• Journal of Korean Society of Industrial and Systems Engineering
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• v.44 no.3
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• pp.117-124
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• 2021

The development of IOT technology and artificial intelligence technology is promoting the smartization of manufacturing system. In this study, data extracted from acceleration sensor and current sensor were obtained through experiments in the cutting process of SKD11, which is widely used as a material for special mold steel, and the amount of tool wear and product surface roughness were measured. SVR (Support Vector Regression) is applied to predict the roughness of the product surface in real time using the obtained data. SVR, a machine learning technique, is widely used for linear and non-linear prediction using the concept of kernel. In particular, by applying GSVQR (Generalized Support Vector Quantile Regression), overestimation, underestimation, and neutral estimation of product surface roughness are performed and compared. Furthermore, surface roughness is predicted using the linear kernel and the RBF kernel. In terms of accuracy, the results of the RBF kernel are better than those of the linear kernel. Since it is difficult to predict the amount of tool wear in real time, the product surface roughness is predicted with acceleration and current data excluding the amount of tool wear. In terms of accuracy, the results of excluding the amount of tool wear were not significantly different from those including the amount of tool wear.

• Proceedings of the Korean Society of Computer Information Conference
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• 2024.01a
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• pp.131-134
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• 2024

본 논문에서는 기존 철도 운영 및 관리시에 철도 주변환경으로 부터 발생하는 소음, 진동, 미세먼지 센서에서 다양한 실시간 스트림 데이터를 감지하고 정형화된된 데이터 패턴을 인식하고 분석할 수 있도록 데이터를 구성 및 저장하고 분석된 데이터를 표현할 수 있도록 시각화 지원을 위한 모니터링 시스템 플랫폼을 구현하였다. 데이터 전송을 위해 시리얼 통신 기법을 주로 적용하였으나, 센서와 디바이스의 증가로 인해 시리얼 통신의 한계가 나타났다. 따라서, 본 연구에서는 기존의 아두이노와 서버 간의 직접 통신 방식 대신 라즈베리파이를 도입하여 MQTT Broker(브로커)를 설치하고 통신을 진행하였다. 철도 데이터 모니터링 시스템 플랫폼은 NoSQL 데이터베이스인 MonGoDB와 데이터 시각화할 수 있는 Grafana를 이용하여 구축하였다.

• Smart Media Journal
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• v.6 no.2
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• pp.42-49
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• 2017

It is important to realize automation services by communicating in IoT with humans, objects & objects, and forming a common network. People used web like the most powerful network way to sharing things and communication. Therefore the efficiency method communication between each device and the web in IoT could be different from ones. The best method for high quality software product in web applications is software reuse ; Modules, classes, patterns, frameworks, and business components are reusable elements of various perspectives. Components is plugged with others through well-defined interfaces, which can overcome the operation and complexity of application development. A web-based distributed environment for IoT applications is a standard architecture use information collected from various devices for developing and using applications. For that reason, the network management which manages the constituent resources for the best service control in IoT application is required as a sub-layer support service in most applications as well as individual applications. In this paper, we measure to develop a network management system based not only by components but on heterogeneous internetworks. For procedure this, we clarify a component architecture for classifying and classify also the component needed in the IOT and network domain or order the type of real network management system.

• Journal of Advanced Navigation Technology
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• v.24 no.6
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• pp.620-626
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• 2020

This research propose and simulate a solar power generation system monitoring system based on Modbus TCP communication using RaspberryPi, an IOT equipment, as a master and an inverter as a slave. In this model, various sensors are added to the RaspberryPi to add necessary information for monitoring solar power plants, and power generation prediction and monitoring information are transmitted to the smart phone through real-time power generation prediction. In addition, information that is continuously generated by the solar power plant is built on the server as big data, and a deep learning model for predicting power generation is trained and updated. As a result of the study, stable communication was possible based on Modbus TCP with the Raspberry Pi in the inverter, and real-time prediction was possible with the deep learning model learned in the Raspberry Pi. The server was able to train various deep learning models with big data, and it was confirmed that LSTM showed the best error with a learning error of 0.0069, a test error of 0.0075, and an RMSE of 0.0866. This model suggested that it is possible to implement a real-time monitoring system that is simpler, more convenient, and can predict the amount of power generation for inverters of various manufacturers.

• Annual Conference of KIPS
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• 2017.11a
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• pp.1055-1057
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• 2017

본 프로젝트는 아두이노 기기와 라즈베리파이 기기, 그리고 여러 센서와 카메라를 이용하여 건강 상태 모니터링 및 판단 기술을 통해 노약자의 위급상황 시에 조치를 취할 수 있게끔 도와주는 프로그램을 개발한다. 라즈베리파이 카메라를 통해 얻은 영상으로 노약자의 위급한 상황의 여부를 판단하고 아두이노를 이용하여 온도와 습도를 측정하여 쾌적한 환경의 적합성을 판단한다. 원격으로 노약자의 응급 상황과 생활 환경의 쾌적함 정도를 웹에서 보호자가 확인할 수 있고, 위급한 상황이 발생할 때 빠른 대처를 취할 수 있게 한다.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2018.11a
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• pp.55-56
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• 2018

In order to reduce the risk of accidents, we proposed a construction safety management system combined with wearable device and LoRa (Low-Range Wireless Network) communication method to apply the usefulness of Internet (IoT) technology which means "everything connected". to construction safety management Management system. The proposed wearable safety device is a device that relays information exchange between wearable safety device and safety management server by LoRa wireless communication method. The safety management server can store workers bio-data and perform big data analysis. If a risk factor is determined from the analysis result, a warning is sent to the wearable safety device and the manager's application. The goal of this system is to prevent construction workers from entering the dangerous area that is not suitable for work, and to prevent safety accidents caused by human cause by detecting abnormal condition during work.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2018.11a
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• pp.57-58
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• 2018

The number of deaths in the korean construction industry is more than three times the OECD average. Although safety management system should be improved to prevent the safety accidents, it is difficult to improve due to domestic safety conditions. Especially, in order to prevent accidents at construction sites, there is an increasing tendency to monitor the movement of workers and equipment in real time by introducing a location positioning system. Therefore, this study proposes a system that can monitor the position of workers and heavy equipments in real - time, detect danger and transmit alarms so that workers can pay attention to safety and keep safety. The system is expected to reduce safety accidents by transmitting alarms to workers so that they can pay attention.

• KIPS Transactions on Computer and Communication Systems
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• v.5 no.9
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• pp.269-274
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• 2016

In this paper We focuses on suggestion to quality model for IoT infrastructure services for Internet of Things. Quality model is suggested on security set out in ISO25000 quality factors and assessment of the existing traditional software application of ISO 9126 quality model. We validated that the proposed model can be realized it was applied to evaluate the 4 elements and related security in Metrics.

• Annual Conference of KIPS
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• 2021.11a
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• pp.91-92
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• 2021

최근 사물 인터넷 관련 해킹 우려 신고 건수가 증가하는 추세를 보이고 있다. 하지만 급격하게 늘어나는 IoT 환경에 따라서 관리자가 새로운 침입 탐지 공격패턴을 인식하는 것에 대한 어려움이 있으며, 대량의 공격이나 새로운 공격패턴이 등장할 경우 이에 맞는 특징을 재선정해야 할 경우도 발생한다. 본 논문에서는 운영 네트워크 상에 특정이상동작 파악 및 근원지 진단을 위한 목적을 가진 전반적인 네트워크 상태 분석 및 사용자 이슈 식별이 가능한 프레임워크를 설계하였다.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.1
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• pp.205-212
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• 2023

In the modern society, the extreme weather caused by climate change has brought about exceptional damage in succession over the world due to the use of fossil fuels, and infectious diseases such as COVID-19 worsen the quality of human life. It is urgently necessary to reduce green-house gas and use new renewable energy. The global environmental pollution should be decreased by reducing the use of fossil fuels and using new renewable energy. This paper suggests a system which can function for the environment of four seasons, safety and communication, through the photovoltaic power-based intelligent CCTV, internet and WiFi, and cooling and heating systems, and can optimally manage power, through the real-time monitoring of the production and the consumption of the photovoltaic power. It suggests a hybrid generation system supporting diesel generation without discontinuation in the case of emergency such as system power outage caused by cold waves, typhoons and natural disasters in which the photovoltaic power generating system cannot be used.