• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.133-135
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• 2022

With the development of IoT and AI technologies and media, various digital devices are being used, and unmanned and automation is progressing rapidly. In particular, high-level image processing technology is required in fields such as smart factories, autonomous driving technology, and intelligent CCTV. However, noise present in the image affects processes such as edge detection and object recognition, and causes deterioration of system accuracy and reliability. In this paper, we propose a filtering algorithm using fuzzy weights to reconstruct images damaged by complex noise. The proposed algorithm obtains a reference value using noise judgment and calculates the final output by applying a fuzzy weight. Simulation was conducted to verify the performance of the proposed algorithm, and the result image was compared with the existing filter algorithm and evaluated.

• Proceedings of the Korea Information Processing Society Conference
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• 2021.11a
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• pp.136-139
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• 2021

사물인터넷을 기반으로 실시간으로 소화기 주변의 상태와 화재 발생 여부, 소화기의 상태를 확인할 수 있는 웹 시스템과 화재 알림을 받을 수 있는 애플리케이션을 설계하였다. 소화기 주변의 온도와 습도를 측정하여 화재 유무를 판단하고, 화재를 감지했을 시에 LED 불빛과 경고음을 출력한다. 자이로센서를 이용하여 소화기의 쓰러짐 상태를 파악한다. 웹페이지에서 소화기의 상태 및 소화기 주변의 온습도 상태, 화재 여부를 확인할 수 있다. 사용자는 애플리케이션을 이용하여 회원가입, 로그인을 수행할 수 있으며 화재 알림을 받을 수 있다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.121-123
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• 2021

Image processing is being used in various forms in important fields of the 4th industrial revolution, such as artificial intelligence, smart factories, and the IoT industry. In particular, in systems that require data processing such as object tracking, medical images, and object recognition, noise removal is used as a preprocessing step, but the existing algorithm has a drawback in that blurring occurs in the filtering process. Therefore, in this paper, we propose a filter algorithm using switching fuzzy weights. The proposed algorithm switches the fuzzy function by dividing the low-frequency region and the high-frequency region by the standard deviation of the filtering mask, and obtains the final output according to the fuzzy weight. The proposed algorithm showed improved results compared to the existing method, and showed excellent characteristics in the region where the high-frequency component is strong.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.207-209
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• 2022

In the IoT environment, it is possible to collect life pattern data by recognizing human physical activity from smart devices. In this paper, the proposed model consists of a prediction stage and a recommendation stage. The prediction stage predicts the scale of anxiety and depression by using logistic regression and k-nearest neighbor algorithm through machine learning on the dataset collected from life pattern data. In the recommendation step, if the symptoms of anxiety and depression are classified, the principal component analysis algorithm is applied to recommend food and light exercise that can improve them. It is expected that the proposed anxiety/depression prediction and food/exercise recommendations will have a ripple effect on improving the quality of life of individuals.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.514-516
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• 2022

Busan Metropolitan City runs Community Health Center which aims to health care service based on the community, besides the established health medical service towards people with low-income. 71 centers are run in 2021, therefore, this papear explores the way of digital transition of these centers. Digital Technologies possibly adopted inside the centers are: First, smart devices to advance the management system of chronical diseases based on health index; Second, IoT with mobile tech to manage health index; Third, AI Robot to care lone elderly people and to warn the emergency.

• Journal of Industrial Convergence
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• v.21 no.1
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• pp.175-185
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• 2023

Recently, novel viral infections such as COVID-19 have spread and pose a serious public health problem. In particular, these diseases have a fatal effect on the elderly, threatening life and causing serious social and economic losses. Accordingly, applications such as telemedicine, healthcare, and disease prevention using the Internet of Things (IoT) and artificial intelligence (AI) have been introduced in many industries to improve disease detection, monitoring, and quarantine performance. However, since existing technologies are not applied quickly and comprehensively to the sudden emergence of infectious diseases, they have not been able to prevent large-scale infection and the nationwide spread of infectious diseases in society. Therefore, in this paper, we try to predict the spread of infection by collecting various infection information with regional limitations through a virus disease information collector and performing AI analysis and severity matching through an AI broker. Finally, through the Korea Centers for Disease Control and Prevention, danger alerts are issued to the elderly, messages are sent to block the spread, and information on evacuation from infected areas is quickly provided. A realistic elderly support system compares the location information of the elderly with the information of the infected area and provides an intuitive danger area (infected area) avoidance function with an augmented reality-based smartphone application. When the elderly visit an infected area is confirmed, quarantine management services are provided automatically. In the future, the proposed system can be used as a method of preventing a crushing accident due to sudden crowd concentration in advance by identifying the location-based user density.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.12
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• pp.1563-1570
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• 2018

Internet of Things technology is rapidly becoming a reality in many parts of our lives through various product services, and product development especially in the field of smart home is being actively carried out. Most controllers for controlling various smart home products use smart phone applications. However, smart phone applications are not suitable as smart home controllers, contrary to smart home services that emphasize intelligence and convenience. In order to provide intelligent smart home service, intuitive form of smart home controller is needed, which enables integrated control of smart home device. Therefore, this paper proposes a smart home remote control that can control the Internet devices and services of objects. The proposed smart home remote control provides an environment where users can build a smart home service through the IFTTT(If This Then That) automated service platform.

• Journal of Information Technology Services
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• v.19 no.4
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• pp.85-107
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• 2020

The Internet of Things market, a technology that connects the Internet to various things, is growing day by day. Besides, various smart home services using IoT and AI (Artificial Intelligence) are being launched in homes. Related to this, existing smart home-related studies focus primarily on ICT technology, not on what service improvements should be made in customer positions. In this study, we will use smart home application customer review data to classify functional and design elements of smart home usability value and examine the ways customers think of service improvement. For this, LG Electronics and Samsung Electronics" Smart Home application, the main provider of Smart Home in Korea, customer reviews were crawled to conduct a comparative analysis between them. In this study, the review of IoT home-applications was analyzed to find service improvement insights from customer perspective, and related analysis of text mining, social network analysis and Doc2vec was used to efficiently analyze data equivalent to about 16,000 user reviews. Through this research, we hope that related companies effectively seek ways to improve smart home services that reflect customer needs and are expected to help them establish competitive strategies by identifying weaknesses and strengths among competitors.

• Journal of the Korea institute for structural maintenance and inspection
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• v.23 no.7
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• pp.164-171
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• 2019

Focusing on the bridge facilities, which occupy the largest proportion among SOC public facilities in Korea, it is possible to reduce the cost compared to existing wired measurement systems or wireless measurement systems developed by domestic telecommunications companies, and to increase the technical perfection to be applied to many bridges. We developed a wireless measurement system for bridges. Using LoRa, one of the unlicensed LPWAN technologies, we have developed an optimized MEMS-based LoRa smart sensor node considering the domestic ISM band and the existing wired sensor LoRa DAQ sensor node that can communicate with the LoRa network. Application server was developed for the test bed performance verification and efficient management of the developed sensor node.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.12
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• pp.2348-2354
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• 2016

In recent days, IoT (Internet of Things) technology has been widely used in the field of agriculture, which enables the collection of environmental data and biometric data into the database. The availability of big data on agriculture results in the increase of the machine learning based analysis. Through the analysis, it is possible to forecast agricultural production and the diseases of livestock, thus helping the efficient decision making in the management of smart farm. Herein, we use the environmental and biometric data of Smart Pig farm to derive the accurate relationship model between the environmental information and the daily weight increase of swine and verify the accuracy of the derived model. To this end, we applied the M5P tree algorithm of machine learning which reveals that the wind speed is the major factor which affects the daily weight increase of swine.