• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.4
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• pp.139-149
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• 2019

As of 2018, a large amount of Chinese fine dust is flowing into Korea in westerlies. However, the amount of fine dust generated in Korea can not be ignored. Even 52% of the causes of fine dust are domestic factors. Especially in Seoul, where the population is densely populated, the dust levels are high enough to be comparable to other regions. In Seoul, the dust levels are different from each other district. In order to understand the difference of fine dust generation by distinction, it is judged based on the highest traffic volume among the causes of fine dust generation in Seoul. Comparing the traffic volume and the fine dust concentration in 2017, it is possible to know the effect of traffic volume actually, how much it affects.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.1
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• pp.29-35
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• 2019

As the fourth industrial revolution is emerging, many companies are increasingly interested in smart factories and the importance of sensors is being emphasized. In the case that sensors for collecting sensing data fail, the plant could not be optimized and further it could not be operated properly, which may incur a financial loss. For this purpose, it is necessary to diagnose the status of sensors to prevent sensor' fault. In the paper, we propose a scheme to diagnose digital-sensor' fault by analyzing the rising time and falling time of digital sensors through the LSTM(Long Short Term Memory) of Deep Learning RNN algorithm. Experimental results of the proposed scheme are compared with those of rule-based fault diagnosis algorithm in terms of AUC(Area Under the Curve) of accuracy and ROC(Receiver Operating Characteristic) curve. Experimental results show that the proposed system has better and more stable performance than the rule-based fault diagnosis algorithm.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.1
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• pp.63-68
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• 2019

Emerging applications such as Smart factory, in-car network, wide area power network require strict bounds on the end-to-end network delays. Flow-based scheduler in traditional Integrated Services (IntServ) architecture could be possible solution, yet its complexity prohibits practical implementation. Sub-optimal class-based scheduler cannot provide guaranteed delay since the burst increases rapidly as nodes are passed by. Therefore a leaky-bucket type regulator placed next to the scheduler is being considered widely. This paper proposes a simple server that achieves both fair scheduling and traffic regulation at the same time. The performance of the proposed server is investigated, and it is shown that a few msec delay bound can be achieved even in large scale networks.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.1
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• pp.187-195
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• 2019

Recently, it has become possible to collect, store, process, and analyze data generated in various fields by the development of the technology related to the big data. These big data technologies are used for clinical results analysis and the optimization of clinical trial design will reduce the costs associated with health care. Therefore, in this paper, we are going to analyze clinical results and present guidelines that can reduce the period and cost of clinical trials. First, we use Sqoop to collect clinical results data from relational databases and store in HDFS, and use Hive, a processing tool based on Hadoop, to process data. Finally we use R, a big data analysis tool that is widely used in various fields such as public sector or business, to analyze associations.

• Industry Promotion Research
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• v.6 no.2
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• pp.47-53
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• 2021

This study is a study on the change of life and leisure satisfaction caused by the reduction of working hours of office workers, summarizing the results of the analysis as follows: First, the change in the working hours of office workers was found to be men (42.4 percent), but women (54.7 percent) had a high increase in personal satisfaction, monthly income of 2 to 3 million won 96.1 percent, and personal satisfaction increased in small and medium-sized cities and towns. Second, leisure satisfaction due to shorter working hours was somewhat high in monthly income of 3 million won to 4 million won (43.6%) and more than 6 million won (39.1%), but there was no change in leisure satisfaction by gender, age, academic background, number of family members, marital status, worker status and region. The revitalization of leisure is a very important task in personal life, but it is meaningful in that it provided implications for socializing leisure as leisure satisfaction is positively spreading in life changes.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.1
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• pp.75-80
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• 2021

Positioning technology is performing important functions in augmented reality, smart factory, and autonomous driving. Among the positioning techniques, the positioning method using beacons has been considered a challenging task due to the deviation of the RSSI value. In this study, the position of a moving object is predicted by training a neural network that takes the RSSI value of the receiver as an input and the distance as the target value. To do this, the measured distance versus RSSI was collected. A neural network was introduced to create synthetic data from the collected actual data. Based on this neural network, the RSSI value versus distance was predicted. The real value of RSSI was obtained as a neural network for generating synthetic data, and based on this value, the coordinates of the object were estimated by learning a neural network that tracks the location of a terminal in a virtual environment.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.3
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• pp.201-210
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• 2021

This paper introduces the futsal video analysis system consisting of an analysis program using object tracking technology and a web server that visualizes and provides analyzed data. In this paper, small and medium-sized organizations and amateur players are unable to provide game analysis services, so they propose a system that can solve this problem through this paper. Existing analytical systems use special devices or high-cost cameras, making them difficult for users to use. Thus, in this paper, a system is designed and developed to analyze the competitors' competitions and visualize the data using flat images only. Track an object and calculate the accumulated values to obtain the distance per pixel of the object and extract speed-related data and distance-based data based on it. Converts extracted data to graphs and images through a visualization library, making it convenient to use through web pages. Through this analysis system, we improve the problems of the existing analysis system and make data-based scientific and efficient analysis available.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.6
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• pp.192-207
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• 2020

In industrial fields like big factories, efficient management of resources is critical in terms of time and expense. So, inefficient management of resources leads to additional costs. Nevertheless, in many cases, there is no proper system to manage resources. This study proposes a system to manage and track large-scale resources efficiently. We attached Bluetooth 5.0-based beacons to our target resources to track them in real time, and by saving their transportation data we can understand flows of resources. Also, we applied a diagonal survey method to estimate the location of beacons so we are able to build an efficient and accurate system. As a result, We achieve 47% more accurate results than traditional trilateration method.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.4
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• pp.189-198
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• 2021

This paper introduces the ball tracking system using image processing. The recent growth of the amateur futsal market has also raised requests for an analysis of amateur players' performance. Sports game analysis services for feedback and growth to athletes or teams are provided in various ways in various sports fields. However, the cost and spatial constraints of sports analysis services make it difficult for providing analysis services to amateur athletes. In this paper, we study and develop a ball tracking algorithm for analyzing futsal game based on the match filming service previously provided in the amateur futsal field. This allows the analysis of the match based on existing services.

• KNOM Review
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• v.24 no.1
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• pp.13-19
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• 2021

In recent, there is research to maximize production by preventing failures/accidents in advance through fault diagnosis/prediction and factory automation in the industrial field. Cloud technology for accumulating a large amount of data, big data technology for data processing, and Artificial Intelligence(AI) technology for easy data analysis are promising candidate technologies for accomplishing this. Also, recently, due to the development of fault diagnosis/prediction, the equipment maintenance method is also developing from Time Based Maintenance(TBM), being a method of regularly maintaining equipment, to the TBM of combining Condition Based Maintenance(CBM), being a method of maintenance according to the condition of the equipment. For CBM-based maintenance, it is necessary to define and analyze the condition of the facility. Therefore, we propose a machine learning-based system and data model for diagnosing the fault in this paper. And based on this, we will present a case of predicting the fault occurrence in advance.