• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.10a
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• pp.277-280
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• 2016

Currently, systems for finding missing children are composed of using communication between a QR code and RFID chip, as the use of a smartphone. However, the current systems for finding missing children have limitations in that children can only be found if there are people in the surrounding area; there is an economic burden on parents required to purchase a smartphone for their children; along with difficulties in finding the missing children without the assistance of those in the surrounding area in critical situations such as a kidnapping, due to the limited duration of the battery life. In order to solve such problems, approaches need to be made from two perspectives: having someone in the surrounding area; and absence of anyone in the surrounding area. This thesis is centered on the development of a IoT (Internet of Things) system for finding missing children that combines two methods, namely, the method of finding missing children without a guardian in the surrounding area -within the limited space in which AP is installed by using a beacon and open source hardware being highlighted as the IoT technology - and the method of finding missing children with the smartphone application in which each individual becomes the Access Point (AP). The Main purpose is to provide accurate information of missing children's location for the 2situations and it is found that the accuracy of smartphones APP is 97.7% and security device AP is 91.1%.

• The Journal of the Korea Contents Association
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• v.21 no.12
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• pp.57-65
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• 2021

A hyper-connected intelligence information society is emerging that creates new value by converging IoT, AI, and Bigdata, which are new technologies of the fourth industrial revolution, in all industrial fields. Everything is connected to the network and data is exploding, and artificial intelligence can learn on its own and even intellectual judgment functions are possible. In particular, the Internet of Things provides a new communication environment that can be connected to anything, anytime, anywhere, enabling super-connections where everything is connected. Artificial intelligence technology is implemented so that computers can execute human perceptions, learning, reasoning, and natural language processing. Artificial intelligence is developing advanced technologies such as machine learning, deep learning, natural language processing, voice recognition, and visual recognition, and includes software, machine learning, and cloud technologies specialized in various applications such as safety, medical, defense, finance, and welfare. Through this, it is utilized in various fields throughout the industry to provide human convenience and new values. However, on the contrary, it is time to respond as intelligent and sophisticated cyber threats are increasing and accompanied by potential adverse functions such as securing the technical safety of new technologies. In this paper, we propose a new data modeling method to enable IoT integrated security control by utilizing artificial intelligence technology as a way to solve these adverse functions.

• Journal of the Korean Geosynthetics Society
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• v.23 no.2
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• pp.43-52
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• 2024

Recent abnormal climate conditions have increased the risk of slope collapses, which frequently result in significant loss of life and property due to the absence of early prediction and warning dissemination. In this paper, we develop a slope condition analysis system using IoT sensors and AI-based camera to assess the condition of slopes. To develop the system, we conducted hardware and firmware design for measurement sensors considering the ground conditions of slopes, designed AI-based image analysis algorithms, and developed prediction and warning solutions and systems. We aimed to minimize errors in sensor data through the integration of IoT sensor data and AI camera image analysis, ultimately enhancing the reliability of the data. Additionally, we evaluated the accuracy (reliability) by applying it to actual slopes. As a result, sensor measurement errors were maintained within 0.1°, and the data transmission rate exceeded 95%. Moreover, the AI-based image analysis system demonstrated nighttime partial recognition rates of over 99%, indicating excellent performance even in low-light conditions. Through this research, it is anticipated that the analysis of slope conditions and smart maintenance management in various fields of Social Overhead Capital (SOC) facilities can be applied.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.7
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• pp.935-941
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• 2020

People estimation is important to provide IoT services. Most people counting technologies use camera or sensor data. However, the conventional technologies have the disadvantages of invasion of privacy and the need to install extra infrastructure. This paper proposes a method for estimating the number of people using a Wi-Fi AP. We use channel state information of Wi-Fi and analyze that using deep learning technology. It can be achieved by pre-installed Wi-Fi infrastructure that reduce cost for people estimation and privacy infringement. The proposed algorithm uses a k-binding data for pre-processing process and a 1D-CNN learning model. Two APs were installed to analyze the estimation results of six people. The result of the accurate number estimation was 64.8%, but the result of classifying the number of people into classes showed a high result of 84.5%. This algorithm is expected to be applicable to estimate the density of people in a small space.

• Electronics and Telecommunications Trends
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• v.31 no.1
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• pp.68-77
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• 2016

최근 들어 5G 이동통신 시스템을 위한 표준화 및 기술개발이 본격화되고 있으며, 기존 이동통신 시스템과 차별화되는 5G 이동통신 시스템의 대표적인 목표 중 하나는 사람이 휴대하는 단말기뿐만 아니라 생활 속 모든 사물을 네트워크에 연결하여 정보를 생성하고 공유하는 초연결 네트워크(Internet of Things: IoT) 구축이다. 시장 조사기관이나 다수의 전문가들은 2020년경에는 전 세계적으로 약 500억개의 디바이스가 네트워크에 연결되는 등 사물 디바이스의 폭발적 증가를 예상하며, 이를 통한 부가가치 창출과 시장이 급격히 성장할 것으로 전망하고 있다. 본고에서는 초다수의 사물 디바이스 수용을 위한 5G massive IoT 기술동향 및 이와 관련하여 현재 진행되는 3GPP 표준화 동향에 대해 기술한다.

• Journal of Internet of Things and Convergence
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• v.7 no.2
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• pp.47-53
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• 2021

In order to transmit video data stored in servers with limited bandwidth in IoT environments to many clients, a transmission plan must be established by considering factors such as the number of transmission rate changes, peak transmission rate, and transmission rate changes. This transmission plan is called smoothing, and includes CBA that minimizes the number of transmission rate increases, MCBA that minimizes the number of transmission rate changes, and MVBA to minimize the transmission rate changes. In this work, to evaluate the performance of the proposed algorithm[16], we compare the proposed algorithm with the existing smoothing algorithms with the peak rate, the number of transmission rate changes, the rate increase, the peak rate utilization, and the average transmission rate with various video data and buffer sizes. The evaluation results show that the proposed algorithm helps to efficiently use the server's finite network resources by establishing a transport plan with the lowest average transfer rate.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.1
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• pp.146-152
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• 2022

Information collected from temperature, humidity, inclination, and pressure sensors using Raspberry Pi or Arduino is used in automatic constant temperature and constant humidity systems. In addition, by using it in the agricultural and livestock industry to remotely control the system with only a smartphone, workers in the agricultural and livestock industry can use it conveniently. In general, temperature and humidity are expressed in a line graph, etc., and the change is monitored in real time. The technology to visually express the temperature has recently been used intuitively by using an infrared device to test the fever of Corona 19. In this paper, the information collected from the Raspberry Pi and the DHT11 sensor is used to predict the temperature change in space through intuitive visualization and to make a immediate response. To this end, an algorithm was created to effectively visualize temperature and humidity, and data representation is possible even if some sensors are defective.

• Journal of Korean Tunnelling and Underground Space Association
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• v.24 no.2
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• pp.129-151
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• 2022

In the current work, a series of three-dimensional finite element analyses have been carried out to understand the behaviour of piles when the adjacent tunnelling passes underneath grouped piles with a reinforced pile cap. In the current study, the numerical analysis studied the computed results regarding the ground reinforcement condition between the tunnel and pile foundation. In addition, several key issues, such as the pile settlements, the axial pile forces, the shear stresses and the relative displacements have been thoroughly analysed, and the IoT platform based preliminary design guidelines were also presented. The pile head settlements of the nearest pile from the tunnel without the ground reinforcement increased by about 70% compared to the farthest pile from the tunnel with the maximum level of reinforcement. The quality management factor data of the piles were provided as API (Application Programming Interface) of various forms by the collection and refinement. Hence it has been shown that it would be important to provide the appropriate API by defining the each of data flow process when the data were created. The behaviour of the grouped piles with the pile cap, depending on the amount of ground reinforcement, has been extensively analysed, and the IoT platform regarding the quality management of piles has been suggested.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2022.06a
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• pp.93-96
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• 2022

IoT 기기의 보급 및 확산으로 많은 산업군에서 이를 바탕으로 시계열 데이터를 획득하고 분석하려는 시도가 확대되고 있다. 시간의 흐름에 따라 저장된 데이터들은 주기에 따라 특정 패턴을 갖는 경우가 많으며 이러한 패턴을 파악한다면 주요 산업군의 의사 결정에 도움이 된다. 그러나 IoT 기기의 수집 오류 및 네트워크 환경에 의해 대부분의 시계열 데이터들은 누락 데이터, 이상 데이터를 갖고 있으며 이를 처리하지 않고 분석할 경우 오히려 잘못된 결과를 초래한다. 본 논문에서는 패턴 파악을 위해 '시간, 일, 주, 월, 년' 등 시간의 주기를 기준으로 데이터를 분할하며 이에 기반하여 데이터셋을 재구성하고 활용 가능한 데이터와 불가능한 데이터로 구분한다. 선별된 데이터셋은 클러스터링에 적용하였으며, 제안하는 방법을 적용할 경우 주기를 갖는 시계열 데이터를 활용하는 분석 및 학습에서 더 나은 결과를 보임을 확인하였다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.12
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• pp.1942-1949
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• 2016

This paper proposed automatic path-tracing methods for Flying Disc Golf by adopting IoT comcepts at smart-marker. We tried to implement service system by making database. Smart-marker's configurations & roles are proposed. By making test-boards and adoption to various Flying Disc Golf games, the efficiency is proved. The positions and distances captured by the smart-marker are transferred to the smart-pole per each hole. The smart-pole captured them and transfers to web-server which is databased them. The result can be searched by web or smartphone in real time.