• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.05a
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• pp.823-826
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• 2008

This paper will show how to design home network management system in the wired/wireless environment using graphical language LabVIEW, J2ME and to apply the design to monitoring and remote controling for the information devices at home. This paper also provides with efficiency of device control and current status check according to the circumstances of administrators by constructing the wire/wirelessly integrated administration system. It means the administrators can access to central administration server and acquire the control right through web being able to operate the system with flexibility and can access to the server without computer whenever, wherever they need to control and administrate it through this wired/wireless unit easily.

• The Journal of the Korea Contents Association
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• v.11 no.6
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• pp.42-50
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• 2011

This paper is to propose design and implementation methods of a pet dog management system that can effectively manage the pet dog in home through client such as a mobile terminal or a PC from remote location, in the absence of the owner in the house. Through this system, we can manage the dog efficiently via a series of monitoring and control functionalities of the dog such as observing of the dog's status, or feeding the dog, or taking the necessary measures on maintaining a healthy environment such as temperature/humidity sensing and turn on/off fans and lights, or sending SMS text to the owner from detection of the barking of the dog.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.8 no.2
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• pp.57-65
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• 2008

Wireless sensor networks achieve environment monitoring and controlling through use of small devices of low cost and low power. Such network is comprised of several sensor nodes, each having a microprocessor, sensor, actuator and wired/wireless transceiver inside a small device. In this paper, we employ the sensor networks in order to design and implement a real-time vehicle safety system. Such system can inform the safe velocity in a specific weather condition to drivers in advance through analyzing the weather data collected from sensor networks. As a result, the drivers can prevent effectively accidents by controlling their car speed.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.19 no.11
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• pp.94-101
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• 2020

In the age of industry 4.0, artificial intelligence is being widely used to realize machinery condition monitoring. Due to their excellent performance and the ability to handle large volumes of data, machine learning techniques have been applied to realize the fault diagnosis of different equipment. In this study, we performed the failure mode effect analysis (FMEA) of an aluminum electrolytic capacitor by using deep learning and big data. Several tests were performed to identify the main failure mode of the aluminum electrolytic capacitor, and it was noted that the capacitance reduced significantly over time due to overheating. To reflect the capacitance degradation behavior over time, we employed the Vanilla long short-term memory (LSTM) neural network architecture. The LSTM neural network has been demonstrated to achieve excellent long-term predictions. The prediction results and metrics of the LSTM and Vanilla LSTM models were examined and compared. The Vanilla LSTM outperformed the conventional LSTM in terms of the computational resources and time required to predict the capacitance degradation.

• Spatial Information Research
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• v.19 no.5
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• pp.87-96
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• 2011

Recently mobile users can access to internet using smart phone at any place and any time, through which they can search and share information. In addition, as the sensors with high-tech functions become cheaper and miniaturized along with the development of MEMS (micro-electo mechanical systems) technology, the extent to utilize smart phone is increasing. Smart phone is equipped with various sensors such as high-resolution camera, GPS, gyroscope and magnetic sensor, which is an appropriate system configuration for remote monitoring research using camera. The remote monitoring system requires camera for video and internet network to send video, for which it has a limitation that it is influenced by the monitoring location. This study is aimed to design and develop the monitoring app. which can be remotely monitored using smart phone technology. The developed monitoring app was designed to take images of ROI (region of interest) within the specified time and to automatically send the images to the server. The developed app. is also possible to be remotely controlled by SMS (short message service). The monitoring proposed in this study can take high-resolution images using CMOS built in the smart phone and send the images and information to the server automatically at any place and any time using 3G and Wi-Fi networks.

• Journal of the Institute of Convergence Signal Processing
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• v.13 no.3
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• pp.136-141
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• 2012

One of the main reasons for serious road accidents is driving while drowsy. For this reason, drowsiness detection and warning system for drivers has recently become a very important issue. Monitoring physiological signals provides the possibility of detecting features of drowsiness and fatigue of drivers. One of the effective signals is to measure electroencephalogram (EEG) signals and electrooculogram (EOG) signals. The aim of this study is to extract drowsiness-related features from a set of EEG signals and to classify the features into three states: alertness, drowsiness, sleepiness. This paper proposes a neural-network-based drowsiness detection system using Linear Predictive Coding (LPC) coefficients as feature vectors and Multi-Layer Perceptron (MLP) as a classifier. Samples of EEG data from each predefined state were used to train the MLP program by using the proposed feature extraction algorithms. The trained MLP program was tested on unclassified EEG data and subsequently reviewed according to manual classification. The classification rate of the proposed system is over 96.5% for only very small number of samples (250ms, 64 samples). Therefore, it can be applied to real driving incident situation that can occur for a split second.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.16 no.6
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• pp.43-54
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• 2016

The occurrence of cyber crime is on the rise every year, and the security control center, which should play a crucial role in monitoring and early response against the cyber attacks targeting various information systems, its importance has increased accordingly. Every endeavors to prevent cyber attacks is being attempted by information security personnel of government and financial sector's security control center, threat response Center, cyber terror response center, Cert Team, SOC(Security Operator Center) and else. The ordinary method to monitor cyber attacks consists of utilizing the security system or the network security device. It is anticipated, however, to be insufficient since this is simply one dimensional way of monitoring them based on signatures. There has been considerable improvement of the security control system and researchers also have conducted a number of studies on monitoring methods to prevent threats to security. In accordance with the environment changes from ESM to SIEM, the security control system is able to be provided with more input data as well as generate the correlation analysis which integrates the processed data, by extraction and parsing, into the potential scenarios of attack or threat. This article shows case studies how to detect the threat to security in effective ways, from the initial phase of the security control system to current SIEM circumstances. Furthermore, scenarios based security control systems rather than simple monitoring is introduced, and finally methods of producing the correlation analysis and its verification methods are presented. It is expected that this result contributes to the development of cyber attack monitoring system in other security centers.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.6B
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• pp.600-607
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• 2011

As network traffic is dramatically increasing due to the popularization of Internet, the need for application traffic identification becomes important for the effective use of network resources. In this paper, we present an Internet application traffic identification method based on flow correlation to overcome limitation of signature-based identification methods and to improve performance (completeness) of it. The proposed method can identify unidentified flows from signature-based method using flow correlation between identified and unidentified flows. We propose four separate correlation methods such as Server-Client, Time, Host-Host, and Statistic correlation and describe a flow correlation-based identification system architecture which incorporates the four separate methods. Also we prove the feasibility and applicability of our proposed method by an acceptable experimental result.

• 전자공학회논문지 IE
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• v.48 no.4
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• pp.61-68
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• 2011

As business management has a high level of dependence on Informational Technology (IT), protecting assets of a company from disaster is one of the most important thing that IT operating managers should consider. Because data or information is a major source of operation of the company, data security is the first priority as an aspect of continuity of business management. Therefore, this paper will realize disaster recovery system, which is suspended because of disaster, based on cloud computing system. Realized High Available Replicate System applied a method of multi thread target database to improve Replicate performance, and real time synchronize technology can improve efficiency of network. From Active to Active operation, it maximizes use of backup system, and it has a effect to disperse load of source database system. Also, High Available Replicate System realized consistency verification mechanism and monitoring technique. For Performance evaluation, High Available Replicate System used multi thread method, which shows more than threefold of replicate performance than single thread method.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.11
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• pp.2097-2104
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• 2008

Ubiquitous services are high duality and differentiated services which are provided for users by recognizing the context of users and environmental conditions actively. In this case, context-aware middleware is one of the most important technologies required to implement the ubiquitous services. In this paper, we propose a method for providing ubiquitous services in a specific user space effectively and monitoring human bio-signal sensors. That is, the design and implementation of intelligent home service middleware and monitoring human bio-signal sensor based on context awareness is discussed here. Context information from various sensors is gathered, and suitable services are inferred and provided to users by the middleware system. In our approach, user services can be modelled easily by using facts and rules, and the system can be extended easily to support various ubiquitous services other than intelligent home services also. The system can be integrated with external applications and legacy systems effectively by using various protocols such as RMI, socket and HTTP, XML and Zigbee etc. We have designed and evaluated various facts and rules for intelligent home services in real environments. Functionality evaluation with the system shows that ubiquitous services can be provided to users effectively in a home environment.