• The Journal of Korean Institute of Communications and Information Sciences
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• v.42 no.4
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• pp.879-888
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• 2017

Recently, the Smart household appliances to provide Smart services have been actively spreaded by providing IoT(Internet of Things). Also, the appliances which Wi-Fi and Bluetooth can directly control are preferred. But until now, the most household appliances are based on IR(InfraRed) and the each procotols of them are different. In this paper, to solve these problems, we suggested the system to control both smart appliances and general appliances by using Smart phone. The system is "Wi-Fi to IR" gateway which receives the Wi-Fi signal to convert to IR signal and transmit it. Also, we made the remote control function in specific brands' appliances possible to most brands without limitation and tried to control not only one remote controller for one TV brand but also for all brand without limitation.

• The Journal of the Korea Contents Association
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• v.16 no.8
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• pp.517-528
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• 2016

This study attempted to explore and examine a new user experience (UX) research method for IoT products which are becoming widely used but lack practical user research. While user experience research has been traditionally opted for survey or observation methods, this paper utilized big data analysis method for user online reviews on an intelligent agent IoT product, Amazon's Echo. The results of topic modelling analysis extracted user experience elements such as features, conversational interaction, and updates. In addition, regression analysis showed that the topic of updates was the most influential determinant of user satisfaction. The main implication of this study is the new introduction of big data analysis method into the user experience research for the intelligent agent IoT products.

• The Journal of Society for e-Business Studies
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• v.22 no.3
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• pp.57-74
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• 2017

The Electronic Shelf Label (ESL) is an alternative to the paper price label attached to merchandise shelves and is attracting attention as a retail IoT infrastructure that will lead the innovation of offline retail outlets. In general, when introducing a substitute product, the company tends to consider the financial factors such as the efficiency of the investment cost compared to the existing product or the reduction of the operating cost. However, considering only financial factors in the decision-making process, it may not properly reflect the various values associated with corporate strategy and the requirements of stakeholders. In this study, 8 evaluation items (Investment Cost, Operating Cost, Quality Level, Customer Management, Job Efficiency, Maintenance, Functional Expandability, and Store Image) based on BSC's 4 perspectives (Financial, Customer, Internal Business Process, Learning & Growth), and using AHP (Analytic Hierarchy Process) to measure the priorities of evaluation items for domestic small supermarket employees. As a result of the research, priority was given in order of Customer, Learning & Growth, Internal Business Process, and Financial aspects among the evaluation items for adopting the price label, and the electronic price label was supported with higher importance than the paper price label. In contrast to the priorities of the financial aspects of most prior studies, the items of Learning & growth and customer perspectives have relatively high priorities. In particular, respondents classified by job group, The priorities of the 8 evaluation items were different among the groups. These results are expected to provide implications for both companies (retail outlets) and ESL providers (manufacturers and service providers) who are considering the introduction of ESL.

• Journal of Convergence for Information Technology
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• v.7 no.1
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• pp.55-60
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• 2017

In order to provide intelligent services without human intervention in the Internet of Things environment, it is necessary to analyze the big data generated by the IoT device and learn the normal pattern, and to predict the abnormal symptoms such as faulty or malfunction based on the learned normal pattern. The purpose of this study is to implement a machine learning model that can predict product failure by analyzing big data generated in various devices of product process. The machine learning model uses the big data analysis tool R because it needs to analyze based on existing data with a large volume. The data collected in the product process include the information about product faulty, so supervised learning model is used. As a result of the study, I classify the variables and variable conditions affecting the product failure, and proposed a prediction model for the product failure based on the decision tree. In addition, the predictive power of the model was significantly higher in the conformity and performance evaluation analysis of the model using the ROC curve.

• Journal of IKEEE
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• v.22 no.1
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• pp.156-161
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• 2018

Recently, as the population rapidly increases, food shortages and waste are emerging serious problem. In order to solve this problem, various countries and enterprises are trying research and product development such as a study of consumers' purchasing patterns of food and a development of smart refrigerator using IoT technology. However, the smart refrigerators which currently sold have high price issue and another waste due to malfunction and breakage by complicated configurations. In this paper, we proposed a low-cost smart refrigerator system based on IoT for solving the problem and efficient management of ingredients. The system recognizes and registers ingredients through QR code, image recognition, and speech recognition, and can provide various services of the smart refrigerator. In order to improve an accuracy of image recognition, we used a model using a deep learning algorithm and proved that it is possible to register ingredients accurately.

• The Journal of the Korea institute of electronic communication sciences
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• v.15 no.4
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• pp.759-764
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• 2020

As the paradigm of manufacturing and production is also changing in line with the fourth industrial revolution, the social demands and directions for Industry 4.0 cannot be reversed, and the scalability and universality of 3D printing technology are attracting attention. 3D printer is a technology developed for the purpose of reducing product development costs, and with the recent expiration of 3D printer technology patent, related technology has been revealed and various technologies applied are being researched and developed, and various singularities have been discovered and supplemented. Thus, to compensate for the inconvenience of the current output method, which requires direct offline adjustment of the machine in the use of 3D printers and 3D printing through direct input of modeling data, the design of the IoT system is proposed to perform real-time online output requests for multiple 3D printers, monitoring functions that can expect normal outputs, and online real-time remote management functions for multiple 3D printers.

• Journal of Internet Computing and Services
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• v.16 no.5
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• pp.93-98
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• 2015

IoT (Internet of Things) is recently burgeoning as business applications as well as ICT itself. Among the business applications of IoT, wearable devices are recognized as a leading area of customer devices. This research first identifies customer needs of activity trackers (fitness trackers), as one of representative wearable devices, and mapping the identified needs with the well-known marketing model of marketing mix (4 P's: Product, Price, Promotion, and Place). Survey was applied to university students for identifying current and potential needs for activity trackers. The needs were classified by 4 P's, and according to the results, different from other IT devices, activity trackers has more potential needs. Moreover, reliable distribution channels, offline and company owned shops were preferred, rather than online shopping mall by third parties. The results would provide some valuable implications to not only designers of activity trackers but also business management.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.10 no.5
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• pp.442-454
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• 2017

As the demand for meat products has steadily increased in Korea, so the livestock industry has full grown. However, the opening of import meat products is taking a toll on the local industry. Cost reduction on livestock feed, which comprises the majority of costs involved in the industry is urgent to gain a competitive edge. As Internet of Things (IoT) technologies are being applied across a multiple of industries, so are the cases of applied Smart Farm technology for efficient production. The following research aims to utilize IoT technologies to measure, in real time, the rate of depletion of feed and remaining amount and to propose an effective automated reorder & delivery system. First, a method of utilization of ultrasonic and temperature/humidity sensors to obtain corresponding data of remaining feed in the Feedbin is proposed. In addition, a method of sending the obtained data via on-the-farm gateway to Supply Chain Management (SCM) servers is proposed. Finally, utilization of the stored data to construct an automated reorder & delivery service system is proposed. It is in the researcher's intention to contribute to and enable the local livestock industry with the application of various IoT services.

• Journal of Internet of Things and Convergence
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• v.6 no.4
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• pp.21-26
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• 2020

An autonomous driving system is based on the deep learning system built by big data which are obtained by various IoT sensors. The miniaturization and high performance of the IoT sensors are needed for diverse devices including the autonomous driving system. Specially, the miniaturization of the sensors leads to compel the miniaturization of the fixer structures. In the viewpoint of the miniaturization, metallic structure is a best solution to attach the small IoT sensors to the main body. However, it is hard to manufacture the small metallic structure with a conventional machining process or manufacturing cost greatly increases. As one of solutions for the problems, in this work, metallic FDM (Fused depositon modeling) based on metallic filament was proposed and the FDM process was investigated to fabricate the small metallic structure. Final part was obtained by the post-process that consists of debinding and sintering. In this work, the relationship between infill rate and the density of the part after the post-process was investigated. The investigation of the relationship is based on the fact that the infill rate and the density obtained from the post-processing is not same. It can be said that this work is a fundamental research to obtain the higher density of the printed part.

• Journal of Digital Convergence
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• v.17 no.11
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• pp.195-200
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• 2019

The role of the Internet of Things in the Fourth Industrial Revolution is in the era of collecting data at the end and analyzing big data through technology to analyze the future or behavior. Therefore, due to the nature of the IoT, it is vulnerable to security and requires a lightweight security protocol. The spread of things Internet technology is changing our lives a lot. IT companies all over the world are already focusing on products and services based on things Internet, and they are going to the era of all things internet that can communicate not only with electronic devices but also with common objects. People, people, people and objects, things and things interact without limitation of time and space, collecting, analyzing and applying information. Life becomes more and more smart, but on the other hand, the possibility of leakage of personal information becomes greater. Therefore, this study proposed security threats that threaten the protection of personal information and countermeasures, and suggested countermeasures for building a secure IoT environment suitable for the Fourth Industrial Revolution.