• Journal of Convergence for Information Technology
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• v.7 no.5
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• pp.177-182
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• 2017

As major ICT technologies such as IoT, cloud computing, and Big Data are being applied to manufacturing, smart factories are beginning to be built. The key of smart factory implementation is the ability to acquire and analyze data of the factory. Therefore, the need for a big data analysis platform is increasing. The purpose of this study is to construct a platform for big data analysis of manufacturing process and propose integrated method for analysis. The proposed platform is a RHadoop-based structure that integrates analysis tool R and Hadoop to distribute a large amount of datasets. It can store and analyze big data collected in the unit process and factory in the automation system directly in HBase, and it has overcome the limitations of RDB - based analysis. Such a platform should be developed in consideration of the unit process suitability for smart factories, and it is expected to be a guide to building IoT platforms for SMEs that intend to introduce smart factories into the manufacturing process.

• Information and Communications Magazine
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• v.30 no.1
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• pp.24-32
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• 2012

우리는 지금 스마트 사회에 살아가고 있다. 언제 어디서든 스마트 디바이스를 통해 기존에 PC에서 하던 작업들을 손쉽게 하고 있다. 한편 스마트폰의 확산으로 이용자 수가 급증하고 있는 소셜네트워크 서비스(SNS)는 이용자들이 자신의 일상적인 이야기를 사이버공간에 게시함으로 인해 개인의 사생활 정보들이 노출되고, 그러한 정보들이 범죄에 악용되는 사례들이 눈에 띄게 증가하고 있다. 또한 SNS를 이용한 악성코드의 유포 및 빠른 전파 등도 새로운 보안위협으로 나타나고 있다. 그 밖에 스마트 기기를 대상으로 한 해킹 및 악성코드 감염 등 위협이 증가하고 있는 형편이다. 본고에서는 스마트 사회의 주요 보안위협을 살펴보고 미국, 유럽, 일본, 호주 등 선진국의 관련 정책 동향과 국내 정책과 실태를 분석하여 새로운 정보보호 정책 수립 방향을 제언하고자 한다. 스마트 사회 위험 요소로 가장 보편적으로 사용되고 있는 스마트폰과 스마트폰을 통해 이용되고 있는 소셜네트워크 서비스, 클라우드 서비스의 보안위협을 제기하고 최근 글로벌 이슈로 떠오르고 있는 빅 데이터 환경의 보안위협을 분석하였다. 스마트 사회의 위협을 대비하고 있는 주요국 정책을 살펴보면, 미국의 경우 사회적 합의를 바탕으로한 감시와 통제를 강화하는 정책을 추진 중에 있으며 유럽의 5개국 EU5(영국, 독일, 프랑스, 스페인, 이탈리아)는 스마트폰 위협을 중심으로 공동 대응 방안을 마련하고 있다. 일본은 스마트 워크중심의 보안대책을 강구하고 있으며 호주는 스마트 사회 보안위협에 대한 국민의 인식제고에 주력하고 있다. 국내의 경우도 스마트 사회의 보안위협에 선제적 대응을 위하여 "스마트 모바일 시큐리티 종합계획"을 수립하여 추진중에 있다. 하지만 보안 실태를 보면 스마트 사회 보안위협에 대한 이용자들의 우려는 높은 반면 기업의 보안 대책 마련에 대한 투자는 여전히 미흡한 상황이다. 향후 우리 사회가 디바이스간 융합을 넘어 모든 사물이 연결되는 초(超)연결(Hyper-Connectivity) 시대로 진화되어 가면 편리성이 증대되는 만큼 더 많은 위협에 우리의 일상이 노출되는 문제가 발생하게 될 것이다. 안전한 미래 사회로 진입하기 위해서는 보다 체계적이고 종합적인 정보보호 정책마련이 필요하다. 본고에서는 이를 위한 정책수립의 방향을 제언했다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.10a
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• pp.540-542
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• 2014

The Universal Plug and Play (UPnP) specification permits networked devices to discover each other and to provide diverse services in the home network environment. Recently, new paradigms such as mobile connected computing, cloud-based service delivery, smart device content sharing, and Internet of Things (IoT) have emerged, but the home network based UPnP shows functional limitations in supporting such paradigms. To support them, the UPnP Forum has recently extended the capabilities of the existing UPnP, calling it UPnP+. In this paper, the UPnP Device Architecture V2.0 (UDA 2.0), which forms the basis of UPnP+, is presented. We present how UDA 2.0 enables the expansion of the home network to wide-area networks and non-IP device domains.

• Journal of Digital Convergence
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• v.19 no.8
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• pp.241-247
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• 2021

As a way to solve the side effects of urban development, a smart city with information and communication technology converges in the city is being built. For this, a smart city platform should support the development and integration of smart city services. Therefore, the underlying technology and the functional and non-functional requirements that the smart platform must support were analyzed. As a result of this, we classified the Internet of Things, cloud computing, big data and cyber-physical systems into four categories as the underlying technologies supported by the smart city platform, and derived the functional and non-functional requirements that can be implemented and the reference model of the smart city platform. The reference model of the smart city platform is used for decision-making on investment in infrastructure technology and the development scope of services according to functional or non-functional requirements to solve specific city problems for city managers. It provides platform developers with guidelines to identify and determine the functional and non-functional requirements and implementation technologies of software platforms for building smart cities.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.12
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• pp.1688-1696
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• 2020

The paradigm of Internet-of-things(IoT) systems is changing from a cloud-based system to an edge-based system to solve delays caused by network congestion, server overload and security issues due to data transmission. However, edge-based IoT systems have fatal weaknesses such as lack of performance and flexibility due to various limitations. To improve performance, application-specific hardware can be implemented in the edge device, but performance cannot be improved except for specific applications due to a fixed function. This paper introduces a edge-centric metamorphic IoT(mIoT) platform that can use a variety of hardware through on-demand partial reconfiguration despite the limited hardware resources of the edge device, so we can increase the performance and flexibility of the edge device. According to the experimental results, the edge-centric mIoT platform that executes the reconfiguration algorithm at the edge was able to reduce the number of server accesses by up to 82.2% compared to previous studies in which the reconfiguration algorithm was executed on the server.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.3
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• pp.368-376
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• 2021

With the recent development of deep learning technology, autonomous things technology is attracting attention, and DNNs are widely used in embedded systems such as drones and autonomous vehicles. Embedded systems that can perform large-scale operations and process multiple DNNs for high recognition accuracy without relying on the cloud are being released. DNNs with various levels of priority exist within these systems. DNNs related to the safety-critical applications of autonomous vehicles have the highest priority, and they must be handled first. In this paper, we propose a priority-based scheduling framework for DNNs when multiple DNNs are executed simultaneously. Even if a low-priority DNN is being executed first, a high-priority DNN can preempt it, guaranteeing the fast response characteristics of safety-critical applications of autonomous vehicles. As a result of checking through extensive experiments, the performance improved by up to 76.6% in the actual commercial board.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.4
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• pp.133-139
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• 2022

Recently, livestock farms in Korea are introducing data-based technologies to improve productivity, such as livestock environment and breeding management, safe livestock production, and animal welfare. In addition, the government has been conducting a smart livestock distribution project since 2017 through the modernization of ICT-based livestock facilities in order to improve the productivity of livestock products and improve the livestock environment as a policy. However, the current smart livestock house has limitations in connection, diversity, and integration between monitoring and control. Therefore, in order to intelligently systemize all processes of livestock with intelligent algorithms and remote control in order to link and integrate various monitoring and control, the Internet of Things, big data, artificial intelligence, cloud computing, and mobile It is necessary to develop a smart livestock system. In this study, domestic and foreign research trends related to smart livestock based on intelligent information technology were introduced and the limitations of domestic application of advanced technologies were analyzed. Finally, future intelligent information technology applicable to the livestock field was examined.

• KIPS Transactions on Computer and Communication Systems
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• v.12 no.3
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• pp.93-102
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• 2023

Data processing through the cloud causes many problems, such as latency and increased communication costs in the communication process. Therefore, many researchers study edge computing in the IoT, and autonomous driving is a representative application. In indoor self-driving, unlike outdoor, GPS and traffic information cannot be used, so the surrounding environment must be recognized using sensors. An efficient autonomous driving system is required because it is a mobile environment with resource constraints. This paper proposes a machine-learning method using neural networks for autonomous driving in an indoor environment. The neural network model predicts the most appropriate driving command for the current location based on the distance data measured by the LiDAR sensor. We designed six learning models to evaluate according to the number of input data of the proposed neural networks. In addition, we made an autonomous vehicle based on Raspberry Pi for driving and learning and an indoor driving track produced for collecting data and evaluation. Finally, we compared six neural network models in terms of accuracy, response time, and battery consumption, and the effect of the number of input data on performance was confirmed.

• Design Convergence Study
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• v.15 no.2
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• pp.237-250
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• 2016

Along with rapid development, progress of the network technology and digital information technology, human are stepping into the intelligent society of internet. Thereby the quality of living environment and working environment are keep improving. Under the big background of internet era, the timeliness and convenience of smart home system has been improved greatly. While lots of smart products have gradually penetrated into people's daily life. The household appliances are among most popular ones. This paper is intended to compare smart features of household living products among most representative brands in China, Japan and South Korea. The smart features include self-learning, self-adapting, self-coordinating, self-diagnosing, self-inferring, self-organizing, and self adjusting. As result, most smart features of these products showed great similarity. While some features were dominated according to countries such as remote control feature in Korea, energy saving feature in Japan, and one button operation feature in China.

• Journal of the Korea Society of Computer and Information
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• v.29 no.5
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• pp.93-100
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• 2024

With the advent of the Fourth Industrial Revolution, cutting-edge technologies such as artificial intelligence, big data, the Internet of Things, and cloud computing are driving innovation across industries. These technologies are generating massive amounts of data that many companies are leveraging. However, there is a notable reluctance among users to share sensitive information due to the privacy risks associated with collecting personal data. This is particularly evident in the healthcare sector, where the collection of sensitive information such as patients' medical conditions poses significant challenges, with privacy concerns hindering data collection and analysis. This research presents a novel technique for collecting and analyzing medical data that not only preserves privacy, but also effectively extracts statistical information. This method goes beyond basic data collection by incorporating a strategy to efficiently mine statistical data while maintaining privacy. Performance evaluations using real-world data have shown that the propose technique outperforms existing methods in extracting meaningful statistical insights.