• Annual Conference of KIPS
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• 2022.11a
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• pp.709-711
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• 2022

ICT 기술의 빠른 발전과 함께 Internet of Things (IoT) 환경에서의 Internet Protocol (IP) 카메라의 사용률이 증가하면서, IP 카메라에 대한 개인정보 이슈와 제품의 보안성 검토 관련 소비자의 개인정보 유출 우려가 증가하고 있다. 본 논문에서는, IP 카메라에 대한 4개 종류의 Denial of Service (DoS) 공격을 통해 IP 카메라 이상 반응을 확인했다. 또한, 이 과정에서 수집한 공격 패킷 데이터를 기반으로, DoS 공격을 탐지하는 간단한 피쳐 구성과 머신러닝 모델을 제안하였다. 최종적으로, DoS 공격을 통해 실제 IP 카메라에 대한 가용성 테스트를 수행하였으며 머신러닝 알고리즘 4개 Decision Tree, Random Forest, Multilayer Perceptron, SVM에서의 DoS 공격 탐지 성능을 비교하였다.

• Smart Media Journal
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• v.11 no.4
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• pp.19-29
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• 2022

Recently, with the development of IoT technology, the number of farms using smart farms is increasing. Smart farms monitor the environment and optimise internal environment automatically to improve crop yield and quality. For optimized crop cultivation, researches on predict crop productivity are actively studied, by using collected agricultural digital data. However, most of the existing studies are based on statistical models based on existing statistical data, and thus there is a problem with low prediction accuracy. In this paper, we use various predition models for predicting the production and sales profits, and compare the performance results through models by using the agricultural digital data collected in the facility horticultural smart farm. The models that compared the performance are multiple linear regression, support vector machine, artificial neural network, recurrent neural network, LSTM, and ConvLSTM. As a result of performance comparison, ConvLSTM showed the best performance in R2 value and RMSE value.

• Electronics and Telecommunications Trends
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• v.29 no.4
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• pp.72-81
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• 2014

최근 CPS(Cyber-Physical Systems)는 IoT(Internet of Things), 빅데이터 기술과 함께 미래 전력산업의 핵심 키워드로 등장하고 있다. CPS는 산업의 중심이 하드웨어에서 소프트웨어로 빠르게 전환하고 있는 현시점에서 기존의 물리시스템 혹은 물리프로세스를 효율적이고 안전하며 지능적으로 만들고 운영하기 위한 기술이다. 지난 2007년 미국을 중심으로 기술개발이 시작된 이래 다시금 새로운 전환기를 맞이하고 있다. 미국은 지난 2013년 제 2기 PIF(Presidential Innovation Fellow)의 주도로 SmartAmerica Challenge라는 이름으로 새로운 가치와 일자리 창출을 위한 국민생활 밀착형 대규모 CPS 융합 프로그램을 추진 중이다. 이를 통해 미국은 학술적이고 이론적인 CPS R&D 전략으로부터 보다 현실적으로 국부를 창출할 수 있는 개방형 R&BD형의 CPS 기술발전을 모색하고 있다. 본고에서는 CPS의 태동 배경으로부터 최근 SmartAmerica Challenge에 이르는 전반적인 CPS 기술동향을 조망하고 향후 우리의 나아갈 바를 제언하는 것으로 글을 맺고자 한다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.10a
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• pp.351-354
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• 2016

The competition of Go between AlphaGo and Lee Sedol attracted global interest leading AlphaGo to victory. The core function of AlphaGo is deep-learning system, studying by computer itself. Afterwards, the utilization of deep-learning system using artificial intelligence is said to be verified. Recently, the government passed the loT Act and developing its business model to promote loT. This study is on analyzing IoT business environment using deep-learning AI and constructing specialized business models.

• The Journal of the Convergence on Culture Technology
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• v.9 no.6
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• pp.1001-1006
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• 2023

Globally, rising energy costs and increased energy demand are important issues for the food processing and manufacturing industries, which consume significant amounts of energy throughout the supply chain. Accordingly, there is a need for the development of a real-time energy monitoring and analysis system that can optimize energy use. In this study, a food factory energy monitoring system was proposed based on IoT installed in a food factory, including monitoring of each facility, energy supply and usage monitoring for the heat treatment process, and search functions. The system is based on the IoT sensor of the food processing plant and consists of PLC, database server, OPC-UA server, UI server, API server, and CIMON's HMI. The proposed system builds big data for food factories and provides facility-specific monitoring through collection functions, as well as energy supply and usage monitoring and search service functions for the heat treatment process. This data collection-based energy monitoring system will serve as a guide for the development of a small and medium-sized factory energy monitoring and management system for energy savings. In the future, this system can be used to identify and analyze energy usage to create quantitative energy saving measures that optimize process work.

• Convergence Security Journal
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• v.22 no.2
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• pp.115-120
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• 2022

This study analyzed the recent trends in the sports environment to which big data and AI technologies, which are representative technologies of the 4th Industrial Revolution, and approached them from the perspective of convergence of big data and AI technologies in the sports field. And the results are as follows. First, it is being used for player and game data analysis and team strategy establishment and operation. Second, by combining big data collected using GPS, wearable equipment, and IoT with artificial intelligence technology, scientific physical training for each player is possible through user individual motion analysis, which helps to improve performance and efficiently manage injuries. Third, with the introduction of an AI-based judgment system, it is being used for judge judgment. Fourth, it is leading the change in marketing and game broadcasting services. The technology of the 4th Industrial Revolution is bringing innovative changes to all industries, and the sports field is also in the process. The combination of big data and AI is expected to play an important role as a key technology in the rapidly changing future in a sports environment where scientific analysis and training determine victory or defeat.

• Information and Communications Magazine
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• v.32 no.11
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• pp.12-20
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• 2015

최근 의학 기술이 눈부시게 발전함에 따라 사람들은 수명이 연장되고 삶의 질 향상에 많은 관심을 가지게 되었다. 더욱이 혁신적인 디지털 기술 발전과 함께 다양한 웨어러블 기기와 수많은 헬스케어 어플리케이션이 출시되고 있으며, 이들은 어떻게 하면 개인의 성향이나 체질에 잘 맞는 맞춤형 (개인화) 서비스를 제공할 수 있을 것인가에 관심을 두고 진화하고 있다. 따라서 IoT 환경의 일상생활에서 입력되는 센서 데이터의 수집, 처리, 가공 기술, 일상 행위 및 라이프 스타일 인지, 지식 획득 및 관리 기술, 개인화 추천서비스 제공, 프라이버시 및 보안을 통합적으로 지원할 수 있는 프레임워크 개발에 대한 요구가 증대되고 있다. 이에 본 고에서는 저자가 개발중인 개인 맞춤 건강 및 웰니스 서비스를 제공하는 마이닝 마인즈 프레임워크를 소개한다. 마이닝 마인즈는 현존하는 최신 기술의 집약체로 개인화, 큐레이션, 빅 데이터 처리, 클라우드 컴퓨팅의 활용, 다양한 센서 정보의 수집과 분석, 진화형 지식의 생성과 관리, UI/UX를 통한 습관화 유도 등 다양한 요소를 포함한다. 그리고 건강 및 웰니스 프레임워크 요구사항 분석을 통해 마이닝 마인즈가 이러한 요구를 충족시킬 수 있으며, 개발된 프로토타입을 통해 개인화 서비스의 발전 가능성을 입증하고 향후 나아가야 할 방향을 제시한다.

• Proceedings of the Korea Water Resources Association Conference
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• 2019.05a
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• pp.48-48
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• 2019

최근 국내 구미 불산 누출사고 등과 같은 화학사고들이 많이 발생하면서 화학사고 대응체계 미흡으로 인한 사건 사례들이 발생하였다. 이러한 화학사고에 대한 대응체계를 4차산업혁명에 부합한 기술들을 접목시킴으로써 피해를 최소화 할 필요성이 있다고 판단되었다. 현재 국내의 화학사고 대응을 위해 다양한 센서를 기반으로 하천에서의 계측이 이루어지고 있으나, 아직은 빅데이터가 구축되기 전단계인 단계적 하천관리가 이루어지고 있는 실정이다. 따라서 화학사고 시 유해물질이나 대체지표를 감지하고 측정할 수 있는 센서기술의 개발이 필요하다. 화학사고의 신속한 대응에 있어 다양한 센서를 기반으로 화학물질을 감지하고, 실시간으로 계측된 데이터들이 IoT망과 연계되어 실시간으로 정보를 제공할 수 있는 기술 개발의 필요성이 매우 중요하다. 따라서 본 연구에서는 하천의 유해화학물질 유출사고 발생 시 유해화학물질의 유출지점 및 유출량을 규명하고 하류 취수장 등 하천 주요지점에서의 유해화학물질 도달 시간, 기준 농도 초과여부를 예측하여 유출 사고에 대한 신속한 대응을 통해 피해가 최소화가 될 수 있도록 각종 수질센서 모듈, IoT 기술을 접목하여 고성능 GPS 전자부자 기술을 개발하고자 하였다.

• Smart Media Journal
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• v.11 no.5
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• pp.9-16
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• 2022

Recently, agricultural sites are automating into digital agricultural smart farms by applying technologies such as big data and Internet of Things (IoT). These smart farms aim to increase production and improve crop quality by measuring the environment of crops, investigating and processing data. Production prediction is an important study in smart farm digital agriculture, which is a high-tech agriculture, and it is necessary to analyze environmental data using big data and further standardized research to manage the quality of growth information data. In this paper, environmental and production data collected from smart farm strawberry farms were analyzed and studied. Based on regression analysis, crop production prediction models were analyzed using Ridge Regression, LightGBM, and XGBoost. Among the three models, the optimal model was XGBoost, and R2 showed 82.5 percent explanatory power. As a result of the study, the correlation between the amount of positive fluid absorption and environmental data was confirmed, and significant results were obtained for the production prediction study. In the future, it is expected to contribute to the prevention of environmental pollution and reduction of sheep through the management of sheep by studying the amount of sheep absorption, such as information on the growing environment of crops and the ingredients of sheep.

• KIPS Transactions on Computer and Communication Systems
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• v.3 no.10
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• pp.383-392
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• 2014

The research for coatings is one of the most popular and active research in the polymer industry. For the coatings, electronics industry, medical and optical fields are growing more important. In particular, the trend is the increasing of the technical requirements for the performance and accuracy of the coatings by the development of automotive and electronic parts. In addition, the industry has a need of more intelligent and automated system in the industry is increasing by introduction of the IoT and big data analysis based on the environmental information and the context information. In this paper, we propose an optimization model for the design of experiments based coating formulation data objects using the Internet technologies and big data analytics. In this paper, the coating formulation was calculated based on the best data analysis is based on the experimental design, modify the operator with respect to the error caused based on the coating formulation used in the actual production site data and the corrected result data. Further optimization model to correct the reference value by leveraging big data analysis and Internet of things technology only existing coating formulation is applied as the reference data using a manufacturing environment and context information retrieval in color and quality, the most important factor in maintaining and was derived. Based on data obtained from an experiment and analysis is improving the accuracy of the combination data and making it possible to give a LOT shorter working hours per data. Also the data shortens the production time due to the reduction in the delivery time per treatment and It can contribute to cost reduction or the like defect rate reduced. Further, it is possible to obtain a standard data in the manufacturing process for the various models.