent marketable key terms. These trend technologies or paradigm in the ICT (Information Communication Technology) fields exert large influence on the most application fields including geo-spatial applications. Among them, cloud computing, though the early stage in Korea now, plays a important role as a platform for other trend technologies uses. Especially, mobile cloud, an integrated platform with mobile device and cloud computing can be considered as a good solution to overcome well known limitations of mobile applications and to provide more information processing functionalities to mobile users. This work is a case study to design and implement the mobile application system for geo-spatial image filtering processing operated on mobile cloud platform built using OpenStack and various open sources. Filtering processing is carried out using R environment, recently being recognized as one of big data analysis technologies. This approach is expected to be an element linking geo-spatial information for new service model development and the geo-spatial analysis service development using R.

Dynamic Load Management Method for Spatial Data Stream Processing on MapReduce Online Frameworks (맵리듀스 온라인 프레임워크에서 공간 데이터 스트림 처리를 위한 동적 부하 관리 기법)

  • Jeong, Weonil
    • Journal of the Korea Academia-Industrial cooperation Society
    • /
    • v.19 no.8
    • /
    • pp.535-544
    • /
    • 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.