• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.5
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• pp.17-22
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• 2022

In this paper, we design a lightweight embedded device that can support intelligent edge computing, and show that the device quickly detects an object in an image input from a camera device in real time. The proposed system can be applied to environments without pre-installed infrastructure, such as an intelligent video control system for industrial sites or military areas, or video security systems mounted on autonomous vehicles such as drones. The On-Device AI(Artificial intelligence) technology is increasingly required for the widespread application of intelligent vision recognition systems. Computing offloading from an image data acquisition device to a nearby edge device enables fast service with less network and system resources than AI services performed in the cloud. In addition, it is expected to be safely applied to various industries as it can reduce the attack surface vulnerable to various hacking attacks and minimize the disclosure of sensitive data.

• Fire Science and Engineering
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• v.34 no.1
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• pp.26-36
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• 2020

It is very difficult to suppress fire by rapid flame spread through flue space between flammable commodities on the rack when a fire occurs in the rack storage. At present, the fire protection system for rack storage in Korea has many issues, and the new fire protection system was designed and developed by it. A smart system using the sensor network and artificial intelligence was designed to detect fire very rapidly and track the location of a fire. In the very early stages, the system was constructed using vertical open sprinkler pipes, wet pipes, and solenoid valves to allow water to spray near fire locations. Based on the design results, the system was installed and tested, and the full-scale test was successfully completed.

• Annual Conference of KIPS
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• 2023.05a
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• pp.522-524
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• 2023

위치 기반 서비스(LBS)의 확산으로 다양한 분야에서 활용할 수 있는 많은 양의 경로 데이터가 생성되고 있다. 하지만 공격자가 경로 데이터를 통해 잠재적으로 사용자의 개인정보를 유추할 수 있다는 문제점이 존재한다. 따라서 경로 데이터의 프라이버시를 보존하며 유용성을 유지할 수 있는 GAN(Generative Adversarial Network)을 사용한 많은 연구가 진행되고 있다. 그러나 GAN은 생성된 결과물을 제어하지 못한다는 한계점을 가지고 있다. 본 논문에서는 ACGAN(Auxiliary classifier GAN)을 통해 생성된 결과물을 제어함으로써 경로 데이터의 민감한 정점을 숨기고, Attention mechanism을 결합하여 높은 유용성과 익명성을 제공하는 합성 경로 생성 모델인 TAP-GAN(Trajectory attention and protection-GAN)을 제안한다. 또한 모델의 성능을 입증하기 위해 유용성 및 익명성 실험을 진행하고, 선행 연구 모델과의 비교를 통해 TAP-GAN이 경로 데이터의 유용성을 보장하면서 사용자의 프라이버시를 효과적으로 보호할 수 있음을 확인하였다.

• Journal of the Korea Society of Computer and Information
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• v.27 no.8
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• pp.241-251
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• 2022

Diagnosis and management of customer's skin condition is an important essential function in the cosmetics and beauty industry. As the social media environment spreads and generalizes to all fields of society, the interaction of questions and answers to various and delicate concerns and requirements regarding the diagnosis and management of skin conditions is being actively dealt with in the social media community. However, since social media information is very diverse and atypical big data, an intelligent skin condition diagnosis system that combines appropriate skin condition information analysis and artificial intelligence technology is necessary. In this paper, we developed the skin condition diagnosis system SCDIS to intelligently diagnose and manage the skin condition of customers by processing the text analysis information of social media into learning data. In SCDIS, an artificial neural network model, AnnTFIDF, that automatically diagnoses skin condition types using artificial neural network technology, a deep learning machine learning method, was built up and used. The performance of the artificial neural network model AnnTFIDF was analyzed using test sample data, and the accuracy of the skin condition type diagnosis prediction value showed a high performance of about 95%. Through the experimental and performance analysis results of this paper, SCDIS can be evaluated as an intelligent tool that can be used efficiently in the skin condition analysis and diagnosis management process in the cosmetic and beauty industry. And this study can be used as a basic research to solve the new technology trend, customized cosmetics manufacturing and consumer-oriented beauty industry technology demand.

• Industry Promotion Research
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• v.5 no.4
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• pp.1-13
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• 2020

Since the 4th industrial revolution was thrown into the world at the Davos World Economic Forum in January 2016, the world has been undergoing major social and economic changes. In this study, the direction of quality management in the 4th industrial revolution era was examined. First, in all the major countries the industrial structural changes and smart business models were confirmed due to the convergence of new ICT such as IoT, robotics, 3D printing, big data, and AI with the existing technologies and industries. Second, we found that although the core technology level of the 4th industrial revolution in Korea is not as good as that of advanced countries, we have been working on expanding smart production methods and creating new industries by utilizing new ICT. Finally, it was confirmed that quality management is a real-time implementation of new ICT that reflects the needs of the market in real time based on big data from the planning and design stage of products or services.

• Journal of the Korea Society of Computer and Information
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• v.28 no.3
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• pp.35-43
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• 2023

Emotion recognition while driving is an essential task to prevent accidents. Furthermore, in the era of autonomous driving, automobiles are the subject of mobility, requiring more emotional communication with drivers, and the emotion recognition market is gradually spreading. Accordingly, in this research plan, the driver's emotions are classified into seven categories using psychological and behavioral data, which are relatively easy to collect. The latent vectors extracted through the auto-encoder model were also used as features in this classification model, confirming that this affected performance improvement. Furthermore, it also confirmed that the performance was improved when using the framework presented in this paper compared to when the existing EEG data were included. Finally, 81% of the driver's emotion classification accuracy and 80% of F1-Score were achieved only through psychological, personal information, and behavioral data.

• Journal of Advanced Technology Convergence
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• v.1 no.2
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• pp.01-09
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• 2022

Recently, safety issues in companies and public institutions are no longer a task that can be postponed, and when a major safety accident occurs, not only direct financial loss, but also indirect loss of social trust in the company and public institution is greatly increased. In particular, in the case of a fatal accident, the damage is even more serious. Accordingly, as companies and public institutions expand their investments in industrial safety education and prevention, open AI learning model creation technology that enables safety management services without being affected by user behavior in industrial sites where high-risk situations exist, edge terminals System development using inter-AI collaboration technology, cloud-edge terminal linkage technology, multi-modal risk situation determination technology, and AI model learning support technology is underway. In particular, with the development and spread of artificial intelligence technology, research to apply the technology to safety issues is becoming active. Therefore, in this paper, an open cloud platform design method that can support AI model learning for high-risk site safety management is presented.

• Industry Promotion Research
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• v.7 no.3
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• pp.17-26
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• 2022

As the well-being mindset to keep our minds and bodies free and healthy more than anything else in the society we live in is spreading, the meaning of health care has become a key part of the 4th industrial revolution such as big data, IoT, AI, and block chain. The advancement of the advanced medical information service industry is being promoted by utilizing convergence technology. In digital healthcare, the development of intelligent information technology such as artificial intelligence, big data, and cloud is being promoted as a digital transformation of the traditional medical and healthcare industry. In addition, due to rapid development in the convergence of science and technology environment, various issues such as health, medical care, welfare, etc., have been gradually expanded due to social change. Therefore, in this study, first, the general meaning and current status of digital health care medical information is examined, and then, developmental tasks to activate digital health care medical information are analyzed and reviewed. The purpose of this article is to improve usability to fully pursue our human freedom.

• Annual Conference of KIPS
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• 2011.11a
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• pp.261-264
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• 2011

최근 들어 스마트폰 보급의 확산과 더불어 일상생활에서 스마트폰 사용자들이 편리하게 이용할 수 있는 모바일 편의 서비스들의 개발도 활발하게 진행되고 있다. 본 논문에서는 안드로이드 스마트폰 환경에서 개발된 일정 안내 서비스의 설계와 구현에 대해 소개한다. 이 서비스는 선행 연구를 통해 개발된 인공지능 자동 계획 기술 기반의 모바일 퍼스널 어시스턴트 개발 도구인 스마트 스크립트 시스템을 이용하여 구현되었으며, 한 번의 버턴이나 아이콘 터치만으로 간단히 구글 캘린더에 저장중인 스마트폰 사용자의 일정 데이터를 기초로 음성 발화를 통해 그 날의 일정과 날씨를 알려주는 서비스이다. 본 논문에서는 실험을 통해 스마트 스크립트 시스템 및 일정 안내 서비스의 편리성과 효율성을 분석해본다.

• Prospectives of Industrial Chemistry
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• v.22 no.4
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• pp.13-19
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• 2019

최근 가공할만한 성능의 슈퍼컴퓨터에 머신 러닝 기법을 연동한 인공 지능형 소재 정보학이 과학 기술 및 산업계에 새로운 연구개발 패러다임으로 급속히 확산되고 있다. 본 기고문에서는 이 기법의 성공에 핵심적 요소인 정확한 데이터베이스 구축을 위해 제일원리 전산을 적용하는 것과 이를 기반으로 소재를 구성하는 원소 간 인공 신경망 포텐셜을 만드는 방법을 소개하고자 한다. 이 연구 방법론은 나노 스케일 신소재 개발에 적용할 경우, 양자역학 수준의 정밀도로 순수 제일원리 전산 대비 100배 이상의 빠른 결과를 도출할 가능성이 있음을 예시한다. 이는 향후 다양한 산업계에 막대한 파급효과를 가져올 것으로 예상된다.