• Journal of Korean Society on Water Environment
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• v.20 no.4
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• pp.321-326
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• 2004

The objective of this study is to test the applicability of neural network models to forecast water quality at Naesa and Pyongchang river. Water quality data devided into rainy day and non-rainy day to find characteristics of them. The mean and maximum data of rainy day show higher than those of non-rainy day. And discharge correlate with TOC at Pyongchang river. Neural network model is trained to the correlation of discharge with water quality. As a result, it is convinced that the proposed neural network model can apply to the analysis of real time water quality monitoring.

• Proceedings of the IEEK Conference
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• 2002.06d
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• pp.351-354
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• 2002

DVR(Digital Video Recorder), a recently popular visual monitoring system, is required to support multi camera channel display(upto 16 channels) with various display modes in real-time. For such a multichannel display system, it is well known that tearing artifacts become more serious. Thus, one needs to design a display system for DVR so that it does not show tearing artifacts as much as possible, but keeps real-time display speed. In this paper, we present our efforts in designing and implementing a display system which rarely ever shows tearing artifacts, but without degradation of required real-time display speed, and which displays character information stably without blinking.

• Journal of the Korea Safety Management & Science
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• v.4 no.3
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• pp.67-78
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• 2002

Automated manufacturing systems are applied to shop floors as tools for increase of productivity and quality and the decrease of manufacturing lead times and industry accidents. One of the most important issue of the present day is the application of Internet. The development of Internet technologies makes manufacturing enterprises break spacial barriers between users and shop floors, and collect various field data in remote sites. In this research, an Internet-based remote control system for a small-sized automated storage and retrieval system is developed for the purpose of real-time monitoring and control of automatic production equipment. The developed system has a client-server architecture and sends real-time images of the automated storage and retrieval system to clients by an CCD camera connected to a server.

• Applied Science and Convergence Technology
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• v.26 no.6
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• pp.214-217
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• 2017

AlSb is a promising material for optical devices, particularly for high-frequency and nonlinear-optical applications. We report the effect of growth temperature on structural properties of AlSb grown on GaAs substrate. In particular we studied the surface of AlSb with the growth temperature by atomic force microscopy, and concluded that optimized growth temperature of AlSb is $530^{\circ}C$. We also show the result of real-time monitoring of AlSb growth by in situ ellipsometry. The results of the structural study are good agreement with the previous reported ellipsometric data.

• International conference on construction engineering and project management
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• 2009.05a
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• pp.479-486
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• 2009

This paper presents an integrated real-time monitoring and control framework that facilitates decision making by enabling project managers to take corrective actions right after any deviation happens and mitigate the damage to the ongoing steel projects. The proposed framework employs the High Level Architecture (HLA) as its infrastructure. It is composed of several individual monitoring and control components called "Federates," which cooperate and interact with each other through the Real-time Infrastructure (RTI). Reusability, interoperability and extendibility of federates in the proposed project control system make this a unique system.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2023.11a
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• pp.165-166
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• 2023

Construction inspection and monitoring are key activities in construction projects. Automation of inspection tasks improves the limitations and inefficiencies of manual construction inspections, enabling systematic and consistent construction inspections. In this paper, an RTSP (Real-Time Streaming Protocol) system is used to remotely manage and supervise the construction site without having to visit the construction site by deploying a robot on site on behalf of four construction stakeholders (owner, supervisor, constructor, and designer). I would like to propose. The proposed system can contribute to identifying and monitoring the process process and work results at the construction site in real time.

• Journal of the Korean Society of Industry Convergence
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• v.27 no.4_2
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• pp.1001-1007
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• 2024

Recent deep learning algorithms for object detection in real-time play a crucial role in various applications such as autonomous driving, traffic monitoring, health care, and water quality monitoring. The size of small objects, in particular, significantly impacts the accuracy of detection models. However, data containing small objects can lead to underfitting issues in models. Therefore, this study developed a deep learning model capable of quickly detecting small objects to provide more accurate predictions. The RE-SOD (Residual block based Small Object Detector) developed in this research enhances the detection performance for small objects by using RGB separation preprocessing and residual blocks. The model achieved an accuracy of 1.0 in image classification and an mAP50-95 score of 0.944 in object detection. The performance of this model was validated by comparing it with real-time detection models such as YOLOv5, YOLOv7, and YOLOv8.

• Journal of the Korean Society of Visualization
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• v.20 no.2
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• pp.86-92
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• 2022

Pipe failure due to thermal fatigue and environmental regulations are increasing the importance of pipe monitoring systems in industrial plants. Since most pipe monitoring systems are focus on external crack inspected, it is necessary to temperature and concentration measuring monitoring system inside the pipe. These systems have spatial uncertainty due to sample inspection by one-point measurement. In addition, real-time measurement is not possible due to the limitation of time delay due to contact measurement. In this study, CT-TDLAS (Computed tomography-Tunable diode laser absorption spectroscopy) apply to overcome the limitations of existing methods. Lasers exhibiting an absorption response at a wavelength of 1395 nm were arranged in a lattice pattern on measuring cell. It showed that the inside of the pipe changed to an unstable combustion state over time.

• Journal of the Korean Society of Industry Convergence
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• v.26 no.5
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• pp.867-874
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• 2023

In this paper, a wireless communication-based sensor data monitoring device with an explosion-proof (Exd IIC) case was implemented to enable installation at explosion-risk industrial sites such as plants. In existing industrial plant sites, most of the temperature sensors and vibration and impact sensors are wired up to several kilometers, which takes a lot of time and money to bury long pipes and cables. In addition, there are not many cases where some wireless devices have been applied to actual plant industry sites due to communication quality problems. Therefore, in order to solve this problem, zigbee mesh wireless communication was applied to provide high reliability wireless communication quality to industrial plant sites, and the time and cost incurred in new or additional installation of sensors could be greatly reduced. In particular, in the event of loss or error of some wireless communication devices, the communication network is automatically bypassed or recovered to enable real-time data monitoring.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.6
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• pp.940-947
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• 2015

A Sitting posture is a very important issue for moderns who is mostly sedentary. Also, a wrong sitting posture causes back-pain and spinal disease. Many researchers have been proposed numerous approaches that classifying and monitoring for a sitting posture. In this paper, we proposed a real-time sitting posture monitoring system that was developed to measure pressure distribution in the human body. The proposed system consists of a pressure sensing module (six pressure sensors), data acquisition and processing module, a communication module and a display module for an individual sitting posture monitoring. The developed monitoring system can classify into five sitting postures, such as a correct sitting, sitting on forward inclination, leaning back sitting, sitting with a right leg crossed and a left leg crossed. In addition, when a user deviates from the correct posture, an alarm function is activated. We selected two kinds of chairs, one is rigid material and fixed form, the other one is a soft material and can adjust the height of a chair. In the experiments, we observed appearance changes for subjects in consequence of a comparison between before the correction of posture and after the correction of posture when using the proposed system. The data from twenty four subjects has been classified with a proposed classifier, achieving an average accuracy of 83.85%, 94.56% when the rigid chair and the soft chair, respectively.