• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2021년도 추계학술발표대회
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• pp.128-130
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• 2021

Smart cities collect data from thousands of IoT-based sensor devices for intelligent application-based services. Centralized cloud servers support application tasks with higher computation resources but introduce network latency. Fog layer-based data centers bring data processing at the edge, but fewer available computation resources and poor task allocation strategy prevent real-time data analysis. In this paper, tasks generated from devices are distributed as high resource and low resource intensity tasks. The novelty of this research lies in deploying a virtual node assigned to each cluster of IoT sensor machines serving a joint application. The node allocates tasks based on the task intensity to either cloud-computing or fog computing resources. The proposed Task Allocation Strategy provides seamless allocation of jobs based on process requirements.

• International Journal of Internet, Broadcasting and Communication
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• 제16권2호
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• pp.112-118
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• 2024

We Design The problem of underdeveloped areas is emerging as a social problem. Industrialization drove the population to the cities, creating underdeveloped areas. Underdeveloped areas are causing social problems such as population decline and aging. It is necessary to study the continuous tourism development of underdeveloped areas through development and improvement projects. Using social media big data to investigate keywords in underdeveloped areas and see the connection between keywords. The purpose of this study was to conduct core research divided by type and to investigate the keywords of tourism in underdeveloped areas through concor analysis of underdeveloped areas. As a result of the study, keywords were connected for each type of redevelopment, regional development, regional economy, and underdeveloped areas. Through this, the keywords for sustainable tourism in underdeveloped areas were identified. It is hoped that this study will develop sustainable tourism for the keywords of underdeveloped areas.

• 한국빅데이터학회지
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• 제8권1호
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• pp.83-97
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• 2023

프로젝트의 평가란 프로젝트의 진행상황과 결과물을 평가하는 과정이다. 스마트시티 프로젝트들은 시스템 구성요소별(인프라, 서비스, 플랫폼)로 프로젝트가 나뉘기도 하고, 여러 가지 서비스별로 프로젝트들이 동시에 진행되기도 한다. 또한 추가 프로젝트를 통하여 서비스들이 개발되고 확장되기도 한다. 이렇게 여러 가지 프로젝트들이 복합적으로 진행되는 스마트시티가 목표 및 전략에 맞추어 진행되기 위해서는 프로젝트를 수행하는 과정에서 주기적인 프로젝트 평가가 필요하다. 본 논문이 제안한 스마트시티 프로젝트 평가체계는 스마트시티의 기획, 설계, 구축 및 운영의 전 단계에서 발생하는 프로젝트에 대해서 반드시 고려해야 할 다양한 요소를 반영하여 종합적이고 객관적인 지표를 제공하도록 설계되었다. 평가체계로부터 도출된 지표는 의사결정자가 스마트시티 프로젝트 개발 방향을 결정하는데 사용될 수 있다. 또한 프로젝트의 종료 이전에도 프로젝트의 성과를 중간 평가하고 이로부터 얻은 피드백을 반영할 수 있도록 설계하였다. 본 연구가 제안한 스마트시티 프로젝트 평가체계의 적용 방법을 소개하기 위해 인천경제자유구역청(IFEZ)의 스마트시티 프로젝트 사례에 개발된 평가체계를 적용하였다. 또한 평가결과를 바탕으로 스마트시티 프로젝트 항목별 개선효과를 극대화할 수 있는 항목을 제시함으로써 스마트시티 프로젝트 추진 방향을 제시하였다. 여러 가지 프로젝트들이 복합적으로 진행되는 스마트시티 프로젝트의 특성을 반영한 스마트시티 프로젝트 평가체계를 활용함으로써 스마트시티 프로젝트의 종합적인 계획 및 관리가 가능할 것이며, 프로젝트의 우선적인 개선 요소를 파악하는 데 본 연구가 참고가 될 것이다.

• 한국콘텐츠학회논문지
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• 제17권6호
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• pp.470-478
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• 2017

본 연구는 현존 스마트시티의 목표와 개념을 명확히 규명하며, 스마트시티와 관련된 주요 기술적 관점을 구체적으로 탐색하는 데에 목적을 두었다. 본 연구에서는 선행연구의 포괄적인 탐색과 분석을 통해 스마트시티와 관련된 기존의 모호한 논의를 구체화함으로써 향후 연구의 기반을 제공하고자 노력하였다. 특히 본 연구는 50대 중반에서 60대 초반의 실버인구를 연구의 대상으로 삼아, 이들을 핵심 표적으로 하는 스마트시티의 바람직한 모델을 이론적인 차원에서 제안하였다. 본 연구에서는 실버인구를 위한 미래지향적 스마트시티의 주제로서 의료보건관리, 은퇴 이후의 고용창출, 지역기반 관리체계, 친환경 사회기반시설 등 네 가지 사항을 제시하였다. 특히 실버인구의 복지후생은 미래지향적 스마트시티의 핵심적 사항이며, 친환경적인 고려가 우선적으로 이루어져야 함이 강조되었다.

• The Journal of Asian Finance, Economics and Business
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• 제7권10호
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• pp.323-328
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• 2020

This study aims to analyze the changes in purchasing decisions in conducting transactions using cash and digital payment systems. Cash payment systems are very different from digital payments because they no longer use banks as intermediaries for transactions. The scope of this study is to determine the differences that take place with purchasing decisions using digital payment systems with OVO Indonesia smart applications. By using the paired T-test sample test method and testing the regression class assumptions, it is expected we will document the comparison between cash and digital payment systems as regards changes in consumers' buying interest behavior towards goods. Data is obtained by purposive sampling using special characteristics for smart application users. The results show that digital payments are developing very quickly, but cash payments still dominate due to the unavailability of complete facilities and infrastructure to support digital payment systems other than in cities. This study illustrates that digital payments have not been able to completely change consumer buying behavior in large numbers, but the main finding in this study is an increase in the percentage of digital payment usage to the online market, due to the many conveniences provided in OVO smart applications.

• 한국BIM학회 논문집
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• 제8권3호
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• pp.12-19
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• 2018

The research aims to find implications of machine learning and urban big data as a way to construct the flexible transportation network system of smart city by responding the urban context changes. This research deals with a problem that existing a bus headway model is difficult to respond urban situations in real-time. Therefore, utilizing the urban big data and machine learning prototyping tool in weathers, traffics, and bus statues, this research presents a flexible headway model to predict bus delay and analyze the result. The prototyping model is composed by real-time data of buses. The data is gathered through public data portals and real time Application Program Interface (API) by the government. These data are fundamental resources to organize interval pattern models of bus operations as traffic environment factors (road speeds, station conditions, weathers, and bus information of operating in real-time). The prototyping model is implemented by the machine learning tool (RapidMiner Studio) and conducted several tests for bus delays prediction according to specific circumstances. As a result, possibilities of transportation system are discussed for promoting the urban efficiency and the citizens' convenience by responding to urban conditions.

• Journal of Information Processing Systems
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• 제15권2호
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• pp.440-448
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• 2019

The Internet of Things (IoT) is one of the main enablers for situation awareness needed in accomplishing smart cities. IoT devices, especially for monitoring purposes, have stringent timing requirements which may not be met by cloud computing. This deficiency of cloud computing can be overcome by fog computing for which fog nodes are placed close to IoT devices. Because of low capabilities of fog nodes compared to cloud data centers, fog nodes may not be deployed with all the services required by IoT devices. Thus, in this article, we focus on the issue of fog service placement and present the recent research trends in this issue. Most of the literature on fog service placement deals with determining an appropriate fog node satisfying the various requirements like delay from the perspective of one or more service requests. In this article, we aim to effectively place fog services in accordance with the pre-obtained service demands, which may have been collected during the prior time interval, instead of on-demand service placement for one or more service requests. The concept of the logical fog network is newly presented for the sake of the scalability of fog service placement in a large-scale smart city. The logical fog network is formed in a tree topology rooted at the cloud data center. Based on the logical fog network, a service placement approach is proposed so that services can be placed on fog nodes in a resource-effective way.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권9호
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• pp.3365-3383
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• 2021

The rapid growth of data has successfully promoted the development of modern information and communication technologies, which are used to process data generated by public urban departments and citizens in modern cities. In specific application areas where the ciphertext of messages generated by different users' needs to be transmitted, the concept of broadcast encryption is important. It can not only improve the transmission efficiency but also reduce the cost. However, the existing schemes cannot entirely ensure the privacy of receivers and dynamically adjust the user authorization. To mitigate these deficiencies, we propose an efficient, secure identity-based broadcast encryption scheme that achieves direct revocation and receiver anonymity, along with the analysis of smart grid solutions. Moreover, we constructed a security model to ensure wireless data transmission under cloud computing and internet of things integrated devices. The achieved results reveal that the proposed scheme is semantically secure in the random oracle model. The performance of the proposed scheme is evaluated through theoretical analysis and numerical experiments.

• ETRI Journal
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• 제44권2호
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• pp.220-231
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• 2022

Building smart transportation services in urban cities has become a worldwide problem owing to the rapidly increasing global population and the development of Internet-of-Things applications. Traffic congestion and environmental concerns can be alleviated by sharing mobility, which reduces the number of vehicles on the road network. The taxi-parcel sharing problem has been considered as an efficient planning model for people and goods flows. In this paper, we enhance the functionality of a current people-parcel taxi sharing model. The adapted model analyzes the historical request data and predicts the current service demands. We then propose two novel online routing algorithms that construct optimal routes in real-time. The objectives are to maximize (as far as possible) both the parcel delivery requests and ride requests while minimizing the idle time and travel distance of the taxis. The proposed online routing algorithms are evaluated on instances adapted from real Cabspotting datasets. After implementing our routing algorithms, the total idle travel distance per day was 9.64% to 12.76% lower than that of the existing taxi-parcel sharing method. Our online routing algorithms can be incorporated into an efficient smart shared taxi system.

• Journal of Smart Tourism
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• 제2권1호
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• pp.21-31
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• 2022

This review paper aims at providing a systematic analysis of articles published in various journals and related to the uses and business applications of big data. The goal is to provide a holistic picture of the place of big data in the tourism industry. The reviewed articles have been selected for the period 2013-2020 and have been classified into 8 broad categories namely business strategy and firm performance; banking and finance; healthcare; hospitality; networks and telecommunications; urbanism and infrastructures; law and legal regulations; and government. While the categories are reflective of components of tourism industries and infrastructures, the meta-analysis is organized around 3 broad themes: preferred research contexts, conceptual developments, and methods used to research big data business applications. Main findings revealed that firm performance and healthcare remain popular contexts of research in the big data realm, but also demonstrated a prominence of qualitative methods over mixed and quantitative methods for the period 2013-2020. Scholars have also investigated topics involving the notions of competitive advantage, supply chain management, smart cities, but also ethics and privacy issues as related to the use of big data.