• Smart Media Journal
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• v.11 no.11
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• pp.49-62
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• 2022

Recently, with the development of Smart City Solutions such as Big data, AI, IoT, Autonomous driving, and Digital twins around the world, the proliferation of various smart devices and social media, and the record of the deeds that people have left everywhere, the construction of Smart Cities using the "Big Data" environment in which so much information and data is produced that it is impossible to gauge the scale is actively underway. The Purpose of this study is to construct an objective and systematic analysis Model based on Big Data to improve the transportation convenience of citizens and formulate efficient policies in Urban Information and Public Transportation accessibility in sustainable Smart Cities following the 4th Industrial Revolution. It is also to derive the methodology of developing a Big Data-Based public transport accessibility and policy management Platform using a sustainable Urban Public DB and a Private DB. To this end, Detailed Living Areas made a division and the accessibility of basic living amenities of Gwangju Metropolitan City, and the Public Transportation system based on Big Data were analyzed. As a result, it was Proposed to construct a Big Data-based Urban Information and Public Transportation accessibility Platform, such as 1) Using Big Data for public transportation network evaluation, 2) Supporting Transportation means/service decision-making based on Big Data, 3) Providing urban traffic network monitoring services, and 4) Analyzing parking demand sources and providing improvement measures.

• The Journal of Bigdata
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• v.9 no.1
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• pp.1-16
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• 2024

In urban design and planning, establishing neighborhood units and arranging urban planning facilities are important matters to be considered first. In particular, effective arrangement considering the influence area of each urban planning facility can solve traffic problems and improve the efficiency of urban structure according to the visitors to the facility, and can be used as basic data for more effective living areas. Therefore, this study proposed a methodology to analyze the number of users, the time required for access, and the destinations of users for major urban planning facilities such as schools and neighborhood parks based on mobile communication base station data. In addition, using this methodology, the users and influence areas of major urban planning facilities in Cheonan-si were analyzed.

• The Journal of the Convergence on Culture Technology
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• v.6 no.2
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• pp.529-534
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• 2020

The development of civilization is in line with evolution of cities and transportation technology caused by industrialization. Up to now, a city has been developed owing to transportation cost reduction and needs for land utilization as a limited core business district. Continuous increase of urban population density has accompanied by lots of problems socioeconomically such as rise of land value, traffic congestion, gap between the rich and poor, air pollution, etc. Those issues are difficult to be solved in existing city ecosystem. However, a clue for solving the problems could be found in there. The design of Seoul mid-night bus route was from analysis of movement of people in the rural area by using ICT so that a city ecosystem should be firstly analyzed for solving rural issues. If the cause of those is found, big data platform construction is required to raise the life quality of citizen and the problems could be solved. Big data should be located in the middle of the platform connected with every element of city based on ICT for real-time collection, analysis and application. This paper addresses construction of big data platform and its application for sustainable smart city.

• The Journal of Bigdata
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• v.2 no.2
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• pp.1-7
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• 2017

Intelligent transportation system (ITS) has been introduced to maximize the efficiency of operation and utilization of the urban traffic facilities and promote the safety and convenience of the users. With the expansion of ITS, various traffic big data such as road traffic situation, traffic volume, public transportation operation status, management situation, and public traffic use status have been increased exponentially. In this paper, we derive structural characteristics of urban traffic according to the vehicle flow by using big data network analysis. DSRC (Dedicated Short Range Communications) data is used to construct the traffic network. The results can help to understand the complex urban traffic characteristics more easily and provide basic research data for urban transportation plan such as road congestion resolution plan, road expansion plan, and bus line/interval plan in a city.

• Informatization Policy
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• v.24 no.4
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• pp.79-92
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• 2017

As city functions develop more complex and advanced, interests in smart cities are also increasing. Smart cities refer to the cities effectively solving urban problems such as traffic, safety, welfare, and living issues by utilizing ICT. Recently, many countries are attempting to introduce big data, Internet of Things, and artificial intelligence into smart cities, but they have not yet developed into comprehensive urban services. In this paper, we review the current status of domestic and overseas smart cities and suggest ways to solve issues of data sharing and service compatibility. To this end, we propose a "Deep Learning City Framework" that incorporates the deep learning technology into smart city services, and propose a new smart city strategy that safely shares spatial and temporal data in cities and converges learning data of various cities.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.5
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• pp.130-145
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• 2021

As part of the Smart Seoul policy, the importance of using big urban data is being highlighted. Furthermore interest in the impact of transportation-related urban environmental factors such as PM10 and noise on citizen's quality of life is steadily increasing. This study established the integrated DB by matching IoT big data with transportation data, including traffic volume and speed in the microscopic Spatio-temporal scope. This data analyzed the impact of a spatial unit in the road-effect zone on environmental risk level. In addition, spatial units with similar characteristics of road traffic and environmental factors were clustered. The results of this study can provide the basis for systematically establishing environmental risk management of urban spatial units such as PM10 or PM2.5 hot-spot and noise hot-spot.

• Journal of the Korean Association of Geographic Information Studies
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• v.23 no.4
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• pp.217-233
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• 2020

This study evaluated the urban vitality of Daegu metropolitan city in 2018 using emerging geographic data such as spatial big data, Wi-Fi AP(access points) and nighttime light satellite image. The emerging geographic data were used in this research to quantify human activities in the city more directly at various spatial and temporal scales. Three spatial big data such as mobile phone data, credit card data and public transport smart card data were employed to reflect social, economic and mobility aspects of urban vitality while public Wi-Fi AP and nighttime light satellite image were included to consider virtual and physical aspects of the urban vitality. With PCA (Principal Component Analysis), five indicators were integrated and transformed to the urban vitality index at census output area by temporal slots. Results show that five clusters with high urban vitality were identified around downtown Daegu, Daegu bank intersection and Beomeo intersection, Seongseo, Dongdaegu station and Chilgok 3 district. Further, the results unveil that the urban vitality index was varied over the same urban space by temporal slots. This study provides the possibility for the integrated use of spatial big data, Wi-Fi AP and nighttime light satellite image as proxy for measuring urban vitality.

• Annual Conference of KIPS
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• 2015.10a
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• pp.1115-1116
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• 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.

• Proceedings of the Korean Society of Disaster Information Conference
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• 2022.10a
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• pp.417-418
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• 2022

최근 기후변화와 집중호우, 도시배수체계의 한계로 인해 도시침수가 빈번하게 일어나고 있으며 이에 따른 인적·물적 피해가 지속적으로 발생하고 있다. 기후변화 보고서에 따르면 우리나라 강우량은 21세기 후반까지 증가할 것으로 예측되고 있어 도시 침수 피해를 사전에 예측하고 피해 규모를 감소시키기 위한 위기 대응 시스템의 개발이 필요하다. 본 논문에서는 효율적이고 정확한 도시침수 상황관리를 가능하게 하기 위해 센서 계측 기술, IoT, 빅데이터 등의 최신 기술을 적용한 도시침수 모니터링 시스템을 설계하였다. 도시침수 모니터링 시스템은 스마트 레인센서, 스마트 지표 침수계측센서, 스마트 지표하 침수계측센서 등 다양한 종류의 센서와 연동되어 있으며 시스템에서 계측 데이터를 감시, 분석, 통계할 수 있어 효율적인 재난관리 대응이 가능하다. 또한, 도시침수 모니터링 시스템은 재난상황 발생 시 사전에 침수예상지역을 분석하고 대피계획 및 시점을 제공함으로써 인명피해를 줄이고 급작스런 홍수에 대비할 수 있다.

• Annual Conference of KIPS
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• 2014.04a
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• pp.939-940
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• 2014

본 논문에서는 CCTV설치 증가로 많은 양의 영상정보 데이터가 저장되고 있지만 활용되지 못하고 있는 문제를 해결하기 위해서 빅데이터 분석 동향과 기술을 조사 및 분석하였다. 이를 통해 영상정보 빅데이터 분석을 하고 소상공인 창업지원 서비스와 도시 인프라 개 보수 지원 서비스를 제공하는 도시고도화 지원 시스템을 설계하였다.