• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.7
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• pp.699-707
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• 2020

With the development of deep learning technology, voice processing-related technology is applied to various areas, such as STT (Speech To Text), TTS (Text To Speech), ChatBOT, and intelligent personal assistant. In particular, the STT is a voice-based, relevant service that changes human languages to text, so it can be applied to various IT related services. Recently, many places, such as general private enterprises and public institutions, are attempting to introduce the relevant technology. On the other hand, in contrast to the general IT solution that can be evaluated quantitatively, the standard and methods of evaluating the accuracy of the STT engine are ambiguous, and they do not consider the characteristics of the Korean language. Therefore, it is difficult to apply the quantitative evaluation standard. This study aims to provide a guide to an evaluation of the STT engine conversion performance based on the characteristics of the Korean language, so that engine manufacturers can perform the STT conversion based on the characteristics of the Korean language, while the market could perform a more accurate evaluation. In the experiment, a 35% more accurate evaluation could be performed compared to the existing methods.

• Proceedings of the Korea Water Resources Association Conference
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• 2017.05a
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• pp.264-264
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• 2017

국외의 상수도 원격검침 시스템 내 데이터 전송방식은 도시 규모, 계량기의 밀도, 전력공급 여부 및 통신망의 설치 여부 등을 종합적으로 고려하여 결정되었다. 대부분의 스마트워터미터 제조업체들은 계량기의 부호기가 공급하는 판독 내용(데이터)을 전송할 검침단말기와 근거리 통신망(neighborhood area network)을 연계하여 개발 및 판매하였으며, 자체 소유 통신 프로토콜을 사용하여 라디오 주파수(RF) 통신 기술을 사용하고 있다. 광역통신망(wide area network)의 경우, 노드(말단의 계량기 및 센서)들과 이에 연결된 통신망 들을 포함한 네트웍의 배열이나 구성이 스타(star), 메쉬(mesh), 버스(bus), 나무(tree) 등의 형태로 통신망이 구성되어 있으나, 스타와 메쉬형 통신망 구성형태가 가장 널리 활용되는 것으로 조사되었다. 시스템 통합운영관리 업체들인 IBM, Oracle, Itron 등은 용수 인프라 관리 또는 통합네트워크 솔루션 등의 통합 물관리 시스템(integrated water management system)을 개발하여 현장적용을 하고 있으며, 원격검침 시스템을 통해 고객들의 현재 소비량과 과거 누적 소비량, 누수 감지 서비스 및 실시간 요금 고지 등을 실시간으로 웹 포털과 앱을 통해 제공하고 있다. 또한, 일부 제조업체들은 도시 용수공급/소비 관리자가 주민의 용수사용량을 모니터링하여 일평균 용수사용량 및 사용 경향을 파악하고, 누수를 검지하여 복구 및 용수 사용 지속가능성 지수를 제시하고, 실시간으로 주민의 용수사용량 관련 데이터를 모니터링하여 용수공급의 최적화를 위한 의사결정지원 서비스를 용수공급자에게 제공하고 있다. 최근에는 인공지능을 활용해 가정용수의 용도별(세탁용수, 화장실용수, 샤워용수, 식기세척용수 등) 사용량 곡선을 패터닝하여 profiling 기법을 도입해, 스마트워터미터에서 용수사용량이 통합되어 검지될 시 용수사용량의 세부 용도별 re-profiling 기법을 도입하여 가정용수내 과소비되는 지점을 도출 후 절감을 유도하는 기술이 개발 중이다. 또한, 미래 용수 사용량 예측을 위해 다양한 시계열 자료를 분석하는 선형 종속 모형(자기회귀모형, 자기회귀이동평균모형, 자기회귀적분이동평균모형 등)과 비선형 종속 모형(Fuzzy Logic, Neural Network, Genetic Algorithm 등)을 활용한 예측기능이 구축되어 상호 비교하여 최적의 용수사용량 예측 도구를 제공되고 있다.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.14 no.2
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• pp.115-121
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• 2021

This paper used big data and artificial intelligence technology to predict the rapidly increasing internet traffic. There have been various studies on traffic prediction in the past, but they have not been able to reflect the increasing factors that induce huge Internet traffic such as smartphones and streaming in recent years. In addition, event-like factors such as the release of large-capacity popular games or the provision of new contents by OTT (Over the Top) operators are more difficult to predict in advance. Due to these characteristics, it was impossible for an ISP (Internet Service Provider) to reflect real-time service quality management or traffic forecasts in the network business environment with the existing method. Therefore, in this study, in order to solve this problem, an Internet traffic collection system was constructed that searches, discriminates and collects traffic data in real time, separate from the existing NMS. Through this, the flexibility and elasticity to automatically register the data of the collection target are secured, and real-time network quality monitoring is possible. In addition, a large amount of traffic data collected from the system was analyzed by machine learning (AI) to predict future traffic of OTT operators. Through this, more scientific and systematic prediction was possible, and in addition, it was possible to optimize the interworking between ISP operators and to secure the quality of large-scale OTT services.

• 재활복지
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• v.22 no.3
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• pp.23-39
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• 2018

The fourth industrial revolution and technological innovation will make the job factor of people with disabilities complicated and difficult. Thus, this study analyzed the technical factors influencing the job structure and tried to find a way to develop the job of the people with disabilities in response to the 4th Industrial Revolution by changing the labor market and changing the trend of the employment by industry. The methods for this study are literature research and FGI. First, technological factors affecting the job structure of the Fourth Industrial Revolution are artificial intelligence, Internet and networking of things, 3D printing, big data, Second, technological innovation due to the industrial revolution was a major factor in the job structure. As the industrial revolution and technological innovation progressed, the job structure shifted rapidly from the manufacturing industry to the service industry, Third, as the measures of the 4th Industrial Revolution and the change of the job structure, it is necessary to make preemptive investment for the development of competency to cope with technological innovation, Finally, in order to respond to the Fourth Industrial Revolution and the rapidly changing technological innovation, the basic data of people with disabilities should be able to be big data.

• Journal of Industrial Convergence
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• v.20 no.3
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• pp.33-40
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• 2022

Recently, IoT-linked services have been used in various environments, and IoT and artificial intelligence technologies are being fused. However, since technologies that process IoT data stably are not fully supported, research is needed for this. In this paper, we propose a processing technique that can optimize IoT data after generating embedded vectors based on machine learning for IoT data. In the proposed technique, for processing efficiency, embedded vectorization is performed based on QR such as index of IoT data, collection location (binary values of X and Y axis coordinates), group index, type, and type. In addition, data generated by various IoT devices are integrated and managed so that load balancing can be performed in the IoT data collection process to asymmetrically link IoT data. The proposed technique processes IoT data to be orthogonalized based on hash so that IoT data can be asymmetrically grouped. In addition, interference between IoT data may be minimized because it is periodically generated and grouped according to IoT data types and characteristics. Future research plans to compare and evaluate proposed techniques in various environments that provide IoT services.

• Journal of Service Research and Studies
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• v.13 no.3
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• pp.127-146
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• 2023

Recently, digital advertising has shifted towards delivering messages through short ads of less than 15 seconds, and on social media, ads need to convey the message within 5 seconds before consumers skip them. Although the length of advertisements has decreased, advancements in artificial intelligence algorithms and big data analysis have made it possible to deliver personalized messages that cater to consumers' interests. In this changing landscape, the importance of delivering tailored messages through short and efficient ads is increasing. In this study, we examined the effects of message framing as part of effective message delivery. Specifically, we examined the differences in the effects of two framings, "health" and "environment," for vegan products. The growing consumer interest in health and the environment has elevated the interest in vegan products, and the vegan market is expanding rapidly. Consumers purchase vegan products not only for personal health benefits but also due to their ethical responsibility towards the environment, which can be considered ethical consumption. Previous research has not shown the differences in the effects between health and environment message framings, and the research has been limited to vegan food products. This study investigates the differences in the effects of health and environment message framings using a dish soap product category. By identifying which advertising messages, either health or environment, are more effective in promoting vegan products, this study provides insights for companies to enhance their message framing strategies effectively.

• Journal of Service Research and Studies
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• v.13 no.1
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• pp.127-143
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• 2023

Currently, the domestic traditional market has not escaped the swamp of stagnation that began in the early 2000s despite various projects promoted by many related players such as the central government and local governments. In order to overcome the crisis faced by the traditional market, various R&Ds have recently been conducted on how to build a smart traditional market that combines information and communication technologies such as big data analysis, artificial intelligence, and the Internet of Things. This study analyzes various previous studies, users of traditional markets, and application cases of ICT technology in foreign traditional markets since 2012 and proposes a model to build a smart traditional market using ICT technology based on the analysis. The model proposed in this study includes building a traditional market metaverse that can interact with visitors, certifying visits to traditional markets through digital signage with NFC technology, improving accuracy of fire detection functions using IoT and AI technology, developing smartphone apps for market launch information and event notification, and an e-commerce system. If a smart traditional market platform is implemented and operated based on the smart traditional market platform model presented in this study, it will not only draw interest in the traditional market to MZ generation and foreigners, but also contribute to revitalizing the traditional market in the future.

• The Journal of Bigdata
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• v.6 no.2
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• pp.17-28
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• 2021

Current development of technologies related to 4^th industrial revolution and the pandemic of COVID-19 lead the rapid expansion of e-marketplace. The level of competition among several companies gets increased by introducing different strategies. To cope with the current change in the market and satisfy the customers who request the better delivery service, the new concept, fulfillment, has been introduced. It makes the leadtime of process from order picking to delivery reduced and the efficiency improved. Still, the efficiency of operation in fulfillment centers constrains the service level of the entire delivery process. In order to solve this problem, several different approaches for demand forecasting and coordinating supplies using Bigdata, IoT and AI, which there exists the trivial limitations. Because it requires the most lead time for operation and leads the inefficiency the process from picking to packing the ordered items, the logistics service providers should try to automate this procedure. In this research, it has been proposed to develop the efficient plans to automate the process to move the ordered items from the location where it stores to stage for packing using AGV and AMR. The efficiency of automated devices depends on the number of items and total number of devices based on the demand. Therefore, the result of simulation based on several different scenarios has been analyzed. From the result of simulation, it is possible to identify the several factors which should be concerned for introducing the automated devices in the fulfillment centers. Also, it can be referred to make the optimal decisions based on the efficiency metrics.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.33 no.6
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• pp.975-987
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• 2023

With the advancement of Artificial Intelligence (AI) technologies, the provision of data-driven AI services that enable automation and intelligence is increasing across industries, raising concerns about the AI security risks that may arise from the use of AI. Accordingly, Foreign countries recognize the need and importance of AI regulation and are focusing on developing related policies and regulations. This movement is also happening in Korea, and AI regulations have not been specified, so it is necessary to compare and analyze existing policy proposals or guidelines to derive common factors and identify complementary points, and discuss the direction of domestic AI regulation. In this paper, we investigate AI security risks that may arise in the AI life cycle and derive six points to be considered in establishing domestic AI regulations through analysis of each risk. Based on this, we analyze AI policy proposals and recommendations in Korea and validate additional issues. In addition, based on a review of the main content of AI laws in the US and EU and the analysis of this paper, we propose measures to improve domestic guidelines and policies in the field of AI.

• Smart Media Journal
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• v.13 no.6
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• pp.9-15
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• 2024

In recent trends, there has been an increase in 'Qshing' attacks, a hybrid form of phishing that exploits fake QR (Quick Response) codes impersonating government agencies to steal personal and financial information. Particularly, this attack method is characterized by its stealthiness, as victims can be redirected to phishing pages or led to download malicious software simply by scanning a QR code, making it difficult for them to realize they have been targeted. In this paper, we have developed a classification technique utilizing machine learning algorithms to identify the maliciousness of URLs embedded in QR codes, and we have explored ways to integrate this with existing QR code readers. To this end, we constructed a dataset from 128,587 malicious URLs and 428,102 benign URLs, extracting 35 different features such as protocol and parameters, and used AutoML to identify the optimal algorithm and hyperparameters, achieving an accuracy of approximately 87.37%. Following this, we designed the integration of the trained classification model with existing QR code readers to implement a service capable of countering Qshing attacks. In conclusion, our findings confirm that deriving an optimized algorithm for classifying malicious URLs in QR codes and integrating it with existing QR code readers presents a viable solution to combat Qshing attacks.