• The Journal of the Korea Contents Association
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• v.22 no.5
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• pp.247-260
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• 2022

This paper investigates plans to expand distribution channels for books by installing a book vending machine at convenience stories for the vitalization of the publishing culture and industry. After establishing the meaning of convenience stories and the concept of a book vending machine, the researcher identified a need for the installation and management of a book vending machine at convenience stories. This plan will promote fairness and transparency in book sales through the convenience store system and push forward outsourcing between the publishing industry and the convenience store industry, the expansion of omnichannel service for consumers, and experiential values for clients to increase their customer satisfaction. The composition of the book vending machine will take the smart library form for its management with a universal design applied to a kiosk program. In the study, the researcher schematized this process and conducted a survey with 310 adults to search for practical management plans for a book vending machine. In the future, more research on the diversification of sales and distribution channels for publications such as the installation of a book vending machine at convenience stores will hopefully contribute to the growing amount of reading per capita and promotion of a reading environment for people according to the vitalization of the publishing culture and industry.

• Journal of the Microelectronics and Packaging Society
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• v.25 no.1
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• pp.23-28
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• 2018

Under the 4th Industrial Revolution, implementation of Smart Factory in the field of surface mounting is an emerging issue. In the field of surface mounting, many researches are going on in line with these changes. Among them, we analyzed the method of optimizing the solder printing process which is a core process and the influence of the external factors affecting the printing efficiency. In this analysis, the Big Data provided by the SPI Machine was used to approach the statistical method, and the possibility of predicting the result through simulation with reliable results was confirmed. I hope this study contributes a little to the Smart Factory implementation.

• The Journal of the Korea institute of electronic communication sciences
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• v.9 no.3
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• pp.351-358
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• 2014

In this study, we are a proposed system that could control a multi-functional welder of the current, voltage of the crater, gas control, the wire feeder's driven, the constant voltage output control, high frequency control, rated current control and the ARC welding control etc., using the mobile-based smart phone. Approximately 90% of user of proposed system are very useful in multi-function welder in their task responded and rest of 10% of the answers don't need it. 30% answered in 90% of the multi-function welding machine according to age group using a smart phone utilizing this "very difficult" at investigated. However, the use of smart phones is gradually lower the user's age group can be seen that effective.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2007.05a
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• pp.448-452
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• 2007

Many industrial operations require continuous or nearly-continuous operation of machines, which if interrupted can result in significant financial loss. The condition monitoring of these machines has received considerable attention recent years. Rapid developments in semiconductor, computing, and communication with a remote site have led to a new generation of sensor called "smart" sensors which are capable of wireless communication with a remote site. The purpose of this research is the development of smart sensor using which can on-line perform condition monitoring. This system is addressed to detect conditions that may lead to equipment failure when it is running. Moreover it will reduce condition monitoring expense using low cost MEMS accelerometer. This sensor can receive data in real-time or periodic time from MEMS accelerometer. Furthermore, this system is capable for signal preprocessing task (High Pass Filter, Low Pass Filter and Gain Amplifier) and analog to digital converter (A/D) which is controlled by CPU. A/D converter that converts 10bit digital data is used. This sensor communicates with a remote site PC using TCP/IP protocols. Wireless LAN contain IEEE 802.11i-PSK or WPA (PSK, TKIP) encryption. Developed sensor executes performance tests for data acquisition accuracy estimations.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.5
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• pp.1967-1983
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• 2020

The goal of this paper is to analyze and build an algorithm to recognize hand gestures applying to smart home applications. The proposed algorithm uses image processing techniques combing with artificial neural network (ANN) approaches to help users interact with computers by common gestures. We use five types of gestures, namely those for Stop, Forward, Backward, Turn Left, and Turn Right. Users will control devices through a camera connected to computers. The algorithm will analyze gestures and take actions to perform appropriate action according to users requests via their gestures. The results show that the average accuracy of proposal algorithm is 92.6 percent for images and more than 91 percent for video, which both satisfy performance requirements for real-world application, specifically for smart home services. The processing time is approximately 0.098 second with 10 frames/sec datasets. However, accuracy rate still depends on the number of training images (video) and their resolution.

• International Journal of Internet, Broadcasting and Communication
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• v.13 no.4
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• pp.121-128
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• 2021

In order to design a real time big data collection and analysis system of manufacturing data in a smart factory, it is important to establish an appropriate wired/wireless communication system and protocol. This paper introduces the latest communication protocol, OPC-UA (Open Platform Communication Unified Architecture) based client/server function, applied user interface technology to configure a network for real-time data collection through IoT Integration. Then, Database is designed in MES (Manufacturing Execution System) based on the analysis table that reflects the user's requirements among the data extracted from the new cutting process automation process, bush inner diameter indentation measurement system and tool monitoring/inspection system. In summary, big data analysis system introduced in this paper performs SPC (statistical Process Control) analysis and visualization analysis with interface of OPC-UA-based wired/wireless communication. Through AI learning modeling with XGBoost (eXtream Gradient Boosting) and LR (Linear Regression) algorithm, quality and visualization analysis is carried out the storage and connection to the cloud.

• Journal of Korea Multimedia Society
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• v.23 no.12
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• pp.1519-1530
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• 2020

As livestock farms grow in size, the number of breeding individuals increases, making it difficult to manage livestock. Livestock farms require an integrated management system such as a monitoring system, an access control system, and an abnormal behavior detection system to manage livestock houses. In this paper, a smart korean cattle livestock management system using IoT and AI technology was proposed for livestock management in livestock farms. The smart korean cattle farm management system consists of a monitoring and control system, a vehicle access management system, and an abnormal cattle behavior detection system. It is expected that this will help manage large-scale livestock houses, and additional research is needed to improve the performance of abnormal behavior detection in the future.

• Journal of Korean Association for Spatial Structures
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• v.22 no.2
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• pp.19-27
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• 2022

Visual inspection methods have limitations, such as reflecting the subjective opinions of workers. Moreover, additional equipment is required when inspecting the high-rise buildings because the height is limited during the inspection. Various methods have been studied to detect concrete cracks due to the disadvantage of existing visual inspection. In this study, a crack detection technology was proposed, and the technology was objectively and accurately through AI. In this study, an efficient method was proposed that automatically detects concrete cracks by using a Convolutional Neural Network(CNN) with the Orthomosaic image, modeled with the help of UAV. The concrete cracks were predicted by three different CNN models: AlexNet, ResNet50, and ResNeXt. The models were verified by accuracy, recall, and F1 Score. The ResNeXt model had the high performance among the three models. Also, this study confirmed the reliability of the model designed by applying it to the experiment.

• Journal of Korea Game Society
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• v.15 no.5
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• pp.119-130
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• 2015

In the recent gaming industry, the paradigm has been changed with upcoming core-platform as time goes by. Arcade, console, PC online and smart device platforms are representative ones. In recently, the platform is changed to multi-platform which connecting to smart device and other platforms. Besides, the multi-platform without PC is up-coming. This paper suggests that a kind of multi-platform which connecting from smart devices to arcade devices be aware of lack of continuous. It provides a new arcade gaming condition connecting to smart devices, then supplies online network conditions to the arcade gaming machine. The original arcade game was lack of continuous and the game platform was so simple, but now, it could be focused from players by connecting to smart devices to increase the gaming machines' continuity. Furthermore, Bluetooth communication module and wireless Wi-Fi communication module are used to adapt various communication environments. The Unity3D engine would make contents' expandability.

• Journal of KIISE
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• v.42 no.8
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• pp.1031-1038
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• 2015

The recent emergence of smart phones, wearable devices, and even the IoT concept made it possible for various objects to interact one another anytime and anywhere. Among many of such smart services, a smart home service typically requires a large number of sensors to recognize the residents' activities. For this reason, the ideas on activity recognition using the data obtained from those sensors are actively discussed and studied these days. Furthermore, plenty of sensors are installed in order to recognize activities and analyze their patterns via data mining techniques. However, if many of these sensors should be installed for IoT smart home service, it raises the issue of cost and energy consumption. In this paper, we proposed a new method for reducing the number of sensors for activity recognition in a smart environment, which utilizes the principal component analysis and clustering techniques, and also show the effect of improvement in terms of the activity recognition by the proposed method.