• Proceedings of the Korea Information Processing Society Conference
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• 2016.04a
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• pp.225-228
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• 2016

CPS(Cyber Physical System)는 사이버 세계(cyber world)와 물리적 세계(physical word)를 연결하여, 현실과 사이버의 정보를 융합 분석하고, 분석한 데이터를 현실에 Feedback 하는 자동적이고 지능적인 제어 시스템이다. 이러한 CPS는 빅데이터를 분석하여 사용자에게 알맞은 정보를 제공해 주며 딥러닝(Deep Learning)을 통해 정확하고 세밀한 Feedback을 제공하는 등 이종 복합 시스템 간의 고신뢰성과 실시간성을 보장하는 무결점 자율 제어 시스템으로 주목 받고 있다. 실생활에서는 의료, 헬스케어, 교통, 에너지, 홈, 국방, 재난대응, 농업, 제조 등에서 폭 넓게 사용되고 있다. 해외에서는 이와 같은 CPS를 이용해 한 분야에 세밀하게 접목시켜 발전을 도모하며, CPS에 의해 변혁되는 데이터 구동형 사회를 준비하고 있다. 하지만, 이러한 CPS를 사용할 때, 보안의 문제점으로 대규모 정전사태가 발생하고, 생명을 위협하는 등의 취약점 또한 드러나고 있어 이에 대한 보안의 중요성과 CPS의 적용분야를 파악하여 전반적인 보안 문제점을 분석하고자 한다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2024.01a
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• pp.153-155
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• 2024

본 논문은 진접선 개통 이후 급증하는 서울 지하철 4호선의 혼잡 문제와 현재 진행 중인 장애인 차별 반대 시위를 다룬다. 네이버의 지도 API를 활용해 위도와 경도 데이터를 추출하고 지하철 노선별 장애인 승객 수와 최대 지연시간을 시각화한다. 2호선과 4호선의 혼잡도가 표시되어 문제의 심각성을 알 수 있다. 평균 출퇴근 시간 탑승 및 하차 수치를 분석하여 4호선 편의시설 개선, 2·4호선 열차 운행 횟수 늘리기, 환승역 운영 최적화 등 전략적 권장 사항을 제시한다. 제안된 대책은 서울시 지하철 시스템의 접근성 향상, 혼잡완화, 전반적인 효율성 제고를 통해 보다 폭넓은 교통시설 개선과 승객 편의 증진에 기여하는 것을 목표로 하고 있다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2020.01a
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• pp.143-144
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• 2020

4차 산업 시대가 도래하여 빅데이터와 딥러닝 기술은 다양한 분야에서 아주 중요한 기술로 자리 잡고 있으며, 현재 세계 여러 분야에서 이 기술들을 이용하여 일상, 산업 분야에 적용을 시키고자 한다. 국내에서는 스마트 팩토리, 스마트 시티와 같은 분야에 적용하고 있다. 본 논문에서는 스마트 시티에 적용할 수 있는 횡단보도 상황을 인지하여 교통제어에 활용할 수 있는 빅데이터를 생산하거나 효율적인 교통제어에 활용할 수 있도록 Nvidia Jetson TX2와 실시간 객체 감지 기술인 YOLO v3를 이용하여 횡단보도용 상황 인식을 위한 영상인식 장치를 개발하였다. 제안하는 기술들을 이용하여 스마트시티 구축에 활용할 수 있고, 실시간으로 추가적으로 필요한 객체를 감지하여 확장이 용이한 장점이 있다. 또한 구현에서 효율성을 높이기 위하여 에지 컴퓨팅, 스페이스 디텍션과 같은 기술들을 활용하였다.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2014.06a
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• pp.311-315
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• 2014

최근 조선기술의 발달과 해운업체의 요구로 선박이 점차 고속화 대형화됨에 따라 선박의 통항량은 매년 증가하고 있으며, 해양사고의 위험도 함께 높아지고 있다. 따라서 전세계 대부분의 국가에서 해양사고를 미연에 방지하고자 해상교통관제 시스템을 설치 운영하고 있는 실정이다. 그러나 그러한 안전장치에도 불구하고 해양사고 발생하였다면 VTS는 보고체계에 따라 사고내용을 신속하고 정확하게 전파하는 등 초동조치를 취하여 더 이상 사고위험이 진행되지 않도록 하여야 한다. 하지만 각종 사건이나 사고가 발생하면 상황 보고 및 지휘 체계는 아직 팩스나 구두보고에 의한 방법이 주로 사용되고 있어 신속하고 효율적인 사고처리업무를 저하시킨다. 이 연구에서는 팩스나 구두보고 등 그동안 사용되었던 사고처리체계의 문제점을 보완하고 해양사고를 효율적으로 관리하기 위한 해양사고관리시스템을 제안하고자 한다.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.8
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• pp.301-310
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• 2021

The TATI model is a Traffic Accident Text to RGB Image model, which is a methodology proposed in this paper for predicting the severity of traffic accidents. Traffic fatalities are decreasing every year, but they are among the low in the OECD members. Many studies have been conducted to reduce the death rate of traffic accidents, and among them, studies have been steadily conducted to reduce the incidence and mortality rate by predicting the severity of traffic accidents. In this regard, research has recently been active to predict the severity of traffic accidents by utilizing statistical models and deep learning models. In this paper, traffic accident dataset is converted to color images to predict the severity of traffic accidents, and this is done via CNN models. For performance comparison, we experiment that train the same data and compare the prediction results with the proposed model and other models. Through 10 experiments, we compare the accuracy and error range of four deep learning models. Experimental results show that the accuracy of the proposed model was the highest at 0.85, and the second lowest error range at 0.03 was shown to confirm the superiority of the performance.

• Journal of Digital Convergence
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• v.14 no.11
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• pp.289-295
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• 2016

Subway is a future-oriented means of transportation that can be safely and quickly mass transport many passengers than buses and taxis. Congestion growth due to the increase of the metro users is one of the factors that hinder citizens' rights to comfortably use the subway. Accordingly, congestion prediction in the subway is one of the ways to maximize the use of passenger convenience and comfort. In this paper, we monitor the level of congestion in real time via the existing congestion on the metro using multiple regression analysis and big data processing, as well as their departure station and arrival station information More information about the transfer stations offer a personalized congestion prediction system. The accuracy of the predicted congestion shows about 81% accuracy, which is compared to the real congestion. In this paper, the proposed prediction and recommendation application will be a help to prediction of subway congestion and user convenience.

• Informatization Policy
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• v.27 no.4
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• pp.67-84
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• 2020

This study proposes a smart city service revitalization policy based on communication facility infrastructure in 5G CPS - the core of the 4th industrial revolution, R&D, and related legislations. The 5G CPS is a converged form of ICT technologies, communications facilities, and physical systems. In this study, we propose methods of creating new services for the smart city domain based on communication facilities and the cloud platform in 5G CPS - first, by improving the communication methods classification system based on the facility scale; second, by establishing the national telecommunication facility infrastructure and making long-term investment; third, by reorganizing the Smart City Act aimed at activating new services; and lastly, by expanding the national data analytics R&D and policy support.

• Journal of Korea Society of Industrial Information Systems
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• v.21 no.4
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• pp.67-78
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• 2016

Recently many countries around the world are actively promoting smart city projects to address various urban problems such as traffic congestion, housing shortage, and energy scarcity. Due to development of the Internet of Things (IoT), the development of a smart city with sustainability, convenience, and environment-friendliness was enabled through the effective control and reuse of urban resources. The purpose of this study is to analyze the technical trends of IoT and present a development plan for smart city which is one of the applications of the IoT. To this end, the news articles of the Electronic Times between 2013 and 2015were analyzed using the text mining technique and smart city development cases of other countries were investigated. The analysis results revealed the close relationships of big data, cloud, platforms, and sensors with smart city. For the successful development of a smart city, first, all the interested parties in the city must work together to create new values throughout the entire process of value chain. Second, they must utilize big data and disclose public data more actively than they are doing now. This study has made academic contribution in that it has presented a big data analysis method and stimulated follow-up studies. For the practical contribution, the results of this study provided useful data for the policy making of local governments and administrative agencies for smart city development. This study may have limitations in the incorporation of the total trends because only the news articles of the Electronic Times were selected to analyze the technical trends of the IoT.

• Journal of Korean Society of Transportation
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• v.33 no.1
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• pp.14-28
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• 2015

Numerous research has been conducted using internet search data since the mid-2000s. For example, Google Inc. developed a service predicting influenza patterns using the internet search data. The main objective of this study is to prove the hypothesis that highway traffic indices are similar to the internet search patterns. In order to achieve this objective, a model to predict the number of vehicles entering the expressway and space-mean speed was developed and the goodness-of-fit of the model was assessed. The results revealed several findings. First, it was shown that the Google search traffic was a good predictor for the TCS entering traffic volume model at sites with frequent commute trips, and it had a negative correlation with the TCS entering traffic volume. Second, the Naver search traffic was utilized for the TCS entering traffic volume model at sites with numerous recreational trips, and it was positively correlated with the TCS entering traffic volume. Third, it was uncovered that the VDS speed had a negative relationship with the search traffic on the time series diagram. Lastly, it was concluded that the transfer function noise time series model showed the better goodness-of-fit compared to the other time series model. It is expected that "Big Data" from the internet search data can be extensively applied in the transportation field if the sources of search traffic, time difference and aggregation units are explored in the follow-up studies.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.5
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• pp.72-84
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• 2017

Together with the Big Data of the 4th Industrial Revolution, the traffic information system has been changed to an section detection system by the point detection system. With DTG(Digital Tachograph) data based on Global Navigation Satellite System, the properties of raw data and data according to processing step were examined. We identified the vehicle trajectory, the link travel time of individual vehicle, and the link average travel time which are generated according to the processing step. In this paper, we proposed a application method for traffic management as characteristics of processing data. We selected the historical data considering the data management status of the center and the availability at the present time. We proposed a method to generate the Travel Time Index with historical link average travel time which can be collected all the time with wide range. We propose a method to monitor the traffic congestion using the Travel Time Index, and analyze the case of intersections when the traffic operation method changed. At the same time, the current situation which makes it difficult to fully utilize DTG data are suggested as limitations.