• Journal of Digital Convergence
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• v.15 no.3
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• pp.65-75
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• 2017

Agricultural sector in Korea faces the threat of aging farmers and many other difficulties. Because agriculture is a very less-competitive industry in Korea and many solutions to improve the competitiveness of Korean agriculture should be studied. The advent of Internet of things(IoT) technology makes possible many new industries and business models in the current society. The adoption of this new technology in agriculture can bring about innovations in agricultural production and distribution as $6^{th}$ industry. This paper summarizes the opportunities in IoT and smart farm. The major benefits and obstacles in introducing smart farms are reviewed and the cases of two successful smart farms in Korea are analyzed. Through these case studies, we can recognize the current status and future strategies in Korean smart farms.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.05a
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• pp.664-665
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• 2016

This paper proposes an identification system based on QR (Quick Response) code for production and disposal information of Internet of Things (IoT) devices. Three thousands and five hundreds of electronic devices have replaced and discarded in South Korea in a year, and twenty millions to fifty millions tons of e-wastes have happened throughout the world every year. According to Gartner, market research institution, the number of IoT devices will increase from 2.3 billions in 2013 to 30 billions in 2020, however, the regulations and systems which take into account environment were not prepared. The identification systems for reflecting information of devices, which are produced or discarded, are required to resolve the problem. The proposed identification system based on QR code can store much more massive data such as the producer, product's model, serial number, recycling rate, recovering rate, recyclability rate, recoverability rate than RFID (Radio-Frequency Identification). Also, users can immediately recognize production and disposal information by a QR code application in a smartphone.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.9
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• pp.1382-1391
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• 2022

White-box cryptography can respond to white-box attacks that can access and modify memory by safely hiding keys in the lookup table. However, because the size of lookup tables is large and the speed of encryption is slow, it is difficult to apply them to devices that require real-time while having limited resources, such as IoT(Internet of Things) devices. In this work, we propose a scheme for collecting short-length plaintexts and processing them at once, utilizing the characteristics that white-box ciphers process encryption on a lookup table size basis. As a result of comparing the proposed method, assuming that the table sizes of the Chow and XiaoLai schemes were 720KB(Kilobytes) and 18,000KB, respectively, memory usage reduced by about 29.9% and 1.24% on average in the Chow and XiaoLai schemes. The latency was decreased by about 3.36% and about 2.6% on average in the Chow and XiaoLai schemes, respectively, at a Traffic Load Rate of 15 Mbps(Mega bit per second) or higher.

• Journal of Internet of Things and Convergence
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• v.9 no.6
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• pp.37-44
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• 2023

As a primary technology of Industry 4.0, human-robot collaboration (HRC) requires additional measures to ensure worker safety. Previous studies on avoiding collisions between collaborative robots and workers mainly detect collisions based on sensors and cameras attached to the robot. This method requires complex algorithms to continuously track robots, people, and objects and has the disadvantage of not being able to respond quickly to changes in the work environment. The present study was conducted to implement a web-based platform that manages collaborative robots by recognizing the emotions of workers - specifically their perception of danger - in the collaborative process. To this end, we developed a web-based application that collects and stores emotion-related brain waves via a wearable device; a deep-learning model that extracts and classifies the characteristics of neutral, positive, and negative emotions; and an Internet-of-things (IoT) interface program that controls motor operation according to classified emotions. We conducted a comparative analysis of our system's performance using a public open dataset and a dataset collected through actual measurement, achieving validation accuracies of 96.8% and 70.7%, respectively.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.5
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• pp.1003-1008
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• 2017

The Internet of Things has attracted considerable research attention in recent years. In order for the new IoT technology to be widely used, the reliability and protection of information is required. IoT systems are very vulnerable to physical security due to their easy accessibility. Along with the development of SoC technology, many operating systems have been developed and many new operating systems have been introduced. In this paper, we describe the vulnerability analysis results for operating systems running on the ARMv7 Thumb Architecture hardware platform. For the recently introduced "Windows 10 IoT Core" operating system, I implemented the Zero-Day Attack by implanting the penetration code developed through the research into a specific IoT system. The virus detection test for the resulting penetration code was validated by referral to the "virustotal" site.

• Journal of Internet of Things and Convergence
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• v.8 no.6
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• pp.15-20
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• 2022

This study is about the development of a device that reduces bacterial diffusion and odor by improving the water quality of the toilet using ozone water. In public toilets used by an unspecified number of people, various pollutants and pathogens are present in the toilet. These substances that are harmful to the human are dispersed in the form of aerosols into the air through toilet flushing. Aerosols containing various contaminants may flow into the user's respiratory tract or spread to the skin and cover, serving as a medium for various diseases. In order to prevent this spread, it is essential to continuously maintain cleanliness inside the toilet. Therefore, in this study, ozone water that can improve the water quality of the toilet was used as a way to keep the toilet environment clean. A device that is mounted in a toilet tank and continuously generates ozone water to improve pollutants inside the toilet was designed and developed.

• Journal of Internet of Things and Convergence
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• v.6 no.1
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• pp.1-8
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• 2020

Following the advanced fuel cycle initiative (AFCI) promotions in the United States, the analytic proposition for global fuel cycle initiative (GFCI) has been investigated using dynamical simulations. The political and economic aspects are considered simultaneously due to the particular characteristics of the nuclear materials. The spent nuclear fuels (SNFs) are treated as the reprocessing by the nuclear non-proliferation treaty (NPT) exemption nations and the NPT excluded nations. Otherwise, the pyroprocessing and repository can be done without NPT restriction. In addition, the international trade is considered as the economic aspect where the energy production is a key issue of the GFCI. The dynamical simulations have been done until 2050. The result of the International Trade shows the gradually increasing shape. Additionally, the Nuclear Power Plant Operation shows the increasing by stepwise shape.

• Membrane and Water Treatment
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• v.14 no.4
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• pp.155-162
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• 2023

Global climate change and urbanization have various demerits, such as water pollution, flood damage, and deterioration of water circulation. Thus, attention is drawn to Nature-based Solution (NbS) that solve environmental problems in ways that imitate nature. Among the NbS, urban wetlands are facilities that perform functions, such as removing pollutants from a city, improving water circulation, and providing ecological habitats, by strengthening original natural wetland pillars. Frequent monitoring and maintenance are essential for urban wetlands to maintain their performance; therefore, there is a need to apply the Internet of Things (IoT) technology to wetland monitoring. Therefore, in this study, we attempted to develop a real-time wetland monitoring device and interface. Temperature, water temperature, humidity, soil humidity, PM1, PM2.5, and PM10 were measured, and the measurements were taken at 10-minute intervals for three days in both indoor and wetland. Sensors suitable for conditions that needed to be measured and an Arduino MEGA 2560 were connected to enable sensing, and communication modules were connected to transmit data to real-time databases. The transmitted data were displayed on a developed web page. The data measured to verify the monitoring device were compared with data from the Korea meteorological administration and the Korea environment corporation, and the output and upward or downward trend were similar. Moreover, findings from a related patent search indicated that there are a minimal number of instances where information and communication technology (ICT) has been applied in wetland contexts. Hence, it is essential to consider further research, development, and implementation of ICT to address this gap. The results of this study could be the basis for time-series data analysis research using automation, machine learning, or deep learning in urban wetland maintenance.

• Journal of Korea Multimedia Society
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• v.18 no.9
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• pp.1091-1097
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• 2015

Internet-of-Things (IoT) becomes one of the most promising future paradigms, which foresees enormous amounts of interoperable things and heterogeneous services. The goal of IoT is to enable all things connected and brings all kinds information and services to people. However, such a great deal of information may lead to cognitive overload or restrain in productivity of people. Thus, it is a necessity to build intelligent mechanisms to assist people in accessing the information or services they needed in a proactive manner. Most of previous related mechanisms are built on well-defined web services and lack of consideration of constrained resources. This paper suggests a services composition method by adapting a hierarchical model, which is a graph-based model composed of four layers: Context Layer, Event Layer, Service Layer and Device Layer. With a such multi-layer graph, service composition can be achieved by the iteration of layer by layer. Then, to evaluate the effectiveness of this proposed hierarchical model, a real-life emergency response dataset is applied and the experimental results are composed with the general probabilistic method and indicate that the proposed method is help for compositing multiple services while considering given context and constrained resources.

• Journal of Convergence for Information Technology
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• v.7 no.1
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• pp.55-60
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• 2017

In order to provide intelligent services without human intervention in the Internet of Things environment, it is necessary to analyze the big data generated by the IoT device and learn the normal pattern, and to predict the abnormal symptoms such as faulty or malfunction based on the learned normal pattern. The purpose of this study is to implement a machine learning model that can predict product failure by analyzing big data generated in various devices of product process. The machine learning model uses the big data analysis tool R because it needs to analyze based on existing data with a large volume. The data collected in the product process include the information about product faulty, so supervised learning model is used. As a result of the study, I classify the variables and variable conditions affecting the product failure, and proposed a prediction model for the product failure based on the decision tree. In addition, the predictive power of the model was significantly higher in the conformity and performance evaluation analysis of the model using the ROC curve.