• The Journal of the Korea institute of electronic communication sciences
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• v.14 no.2
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• pp.317-322
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• 2019

This study is based on big big data base for real-time collection/analysis/processing of data, creative analysis of data assets, and intelligent processing system based on IoT, which can measure distribution phase in real time. The mobile terminal uses the SDK of the provided device to measure the data information on the consumption of specific seafood production and distribution. We use the oneM2M protocol to store various kinds of information needed for seafood production, and implement a DB Server and a system that allows the administrator to manage the system using the UI.

• Journal of Digital Convergence
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• v.17 no.12
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• pp.219-228
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• 2019

Thanks to the development of information technology and the vitalization of smart services, the Internet of Things (IoT) technology, in which various smart devices are connected to the network, has been continuously developed. In the legacy IoT architecture, data processing has been centralized based on cloud computing, but there are concerns about a single point of failure, end-to-end transmission delay, and security. To solve these problems, it is necessary to apply decentralized blockchain technology to the IoT. However, it is hard for the IoT devices with limited computing power to mine blocks, which consumes a great amount of computing resources. To overcome this difficulty, this paper proposes an IoT architecture based on the edge computing technology that can apply blockchain technology to IoT devices, which lack computing resources. This paper also presents an operaional procedure of blockchain in the edge computing-based IoT architecture.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.10a
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• pp.261-264
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• 2018

As the application of IoT has diversified, there is a growing need to store information of sensors on servers in real time. However, building servers and collecting data requires a lot of money to secure existing PCs and storage space. This paper presents an easy way to build a cloud system at a low cost. This system presents the process of simply proposing and implementing a cloud system using Raspberry which is open hardware and Node-Red which is open software.

• Journal of Internet of Things and Convergence
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• v.7 no.1
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• pp.9-19
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• 2021

The data mining design incorporated with big data based cloud computing system is investigated for the nuclear terrorism prevention where the conventional physical protection system (PPS) is modified. The networking of terror related bodies is modeled by simulation study for nuclear forensic incidents. It is needed for the government to detect the terrorism and any attempts to attack to innocent people without illegal tapping. Although the mathematical algorithm of the study can't give the exact result of the terror incident, the potential possibility could be obtained by the simulations. The result shows the shape oscillation by time. In addition, the integration of the frequency of each value can show the degree of the transitions of the results. The value increases to -2.61741 in 63.125th hour. So, the terror possibility is highest in later time.

• Convergence Security Journal
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• v.24 no.2
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• pp.31-38
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• 2024

Recent expansion in cloud service usage has heightened the importance of cloud security. The purpose of this study is to analyze current research trends in the field of cloud security and to derive implications. To this end, R&D project data provided by the National Science and Technology Knowledge Information Service (NTIS) from 2010 to 2023 was utilized to analyze trends in cloud security research. Fifteen core topics in cloud security research were identified using LDA topic modeling and ARIMA time series analysis. Key areas identified in the research include AI-powered security technologies, privacy and data security, and solving security issues in IoT environments. This highlights the need for research to address security threats that may arise due to the proliferation of cloud technologies and the digital transformation of infrastructure. Based on the derived topics, the field of cloud security was divided into four categories to define a technology reference model, which was improved through expert interviews. This study is expected to guide the future direction of cloud security development and provide important guidelines for future research and investment in academia and industry.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.533-535
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• 2021

The differences between this study and previous studies are as follows. First, by building a cloud-based system using IoT technology, the system was built to monitor the status of buildings in real time from anywhere with an internet connection. Second, a model for predicting the future was developed using artificial intelligence (LSTM) and statistical (ARIMA) methods for the measured time series sensor data, and the effectiveness of the proposed prediction model was experimentally verified using a scaled-down building model. Third, a method to analyze the condition of a building more three-dimensionally by visualizing the structural deformation of a building by convergence of multiple sensor data was proposed, and the effectiveness of the proposed method was demonstrated through the case of an actual earthquake-damaged building.

• Journal of Internet of Things and Convergence
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• v.10 no.1
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• pp.53-58
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• 2024

IoT, Big-data, AI, and Cloud technologies, which are core technologies of the 4th Industrial Revolution, have recently been applied to various fields and are being used as core technologies for new growth engines. Accordingly, these core technologies are applied to the agricultural field without exception, contributing to solving the problem of labor shortage, reducing production costs, and reducing environmental burden through remote and automated production without time and space constraints. However, as these core technologies are utilized, security incidents are occurring in the agricultural field as well. Accordingly, this study divides smart farms into three stages(Basic, Middle, and High) and presents the characteristics and security threats of each stage. In particular, as the number of container-based services and research increases under cloud platforms, we would like to suggest countermeasures focusing on security threats.

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.1
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• pp.147-152
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• 2018

This study investigates the demand management and energy saving plan of the apartment house based on the ESS (: Energy Storage System), which is the main equipment in the field of electric power energy efficiency, and suggests standardization for various technical factors and operation. It contributes to the spread of ESS industry. In addition, to create ESS market for apartment houses and smart homes, housing IoT technology is used to integrate apartment houses with smart home-based ESS and it is possible to achieve use efficiency and economic feasibility of power users, We will study a business model that can reconsider the acceptability of power users.

• IEMEK Journal of Embedded Systems and Applications
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• v.18 no.4
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• pp.159-164
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• 2023

Solar energy harvesting IoT devices prioritize maximizing the utilization of collected energy due to the periodic recharging nature of solar energy, rather than minimizing energy consumption. Meanwhile, research on edge AI, which performs machine learning near the data source instead of the cloud, is actively conducted for reasons such as data confidentiality and privacy, response time, and cost. One such research area involves performing various audio AI applications using audio data collected from multiple IoT devices in an IoT edge computing environment. However, in most studies, IoT devices only perform sensing data transmission to the edge server, and all processes, including data preprocessing, are performed on the edge server. In this case, it not only leads to overload issues on the edge server but also causes network congestion by transmitting unnecessary data for learning. On the other way, if data preprocessing is delegated to each IoT device to address this issue, it leads to another problem of increased blackout time due to energy shortages in the devices. In this paper, we aim to alleviate the problem of increased blackout time in devices while mitigating issues in server-centric edge AI environments by determining where the data preprocessed based on the energy state of each IoT device. In the proposed method, IoT devices only perform the preprocessing process, which includes sound discrimination and noise removal, and transmit to the server if there is more energy available than the energy threshold required for the basic operation of the device.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.10a
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• pp.716-717
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• 2017

In this paper, we propose a modeling approach for marine environment monitoring by leveraging open-source software to link IoT and Cloud together. The proposed model can be scale out by employing Apache Hadoop-based time-series database so that it can handle collected data increase with a resource pool of the same computers. It can also support the analyze monitored data of marine environment by visualizing collected data.