• Journal of the Korean Society of Food Science and Nutrition
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• v.44 no.6
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• pp.904-911
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• 2015

The objective of this study was to investigate the quality characteristics of traditional wine using an radio-frequency identification (RFID) system annexed to a fermenter. In this study, we proposed an RFID-based data transmission scheme for monitoring fermentation of traditional alcoholic beverages. The pH, total acidity, total sugar, soluble sugar, free sugar, alcohol content, and organic acids of were investigated and subjected to fermentation of traditional alcoholic beverages three times. The pH ranged from 7.98, 7.95, and 7.68 at day 0, decreased drastically to 3.31~2.96 at day 2, and then slowly increased to the end point, finally reaching 3.34 at day 20. Acidity tended to increase quickly with time, especially for all samples after day 2. The fermentation environment induced a sudden increase acidity in reactants and indicated a low pH. The total sugars during fermentation quickly decreased to the range of 20.3, 22.43, and 19.2% at day 2, and the slope of reduction steadily decreased to 5.1, 6.1, and 4.8% at day 10. On the other hand, the alcohol content showed the reverse trend as total sugars. The alcohol content also showed the same pattern as total acids, showing the highest alcohol content of 17.3% (v/v) on day 20. In this study on traditional wine fermentation using an RFID system, we showed that pH, soluble sugar, and alcohol content can be adopted as key indicators for quality control and standardization of traditional wine manufacturing.

• Fire Science and Engineering
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• v.31 no.1
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• pp.58-62
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• 2017

There is a growing need for seismic resistance design. But it is controversial that standards of sway brace device in non-structural elements for buildings like pump waterway is vary widely. Therefore, in this study to get a valid range of sway brace device in seismic resistance design, using load test of sway brace device. As a result, load of safe range from 0 to 18.5 kN and under 29.4 kN, no structural fault of sway brace device. And using internet of things get a data of seismic resistance design from sensor node like accelerometer, GPS, tilt sensor and temperature sensor through steps of sampling and prediction. These results will be acceptable for monitoring system for seismic resistance in non-structural elements.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.11
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• pp.2167-2175
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• 2017

In recent years, an IoT is dramatically developing according to the enhancement of AI, the increase of connected devices, and the high-performance cloud systems. Huge data produced by many devices and sensors is expanding the scope of services, such as an intelligent diagnostics, a recommendation service, as well as a smart monitoring service. The studies of edge computing are limited as a role of small server system with high quality HW resources. However, there are specialized requirements in a smart factory domain needed edge computing. The edges are needed to pre-process containing tiny filtering, pre-formatting, as well as merging of group contexts and manage the regional rules. So, in this paper, we extract the features and requirements in a scope of efficiency and robustness. Our edge offers to decrease a network resource consumption and update rules and learning models. Moreover, we propose architecture of edge computing based on learning factors sharing with a cloud system in a smart factory.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.42 no.4
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• pp.203-210
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• 2019

Recently, a number of researchers have produced research and reports in order to forecast more exactly air quality such as particulate matter and odor. However, such research mainly focuses on the atmospheric diffusion models that have been used for the air quality prediction in environmental engineering area. Even though it has various merits, it has some limitation in that it uses very limited spatial attributes such as geographical attributes. Thus, we propose the new approach to forecast an air quality using a deep learning based ensemble model combining temporal and spatial predictor. The temporal predictor employs the RNN LSTM and the spatial predictor is based on the geographically weighted regression model. The ensemble model also uses the RNN LSTM that combines two models with stacking structure. The ensemble model is capable of inferring the air quality of the areas without air quality monitoring station, and even forecasting future air quality. We installed the IoT sensors measuring PM2.5, PM10, H2S, NH3, VOC at the 8 stations in Jeonju in order to gather air quality data. The numerical results showed that our new model has very exact prediction capability with comparison to the real measured data. It implies that the spatial attributes should be considered to more exact air quality prediction.

• Journal of the Korea Society of Computer and Information
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• v.25 no.7
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• pp.143-150
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• 2020

Recently, many companies are interested in smart factory services. Because various smart factory services are provided by the combination of mobile devices, cloud computing, and IoT services. However, many workers turn away from these systems because most of them are not implemented from the worker's point of view. To solve this, we implemented a development tool that allows field workers to produce their own services so that workers can easily create smart factory services. Manufacturing data is collected in real time from sensors which are connected to manufacturing facilities and stored within smart factory platforms. Implemented development tools can produce services such as monitoring, processing, analysis, and control of manufacturing data in drag-and-drop. The implemented system is effective for small manufacturing companies because of their environment: making various services quickly according to the company's purpose. In addition, it is assumed that this also will help workers' improve operation skills on running smart factories and fostering smart factory capable personnel.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.15 no.6
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• pp.83-88
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• 2016

Over the last five years, 568 people have died while hiking according to 2015 statistics from the public safety ministry. Among those deaths, approximately 33% were due to loss of footing or falling. In this respect, the highly advanced functions of hiking boots should be considered to prevent these unfortunate accidents. For example, by utilizing the Internet of Things (IoT) and Information and Communications Technology (ICT), hiking boots equipped with a Global Positioning System (GPS) or vital signs monitoring systems should be considered. In addition, many challenges remain for the production of 3D printed hiking boots, because the functions of hiking boots are variable, which is important when handling changing terrains and situations. The design of customized hiking boots was introduced in this paper, and 3D printing applications for midsoles using a Porous Polymer Printing (PPP) method was also suggested to verify the possibility of manufacturing hiking boots.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.17 no.5
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• pp.231-237
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• 2017

This paper presents an implementation of a smart flowerpot which can adjust humidity and illumination automatically after monitoring the temperature, humidity, and illumination. We made a container of the flowerpot with a 3D printer and embedded a NodeMCU micro controller in it. We attached a temperature sensor, a humidity sensor, an illumination sensor, and a water pump to the NodeMCU. We developed a control program that adjusts humidity and illumination and ran it on the NodeMCU. Also we developed an Android application and set up an MQTT server. Using the MQTT server, the NodeMCU and the Android application can exchange messages which keep sensor values and commands. Using the Android application. the user can send the proper temperature, humidity, and illumination to the smart flowerpot and monitor the sensor values.

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.1
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• pp.45-52
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• 2018

In this paper, we propose smart digital door lock system using heterogeneous communication. This system has efficient function using RF communication and Internet communication, and realizes access and real image of the passengers by combining camera control technology to secure original competitiveness with existing products. It uses the Internet of things and receive images to and from your smart-phone. And senses human behavior. In the simulated results, the image transmission rate of 90 % or more and the time required to transmit 10,000 images have an average transmission speed of 3 seconds. It is expected to secure competitiveness to increase the security of door lock in the future by enabling minimum security and fire monitoring service in real time.

• Journal of the Korea Convergence Society
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• v.10 no.11
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• pp.47-53
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• 2019

Safety accidents at industrial sites can occur anytime, anywhere. Recently, research on the industrial safety management system based on the IoT has been actively conducted. However, most of the studies are studies of actions after safety accidents or simply monitoring. In this paper, the safety equipment was introduced before safety accidents occurred, and the subjects could be managed not only by workers but also by visitors. Also, it implements a system to prevent the accident by detecting the user's motion and situation periodically before a safety accident occurs. The implemented system is a system that attaches the device for safety management to the hard hat and can identify the safety situation by using the Bluetooth beacon device attached to the user's smartphone and the industrial site.

• Journal of the Korean Association of Geographic Information Studies
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• v.22 no.2
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• pp.97-106
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• 2019

Today, many smart sensor's measurement instruments are used to check the safety situation of various medium and large bridge structures that should be maintained in the construction facilities, but most of them use the method of measuring and confirming the displacement behavior of the bridge at regular intervals. In order to continuously check the safety situation, various measuring instruments are used, but most of them are not able to measure and measure the displacement and behavior of main construction structures at regular intervals. In this study, GNSS and environment smart sensors and drone's image data are transmitted to wireless network so that risk of many bridge's structures can be detected beforehand. As a result, by diagnosing the fine displacement of the bridge in real time and its condition, reinforcement, repair and disaster prevention measures for the structural parts of the bridges, which are expected to be dangerous, and various disasters and accidents can be prevented, and disaster can be prevented could suggest a new alternative.