• Journal of the Korean Society of Manufacturing Process Engineers
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• v.21 no.4
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• pp.46-52
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• 2022

In the existing wired communication network, wired communication is frequently interrupted by lightning, which accompanies rain, and remote management cannot be performed when it is actually necessary. In the case of communication interruption, field data stored in the database are lost, and data at an important point in time may go missing; this causes a decrease in the reliability of the stored data. Therefore, in this study, wireless communication using the Internet of Things (IoT) communication network of the 4^th industrial technology is installed in the prototype to reduce wired communication construction costs, prevent resource waste and environmental damage due to communication facility construction, and prepare for communication loss.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.42 no.1
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• pp.21-32
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• 2019

The flow of the $4^{th}$ Industrial Revolution calls for the innovation of the traditional business models of the manufacturers. Servitization is a corporate strategy to respond to changes in the business environment. These days, the value that the market demands can be created on the basis of the product-service integration. Thus the manufacturers must pursue the fundamental innovation of the current strategy and business models. It is necessary to create common values with customers through providing product-service integrated offerings beyond the development, production, and delivery. The purpose of this study is to develop the evaluation indicators for selecting suppliers when the manufacturer who offers the value of product-service integration needs to obtain the resources from outside. The case company in this study is the manufacture firm conducting the retail IoT business as a new business. The Delphi method is used to develop the evaluation indicators for selecting suppliers. This study suggests the academic implications providing the perspective of Servitizaiton by using Delphi method, and the practical implications applying the creating value method of Servitization by collecting the opinions from both value providers and value consumers in the process of developing the evaluation indicators.

• Journal of Internet of Things and Convergence
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• v.6 no.4
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• pp.33-38
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• 2020

It was reported that a mobile application was designed to easily provide natural dyeing information such as natural dye related resources, colors and dyed fabrics in 2007. Since studies on the linkage, application, etc. between natural dye dyeing and IoT are still lacking, diversity of information on the change of dyeing pattern by natural dye dyeing is required. In this study, it was to construct dyeing information by natural dyes, e.g., Lithospermum erythrorhizon, on silk, which has been traditionally used as many fibers in Korea. The extraction of the dye from L. erythrorhizon was carried out under pH4. The dried root of L. erythrorhizon showed dark brownish purple. Silk fabric by a without a mordant typically showed a purple dyed pattern. In the staining by sodium tartrate plus citric acid, silk fabric was stained clear brown. Interestingly, the mordant of iron (II) sulfate, the silk fabric was dyed in a light gray color rather than black. When the mordant of aluminum potassium sulfate was treated with L. erythrorhizon-extracted dye, the results were almost the same as when the mordant was not treated. When the degree of dyeing was evaluated numerically, the treatment of the mordant of potassium dichromate was about 50% darker, and the dyeing by iron (II) sulfate was about 75% darker. These results will be helpful in the study of applying various dye colors using L. erythrorhizon, and it will provide information on dyeing controller and database system construction by dyeing parameters such as dyeing degree, pH concentration, and chromaticity change.

• Journal of the Korean Society of Safety
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• v.32 no.1
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• pp.21-26
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• 2017

An IoT-based particulate matter (PM2.5) sensing device (PSD) is developed. The PSD consists of a PM2.5 sensor, signal processing circuit, and wi-fi enabled-microprocessor along with temperature and humidity sensors. The PSD estimates PM2.5 density by measuring light scattered by PM2.5. To gauge performance of the PSD, PM2.5 density of open air was measured with the PSD and compared with that of the collocated-government-certified measuring station. Measurements were taken at a sampling frequency of 100 Hz and moving-averaged to remove measurement noise. When compared to the result of the measuring station, average percentile error of PM2.5 density from the PSD is found to be 31%. A correlation coefficient is found to be 0.72 which indicates a strong correlation. Instantaneous variation, however, may far exceed average errors, leading to a conclusion that the PSD is more suitable for estimating average trend of PM2.5 density variations than estimating instantaneous PM2.5 density.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.36 no.3
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• pp.177-184
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• 2018

In case that limited resources can be mobilized, non-structural countermeasures such as 'monitoring using Information and Communication Technology might be one of solutions to mitigate disaster risks. Having established the monitoring system, operational and maintenance costs to maximize the effectiveness might trouble the authority concerned or duty attendant who is in charge. In this respect, "Guerrilla Sensor" would be very cost effective because of the inherent mobility characteristic. The sensor device with the IRIS camera and GPS (Global Positioning System) equipped, is basically battery-operated and communicates with WCDMA (Wideband Code Division Multiple Access). It has a strong advantage of capabilities for 'Disaster Response' with immediate and prompt action on the spot, making the best use of IoT (Internet of Things), especially with the mobile web. This paper will explain how the sensor system works in real-time GIS (Geographic Information System) pinpointing the exact location of the abnormal movement/ground displacement and notifying the registered users via SMS (Short Message Service). Real time monitoring with early warning and evaluation of current situations with LBS (Location Based Service), live image and data information can help to reduce the disaster impact. Installation of Guerrilla sensor for a real site application at Gimcheon, South Korea is also reported.

• International Journal of Computer Science & Network Security
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• v.21 no.3
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• pp.212-218
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• 2021

Low-power and Lossy Networks (LLNs) have become the common network infrastructure for a wide scope of Internet of Things (IoT) applications. For efficient routing in LLNs, IETF provides a standard solution, namely the IPv6 Routing Protocol for LLNs (RPL). It enables effective interconnectivity with IP networks and flexibly can meet the different application requirements of IoT deployments. However, it still suffers from different open issues, particularly in large-scale setups. These include the node unreachability problem which leads to increasing routing losses at RPL sink nodes. It is a result of the event of memory overflow at LLNs devices due to their limited hardware capabilities. Although this can be alleviated by the establishment of multi-sink topologies, RPL still lacks the support for effective load balancing among multiple sinks. In this paper, we address the need for an efficient multi-sink load balancing solution to enhance the performance of PRL in large-scale scenarios and alleviate the node unreachability problem. We propose a new RPL objective function, Multi-Sink Load Balancing Objective Function (MSLBOF), and introduce the Memory Utilization metrics. MSLBOF enables each RPL node to perform optimal sink selection in a way that insure better memory utilization and effective load balancing. Evaluation results demonstrate the efficiency of MSLBOF in decreasing packet loss and enhancing network stability, compared to MRHOF in standard RPL.

• Journal of Information Processing Systems
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• v.18 no.1
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• pp.115-129
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• 2022

Adopting Internet of Things (IoT)-based technologies in smart homes helps users analyze home appliances electricity consumption for better overall cost monitoring. The IoT application like smart home system (SHS) could suffer from large missing values gaps due to several factors such as security attacks, sensor faults, or connection errors. In this paper, a novel framework has been proposed to predict large gaps of missing values from the SHS home appliances electricity consumption time-series datasets. The framework follows a series of steps to detect, predict and reconstruct the input time-series datasets of missing values. A hybrid convolutional neural network-long short term memory (CNN-LSTM) neural network used to forecast large missing values gaps. A comparative experiment has been conducted to evaluate the performance of hybrid CNN-LSTM with its single variant CNN and LSTM in forecasting missing values. The experimental results indicate a performance superiority of the CNN-LSTM model over the single CNN and LSTM neural networks.

• Journal of Information Processing Systems
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• v.17 no.5
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• pp.905-917
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• 2021

In recent years, edge computing technology consists of several Internet of Things (IoT) devices with embedded sensors that have improved significantly for monitoring, detection, and management in an environment where big data is commercialized. The main focus of edge computing is data optimization or task offloading due to data and task-intensive application development. However, existing offloading approaches do not consider correlations and associations between data and tasks involving edge computing. The extent of collaborative offloading segmented without considering the interaction between data and task can lead to data loss and delays when moving from edge to edge. This article proposes a range segmentation of dynamic offloading (RSDO) algorithm that isolates the offload range and collaborative edge node around the edge node function to address the offloading issue.The RSDO algorithm groups highly correlated data and tasks according to the cause of the overload and dynamically distributes offloading ranges according to the state of cooperating nodes. The segmentation improves the overall performance of edge nodes, balances edge computing, and solves data loss and average latency.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.10
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• pp.1249-1254
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• 2020

As the market for life friendly ICT (Information and Communication Technologies) services has grown up, high tech elevator with IoT (Internet of Things), a key area of the fourth industry, have become an indispensable part of life. Existing elevators are composed of up and down buttons to conveniently climb up and down high rise buildings, but there is a small inconvenience that everyone experiences depending on the characteristics of the user's composition, types of use, frequency, etc. Existing elevators are automatically closed if there are no people within the range of sensors, but they are inconvenient for the passengers with disabilities to carry luggage or to use. In this paper, the smart button, a hardware firmware device, was designed to relieve user inconvenience by opening the elevator for a certain period of time considering the boarding time of the passengers.

• Korean Journal of Agricultural Science
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• v.49 no.1
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• pp.31-43
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• 2022

The global trade environment is rapidly changing. The spread of COVID-19 promotes digitalization, and online transactions are becoming the new normal. Currently, Korea is actively introducing information and communication technology (ICT) that uses the internet of things (IoT) in relation to agriculture. However, few studies have analyzed the impact of digitalization on trade in the agricultural sector. Thus, the purpose of this study is to examine how the introduction of digital technology can affect the economy and trade of Korea. In this study, we estimate the impact of introducing digital technologies using the computable general equilibrium (CGE) model. The results of this analysis indicate that the GDP could increase by 3.82% to 10.53%. Also, agricultural production and trade according to the model will significantly increase to 8.67% and 5.72%, respectively, through a productivity increase from Blockchain, IoT, and artificial intelligence (AI) technologies, despite logistics inefficiencies. Although the effects of digitalization could be significant, farmers are still struggling to introduce digital technologies, stemming from the fact that government support systems are concentrated in only a few sub-sectors. In this regard, support in this area must be expanded and diversified according to the current environment of agriculture in Korea.