• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.6 no.2
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• pp.81-88
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• 2016

Machine-to-Machine (M2M) communication provides each component (machine) with access to Internet, evolving into the IoT technology. IoT is a trend where numbers of devices provide the communication service, using the Internet protocol. As spreading the concept of IoT(Internet of Things), various objects become home information sources. According to the wide spread of various devices, it is difficult to access data on the devices with unified manners. Under this environment, security is a critical element to create various types of application and service. In this paper propose the inter-device authentication and Centralized Remote Security Provisioning framework in Open M2M environment. The results of previous studies in this task is carried out by protecting it with the latest information on M2M / IoT and designed to provide the ultimate goal of future M2M / IoT optimized platform that can be integrated M2M / IoT service security and security model presents the information.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.380-380
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• 2020

가뭄 피해 극복을 위한 인공 함양지 통합관리시스템의 일부로써 지표수-지하수 연계 특성 분석용 의사결정을 전달하는 인공지능 스마트 계측기의 필요성이 꾸준히 제기되어 왔으나 실용성과 효율성을 동시에 갖춘 계측기는 시장에 출시되지 않았다. 기존의 계측기는 단순 측정이 목적이었으며 분석을 위해서는 일정 기간 직접 계측하여 분석하거나, 계측데이터를 원격 망을 통하여 서버로 전송하고 관리자가 데이터를 해석하는 방식을 취하였다. 또한, 수질 계측과 수질의 미소 변동성을 동시에 계측하여 수질 변화상태를 판단 할 수 있는 수질 계측기는 상품화되지 않아 다목적 수질 분석에 한계점을 갖고 있다. 이러한 한계점이 기존의 지하수 수질 계측기로는 불가능한 수중 라돈을 채수 없이 계측 가능하도록 하고, 순간 수질 변화 및 수질 변화 요인분석이 가능한 계측을 위하여 라돈, 전도도, 수위, 수온 및 필름형 pH 센서를 개발하여 적용한 다항목 계측기로 통합하는 연구가 필요한 이유이다. 개발한 계측기는 빅데이터 기반의 지능형 수질 변동성 분석 알고리즘을 내장하고 수직 깊이 방향의 다중심도 계측이 가능하도록 핵심적인 통신 연결성을 확보하였고 다양한 수질에서 견딜 수 있으며 특히 인공함양에서 발생하는 철, 망간에 부식되지 않는 재질을 이용하여 설계한 '지표수-지하수 연계 특성 분석용 다심도 및 인공지능 스마트 계측장치'이다. 본 장치는 기존 지하수 수질 계측기에서는 불가능하였던 순간 수위변화 및 수위변화 요인분석이 가능한 계측을 위하여 초당 측정 샘플링 주파수(10Hz)를 높인 계측회로를 개발하여 적용하였다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2020.01a
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• pp.143-144
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• 2020

4차 산업 시대가 도래하여 빅데이터와 딥러닝 기술은 다양한 분야에서 아주 중요한 기술로 자리 잡고 있으며, 현재 세계 여러 분야에서 이 기술들을 이용하여 일상, 산업 분야에 적용을 시키고자 한다. 국내에서는 스마트 팩토리, 스마트 시티와 같은 분야에 적용하고 있다. 본 논문에서는 스마트 시티에 적용할 수 있는 횡단보도 상황을 인지하여 교통제어에 활용할 수 있는 빅데이터를 생산하거나 효율적인 교통제어에 활용할 수 있도록 Nvidia Jetson TX2와 실시간 객체 감지 기술인 YOLO v3를 이용하여 횡단보도용 상황 인식을 위한 영상인식 장치를 개발하였다. 제안하는 기술들을 이용하여 스마트시티 구축에 활용할 수 있고, 실시간으로 추가적으로 필요한 객체를 감지하여 확장이 용이한 장점이 있다. 또한 구현에서 효율성을 높이기 위하여 에지 컴퓨팅, 스페이스 디텍션과 같은 기술들을 활용하였다.

• Journal of Aerospace System Engineering
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• v.17 no.2
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• pp.111-119
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• 2023

Internal storage state, weight data, and weight-centered calculation values for overhead bin can all be seen in this paper's real-time internal status identification system. The suggested system offers such valuable data via a range of sensors, including load cells and switch arrays. The proposed system could locate internal free space, locate the center of gravity, and give real-time visual information. It was developed utilizing an embedded system and the C programming language. These features led to the creation of smart overhead bins and real-time cargo loading monitoring technologies, both of which could one day aid in the creation of a cargo loading automation system.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.59 no.4
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• pp.387-398
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• 2023

Conventional aquaculture faces declining productivity, shifting to recirculating aquaculture system (RAS), known for minimizing water usage and maintaining consistent water temperatures for year-round fish growth. Rainbow trout (Oncorhynchus mykiss), a globally important cold-water species and the third most farmed fish in inland waters of Korea, valued for its fecundity and rapid growth. Dissolved oxygen, an important environmental factor affecting fish production and economics, highlights the need for smart aquaculture practices. Since 2018, the rise of intelligent aquaculture platforms, incorporating information and communications technology (ICT), emphasizes the essential role of RAS implementation. This eight-week study aimed to determine the optimal dissolved oxygen concentration for rainbow trout in RAS, utilizing a device for continuous monitoring, control and record. Dissolved oxygen concentrations were set at 5-6 mg/L, 9-10 mg/L, 14-15 mg/L and 17-18 mg/L. The growth rate significantly decreased at 5-6 mg/L, with no significant differences in other experimental groups. In hematological analysis, growth hormone (GH) was significantly highest at 5-6 mg/L, followed by 9-10 mg/L while Insulin-like growth factor-1 (IGF-1) was significantly lowest at 5-6 mg/L. In conclusion, the optimal dissolved oxygen concentration for rainbow trout in RAS is approximately 9-10 mg/L. Higher concentrations do not contribute to further growth or profitability.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.6
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• pp.1345-1352
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• 2023

With the development of virtual reality (VR) and blockchain technology, Metaverse is being used in various fields such as games, education, and social networking. At the same time, shipments of wearable devices such as smartwatches are growing every year, becoming more and more integrated into people's daily lives. This study presents a new possibility of reflecting the user's body signals measured through the combination of the two phenomena in the metaverse character. Various biometric information such as the user's heart rate and amount of exercise collected through the smartwatch are reflected on the character in the metaverse, allowing the user's physical condition to be reflected in the virtual world. Through this, Metaverse is expected to provide a new experience that can be called 'extended reality' beyond simple virtual reality, improve user's satisfaction with Metaverse, and suggest a direction for the development of smartwatches.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.6
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• pp.1239-1244
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• 2023

In this study, we developed an IoT-based management system to manage a can/PET crusher. Various sensors such as two load cells, DHT22 temperature and humidity sensor, and fine dust meter were interfaced with ESP32 to construct an IoT device, and a management server was built using Node-RED. The system monitors the weight of pressed cans and shredded PET bottles in real time and sends a text message to the manager when the weight exceeds the predetermined threshold for timely collection. The results of the operational test confirmed that the system provides accurate monitoring and efficient notification functions, and offers the possibility of solving environmental problems by improving the efficiency of waste management such as cans and PET bottles.

• Smart Structures and Systems
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• v.33 no.1
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• pp.55-64
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• 2024

This paper proposes a fusion imaging-based coating-defect classification method for steel structures that uses zero-shot learning. In the proposed method, a halogen lamp generates heat energy on the coating surface of a steel structure, and the resulting heat responses are measured by an infrared (IR) camera, while photos of the coating surface are captured by a charge-coupled device (CCD) camera. The measured heat responses and visual images are then analyzed using zero-shot learning to classify the coating defects, and the estimated coating defects are visualized throughout the inspection surface of the steel structure. In contrast to older approaches to coating-defect classification that relied on visual inspection and were limited to surface defects, and older artificial neural network (ANN)-based methods that required large amounts of data for training and validation, the proposed method accurately classifies both internal and external defects and can classify coating defects for unobserved classes that are not included in the training. Additionally, the proposed model easily learns about additional classifying conditions, making it simple to add classes for problems of interest and field application. Based on the results of validation via field testing, the defect-type classification performance is improved 22.7% of accuracy by fusing visual and thermal imaging compared to using only a visual dataset. Furthermore, the classification accuracy of the proposed method on a test dataset with only trained classes is validated to be 100%. With word-embedding vectors for the labels of untrained classes, the classification accuracy of the proposed method is 86.4%.

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.2
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• pp.397-402
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• 2024

Speech recognition and motion recognition technologies are applied and used in various smart devices, but they are composed of simple command recognition forms and are used as simple functions. Apart from simple functions for recognition data, professional command execution capabilities are required based on data learned in various fields. Research is being conducted on a system platform that provides optimal data to users using Generative AI, which is currently competing around the world, and can interact through voice recognition and motion recognition. The main technical processes designed for this study were designed using technologies such as voice and motion recognition functions, application of AI technology, and two-way communication. In this paper, two-way communication between a device and a user can be achieved by various input methods through voice recognition and motion recognition technology applied with AI technology.

• Journal of the Korea Society of Computer and Information
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• v.29 no.5
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• pp.67-74
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• 2024

As the number of coffee shops increases, many people are studying or working at coffee shops. Coffee shop operators have been required to analyze customer visits due to customer turnover and profit problems. Methods such as image analysis, QR code authentication, and Bluetooth beacon have been proposed for these statistics and analysis. However, it is difficult to use due to problems such as invasion of privacy and low accuracy. Therefore, in this study, to solve these problem and provide more accurate in-store congestion information, we propose a crowding measurement method of coffee shop using high frequency signal. There is an advantage in that a high frequency signal replaces the Bluetooth signal, and the transmission range of the signal is limited to the store, thereby increasing the accuracy of the method. To verify the performance of the proposed system, we conducted a comparative experiment with a Bluetooth based system, and as a result, the proposed method showed lower misrecognition rate. Thus, the proposed method will be an effective useful service for providing information on crowding at coffee shops and processing statistics.