• Journal of Convergence for Information Technology
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• v.11 no.2
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• pp.16-24
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• 2021

This paper introduces a smart aging service that helps the elderly lead a happy old age by actively utilizing IoT and AI technologies for the elderly who are increasing rapidly as they enter the aging society. In particular, we propose a future-oriented, age-friendly well-being support system that breaks away from the existing welfare concept to solve the aging problem but leads to a paradigm shift toward building a vibrant aging society by protecting from emergency and satisfying emotions. By introducing IoT and AI, it judges the life situation and emotional state from the living information of the elderly can respond to emergencies and suggest meetings as a change of mood and give an emotional comfort. Since the proposed system uses artificial intelligence techniques to determine the degree of depression when inputting information such as pulse-rate, dangerous word usage, and external communication, I think it showed the feasibility of the new concept of wellbeing support system that is totally different from conventional wellbeing concept of health-care.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.6
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• pp.61-73
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• 2020

Real-time location-sensing technology using location information collected from IoT devices is being applied for safety management purposes in many industries, such as ports. On the other hand, positional error is always present owing to the characteristics of GPS. Therefore, accident-risk detection algorithms must consider positional error. This paper proposes an methodology of calibration for falling object accident-risk-zone approach detection algorithm considering GPS errors. A probability density function was estimated, with positional error data collected from IoT devices as a probability variable. As a result of the verification, the algorithm showed a detection accuracy of 93% and 77%. Overall, the analysis results derived according to the GPS error level will be an important criterion for upgrading algorithms and real-time risk managements in the future.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.4
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• pp.537-542
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• 2021

Smart TVs provide a variety of services and information compared to existing TVs based on the Internet. In order to provide more personalized services or information, it is necessary to analyze users' viewing patterns and provide customized services or information based on them. The proposed system receives the user's TV viewing pattern, analyzes it, and recommends a TV program or movie as customized information to the user. For this, the system was constructed with a preprocessor and a deep learning model. The preprocessor refines the name of the TV program watched by the user, the date the TV program was watched, and the watched time. Then, the multi-attribute LSTM model trains the refined data and performs prediction.The proposed system is a system that provides customized information to users, and is believed to be a leading technology in digital convergence that combines existing IoT technology and deep learning technology.

• International Journal of Computer Science & Network Security
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• v.21 no.6
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• pp.107-118
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• 2021

The deployment of 5G is in full swing, with a significant yearly growth in the data traffic expected to reach 26% by the year and data consumption to reach 122 EB per month by 2022 [10]. In parallel, the idea of smart cities has been implemented by various governments and private organizations. One of the main objectives of 5G deployment is to help develop and realize smart cities. 5G can support the enhanced data delivery requirements and the mass connection requirements of a smart city environment. However, for specific high-demanding applications like tactile Internet, transportation, and augmented reality, the cloud-based 5G infrastructure cannot deliver the required quality of services. We suggest using multi-access edge computing (MEC) technology for smart cities' environments to provide the necessary support. In cloud computing, the dependency on a central server for computation and storage adds extra cost in terms of higher latency. We present a few scenarios to demonstrate how the MEC, with its distributed architecture and closer proximity to the end nodes can significantly improve the quality of services by reducing the latency. This paper has surveyed the existing work in MEC for 5G and highlights various challenges and opportunities. Moreover, we propose a unique framework based on the use of MEC for 5G in a smart city environment. This framework works at multiple levels, where each level has its own defined functionalities. The proposed framework uses the MEC and introduces edge-sub levels to keep the computing infrastructure much closer to the end nodes.

• International Journal of Computer Science & Network Security
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• v.21 no.1
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• pp.137-142
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• 2021

The Internet of Things (IoT) paradigm is at the forefront of present and future research activities. The huge amount of sensing data from IoT devices needing to be processed is increasing dramatically in volume, variety, and velocity. In response, cloud computing was involved in handling the challenges of collecting, storing, and processing jobs. The fog computing technology is a model that is used to support cloud computing by implementing pre-processing jobs close to the end-user for realizing low latency, less power consumption in the cloud side, and high scalability. However, it may be that some resources in fog computing networks are not suitable for some kind of jobs, or the number of requests increases outside capacity. So, it is more efficient to decrease sending jobs to the cloud. Hence some other fog resources are idle, and it is better to be federated rather than forwarding them to the cloud server. Obviously, this issue affects the performance of the fog environment when dealing with big data applications or applications that are sensitive to time processing. This research aims to build a fog topology job scheduling (FTJS) to schedule the incoming jobs which are generated from the IoT devices and discover all available fog nodes with their capabilities. Also, the fog topology job placement algorithm is introduced to deploy jobs into appropriate resources in the network effectively. Finally, by comparing our result with the state-of-art first come first serve (FCFS) scheduling technique, the overall execution time is reduced significantly by approximately 20%, the energy consumption in the cloud side is reduced by 18%.

• KIPS Transactions on Computer and Communication Systems
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• v.9 no.12
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• pp.315-320
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• 2020

Identity authentication is an important technology that has long been used in society to identify individuals and provide appropriate services. With the development of the Internet infrastructure, many areas have expanded into online areas, and identity authentication technologies have also expanded online. However, there is still a limit to identity authentication technology that relies entirely on trusted third parties like the government. A centralized identity management system makes the identification process between agencies with different identity management systems very complex, resulting in a waste of money and time for users. In particular, the limits of the centralized identity management system were clearly revealed in the face mask shortage in the 2020 COVID-19 crisis. A Decentralized Identity (DID) is a way for users to manage their identity on their own, and recently, a number of DID platform based on blockchain technology have been proposed. In this paper, we analyze the limitations of the existing centralized identity management system and propose a DID system that can be utilized in future national emergency situations such as COVID-19.

• The Journal of Korean Medicine Ophthalmology and Otolaryngology and Dermatology
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• v.34 no.1
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• pp.13-28
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• 2021

Objectives : Strabismus is a disease that can be observed and treated directly from the outside. Therefore, it is very important in Korean medicine ophthalmology in accessibility to treatment. This study is designed to investigate the trends of strabismus-related studies published in Journal of Korean medicine. Methods : 5 Internet databases were selected to search for the study subject. The following 9 keywords were used; Strabismus, Heterophoria, Binocular vision, Visual acuity, Diplopia, Paralytic, Cover test, Oculomotor nerve paralysis, Abducens nerve paralysis. Through this process, a total of 45 studies were found and analyzed into 5 categories ; publication year, publication journal, number of author, type of article, analyzation of case report. Results : There were 2 review articles, 1 original article and 42 case reports. 5 studies(11.1%) were published in 2004 year. Journal of Korean Oriental Medical Ophthalmology & Otolaryngology & Dermatology were the most common with 40%. The authors were often 2 and 3 (each 22.2%). In the case report study, the treatment period was most often 1-30 days (35.7%). Conclusions : 42 studies were on paralytic strabismus and 1 study was on paralytic and non-paralytic strabismus. These results represent that the studies are concentrated in case reports about paralytic strabismus, but this seems to be an area to be improved in future research.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.30 no.6
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• pp.1067-1078
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• 2020

With the development of internet technology, a lot of content is produced, and the demand for it is increasing. Accordingly, the number of contents in circulation is increasing, while the number of distributing illegal copies that infringe on copyright is also increasing. The Korea Copyright Protection Agency operates a illegal content obstruction program based on substring matching, and it is difficult to accurately search because a large number of noises are inserted to bypass this. Recently, researches using natural language processing and AI deep learning technologies to remove noise and various blockchain technologies for copyright protection are being studied, but there are limitations. In this paper, noise is removed from data collected online, and keyword-based illegal copies are searched. In addition, the same heavy uploader is estimated through profiling analysis for heavy uploaders. In the future, it is expected that copyright damage will be minimized if the illegal copy search technology and blocking and response technology are combined based on the results of profiling analysis for heavy uploaders.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.1
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• pp.124-133
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• 2021

Smart factory is a future factory that collects, analyzes, and monitors various data in real time by attaching sensors to equipment in the factory. In a smart factory, it is very important to inquire and generate the status and history of equipment in real time, and the emergence of various smart devices enables this to be performed more efficiently. This paper proposes a multi device-based system that can create, search, and delete equipment status and history in real time. The proposed system uses the Android system and the smart glass system at the same time in consideration of the special environment of the factory. The smart glass system uses a QR code for equipment recognition and provides a more efficient work environment by using a voice recognition function. We designed a system structure for real time equipment monitoring based on multi devices, and we show practicality by implementing and Android system, a smart glass system, and a web application server.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.4
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• pp.481-488
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• 2020

In recent years, realistic contents technology such as virtual reality, augmented reality, and mixed reality has been spreading in travel and tourism industries, and hence there have been various smart tourism AR, VR contents developed. In the past, people mainly used books and Internet for travel, but the use of VR, AR and MR technologies will be used more for consumption of cultural leisure contents in the future. This study describes the Mixed Reality based Baekje Neungsa Cultural Heritage On-Site Guide System to accelerate smart tourism. In this study, the immersive mixed reality HMD was used to provide visitors with more intuitive and effective information about the historical, cultural and architectural values of Baekje Neungsa through virtual experiences. The cultural heritage on-site guide system module supports various Meta Data services and can be easily used for mixed reality content development by designating Meta Data scripts. This research can make contributions to the development of mixed reality based smart tourism contents.