• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.6
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• pp.96-106
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• 2020

To solve the limitation of traffic monitoring that occur from embedded sensor such as loop and piezo sensors, the thermal imaging camera was installed on the roadside. As the length of Class 1(passenger car) is getting longer, it is becoming difficult to classify from Class 3(2-axle truck) by using an embedded sensor. The collected images were labeled to generate training data. A total of 17,536 vehicle images (640x480 pixels) training data were produced. CNN (Convolutional Neural Network) was used to achieve vehicle classification based on thermal image. Based on the limited data volume and quality, a classification accuracy of 97.7% was achieved. It shows the possibility of traffic monitoring system based on AI. If more learning data is collected in the future, 12-class classification will be possible. Also, AI-based traffic monitoring will be able to classify not only 12-class, but also new various class such as eco-friendly vehicles, vehicle in violation, motorcycles, etc. Which can be used as statistical data for national policy, research, and industry.

• Journal of Korea Multimedia Society
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• v.14 no.5
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• pp.703-709
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• 2011

State-based infrastructure on IT-based network are prone to numerous cyber attack including subsequent hacking and internet infringement. These acts of terrorism are increasing because of the expanding IT convergence technology. Recently, the trend on cyber security monitoring and control researches focus on combining the general idea of security monitoring and control along with IT field and other control systems. This convergence trend has been increasing in both the use and importance. This research analyzes the state-based infrastructure monitoring and control system, its vulnerability as well as its improvement by incorporating the cyber convergence systems to existing systems. The subject of this research is for extensive use of CCTV systems which is expanded for 'CCTV Monitoring and Control Field' as well as 'Traffic Monitoring and Control Field' operated by 'Intelligent Traffic Information System' and Disaster Management Area which is studied in various fields. Eventually, the objective of the paper is to solve these issues, to apply related systems and to suggest improvement on the convergence system.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.6
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• pp.1311-1322
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• 1997

Performance management of ATM network is urgently required because a different quality of service should be guaranteed on each connection. A lot of performance measurement data increase the burden on agent systems and on managment stations. In this paper, an effective OAM-based performance monitoring and faulty node identification technique is proposed. A proposed VP Selection Algorithm reduces management-related traffic and when the indication of hard or soft failure state is detected, failed node is identified by Fault Identification Rule.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.1243-1244
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• 2022

In recent years, the growing interest in off-site construction has led to factories scaling up their manufacturing and production processes in the construction sector. Consequently, continuous large-scale site monitoring in low-variability environments, such as prefabricated components production plants (precast concrete production), has gained increasing importance. Although many studies on computer vision-based site monitoring have been conducted, challenges for deploying this technology for large-scale field applications still remain. One of the issues is collecting and transmitting vast amounts of video data. Continuous site monitoring systems are based on real-time video data collection and analysis, which requires excessive computational resources and network traffic. In addition, it is difficult to integrate various object information with different sizes and scales into a single scene. Various sizes and types of objects (e.g., workers, heavy equipment, and materials) exist in a plant production environment, and these objects should be detected simultaneously for effective site monitoring. However, with the existing object detection algorithms, it is difficult to simultaneously detect objects with significant differences in size because collecting and training massive amounts of object image data with various scales is necessary. This study thus developed a large-scale site monitoring system using edge computing and a small-object detection system to solve these problems. Edge computing is a distributed information technology architecture wherein the image or video data is processed near the originating source, not on a centralized server or cloud. By inferring information from the AI computing module equipped with CCTVs and communicating only the processed information with the server, it is possible to reduce excessive network traffic. Small-object detection is an innovative method to detect different-sized objects by cropping the raw image and setting the appropriate number of rows and columns for image splitting based on the target object size. This enables the detection of small objects from cropped and magnified images. The detected small objects can then be expressed in the original image. In the inference process, this study used the YOLO-v5 algorithm, known for its fast processing speed and widely used for real-time object detection. This method could effectively detect large and even small objects that were difficult to detect with the existing object detection algorithms. When the large-scale site monitoring system was tested, it performed well in detecting small objects, such as workers in a large-scale view of construction sites, which were inaccurately detected by the existing algorithms. Our next goal is to incorporate various safety monitoring and risk analysis algorithms into this system, such as collision risk estimation, based on the time-to-collision concept, enabling the optimization of safety routes by accumulating workers' paths and inferring the risky areas based on workers' trajectory patterns. Through such developments, this continuous large-scale site monitoring system can guide a construction plant's safety management system more effectively.

• Transactions of The Korea Fluid Power Systems Society
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• v.8 no.4
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• pp.17-23
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• 2011

Proportional control solenoid is a type of modulating valve that can continuously control the valve position with magnetic force of solenoid. Recent microcontroller based digital servocontroller for proportional valve is being developed toward the smart valve with additional features such as enhanced control algorithm for finer process and intelligent on-board diagnosis for maintenance. In this paper, development of servocontroller network control with CAN bus which is free from problems of security and network traffic jam is presented. Design of network control system includes modes of communication between master and slave, assignment of 29bit message identifier and message objects, transaction of communication sequence, etc. Monitoring function and control experiments for remote valve through CAN network prove the extended function of smart valve control system.

• Journal of Communications and Networks
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• v.13 no.2
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• pp.149-159
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• 2011

In this paper, we study the problem of how to design a medical-grade wireless local area network (WLAN) for healthcare facilities. First, unlike the IEEE 802.11e MAC, which categorizes traffic primarily by their delay constraints, we prioritize medical applications according to their medical urgency. Second, we propose a mechanism that can guarantee absolute priority to each traffic category, which is critical for medical-grade quality of service (QoS), while the conventional 802.11e MAC only provides relative priority to each traffic category. Based on absolute priority, we focus on the performance of real-time patient monitoring applications, and derive the optimal contention window size that can significantly improve the throughput performance. Finally, for proper performance evaluation from a medical viewpoint, we introduce the weighted diagnostic distortion (WDD) as a medical QoS metric to effectively measure the medical diagnosability by extracting the main diagnostic features of medical signal. Our simulation result shows that the proposed mechanism, together with medical categorization using absolute priority, can significantly improve the medical-grade QoS performance over the conventional IEEE 802.11e MAC.

• Journal of the Korea Society of Computer and Information
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• v.7 no.3
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• pp.115-121
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• 2002

This paper discussed to design system to overcome time, place and service limitation in the case of extracting traffic on active service in the ATM network. There are several specification in this system : for a remote control function, a real-time traffic extraction from ATM link on service without affect in-service, and an O&M(Operating and Maintenance) cost down effect. This paper include the requirement, module structure, operating characteristics and command for the developing function. This product installed at the KT's telephone office. And we have tested the stability, reliability and functionality. As the result, it was verified that this system commercially is abel to use without especial problem. Hereafter, we are improving module structure for the cost down.

• Journal of the Korea Society of Computer and Information
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• v.11 no.3
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• pp.203-211
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• 2006

Today, Internet covers a world wide range and most appliances of our life are linked to network from enterprise server to household electric appliance. Therefore, the importances of administrable framework that can grasp network state by real-time is increasing day by day. Our objective in this paper is to describe a network weather report framework that monitors network traffic and performance state to report a network situation including traffic status in real-time. We also describe a mobile agent architecture that collects state information in each network segment. The framework could inform a network manager of the network situation. Through the framework. network manager accumulates network data and increases network operating efficiency.

• Proceedings of the Korean Information Science Society Conference
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• 2011.06a
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• pp.407-409
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• 2011

Wireless Sensor Networks "WSN" can be implemented in a wide range of applications. Some of these have unpredictable behavior, such as disaster or intrusion monitoring. Sudden large bursting amounts of data can increase traffic and degrade the WSN's performance as well as energy resources. In this work we propose an adjustment of radio transmission range where more or less nodes can be part of the neighborhood area and collaborate in retransmission. As simulation results prove, such adjustment based on traffic can benefit to balance network lifetime.

• Proceedings of the Korea Contents Association Conference
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• 2005.05a
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• pp.83-86
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• 2005

Recently, demage of denial of service attack and worm attack has grown larger and larger every year. But Research of harmful traffic detection is not sufficient when the IPv4 environment is replaced with the IPv6 environment in near future. The purpose of this paper is attact detection which has been detected harmful traffic monitoring on the IPv6 using the Internet management protocol SNMP.