• Journal of the Korean Society for Marine Environment & Energy
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• v.8 no.2
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• pp.53-59
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• 2005

An integrated real-time monitoring software for coastal environment has been developed by using GUI. The system consists of modeling module, real-time monitoring module, and post-processing module of the modeling and monitoring results. The system was applied to a port construction site. The main purpose for the system is to setup the information system that user can obtain the environmental information easily and quickly. The system can be used to monitor environmental changes due to construction activities in coastal waters and to assess environmental impacts accurately in real-time. In conclusion, the system will be a good tool for finding out countermeasures to lessen water pollution and clean seawater.

• Convergence Security Journal
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• v.17 no.2
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• pp.69-80
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• 2017

Due to the advanced IT environment, the role of Security Monitoring & Control becomes more important as the cyber-crime is becoming intelligent, diversified, and advanced. In contrast to the way it relied solely on security devices such as Firewall and IDS in the past, Security Monitoring & Control tasks responding to cyber attacks through real-time monitoring have become wide spread and their role is also important. In response to current cyber threats, since security equipment alone can not be guaranteed a stable defense, the task of Security Monitoring & Control became essential to operate and monitor security equipment and to respond in real time. In this study, we will discuss how to configure network security system effectively and how to improve the real-time Security Monitor & Control.

• International journal of advanced smart convergence
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• v.12 no.3
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• pp.104-108
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• 2023

This paper deals with research on innovative systems using Python-based artificial intelligence technology in the field of plant growth monitoring. The importance of monitoring and analyzing the health status and growth environment of plants in real time contributes to improving the efficiency and quality of crop production. This paper proposes a method of processing and analyzing plant image data using computer vision and deep learning technologies. The system was implemented using Python language and the main deep learning framework, TensorFlow, PyTorch. A camera system that monitors plants in real time acquires image data and provides it as input to a deep neural network model. This model was used to determine the growth state of plants, the presence of pests, and nutritional status. The proposed system provides users with information on plant state changes in real time by providing monitoring results in the form of visual or notification. In addition, it is also used to predict future growth conditions or anomalies by building data analysis and prediction models based on the collected data. This paper is about the design and implementation of Python-based plant growth monitoring systems, data processing and analysis methods, and is expected to contribute to important research areas for improving plant production efficiency and reducing resource consumption.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.33 no.2
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• pp.215-229
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• 2023

Objectives: To validate the effectiveness of a real-time chemical exposure monitoring system developed by KOSHA (Korea Occupational Safety and Health Agency), we applied the system to a workplace in the electronics industry for 153 days. Methods: The monitoring system consisted of a PID chemical sensor, a LTE communication equipment, and a web-based platform. To monitor chemical exposure, four sets of sensors were placed in two manufacturing tasks - inspection and jig cleaning - which used TCE as a degreasing agent. We reviewed previous reports of work environment measurements and conducted a new work environment measurement on one day during the period. The PID sensor systems detected the chemical exposure levels in the workplace every second and transmitted it to the platform. Daily average and maximum chemical exposure levels were also recorded. Results: We compared the results from the real-time monitoring system and the work environment measurement by traditional methods. Generally, the data from the real-time monitoring system showed a higher level because the sensors were closer to the chemical source. We found that 28% of jig cleaning task data exceeded the STEL. Peak exposure levels of sensor data were useful for understanding the characteristics of the task's chemical use. Limitations and implications were reviewed for the adoption of the system for preventing poisoning caused by chemical substances. Conclusions: We found that the real-time chemical exposure monitoring system was an efficient tool for preventing occupational diseases caused by chemical exposure, such as acute poisoning. Further research is needed to improve the reliability and applicability of the system. We also believe that forming a social consensus around the system is essential.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.10a
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• pp.564-567
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• 2005

For the application of monitoring system of the machine tool to industry, the requirements such as high reliability and low cost need to be satisfied. In this study, a reliable but inexpensive monitoring method for machine tool is introduced. To improve the monitoring reliability, several kinds of information related to machining and operation are selected; real-time video clip from USB camera, operation data and signal from CNC and feed motor torque. Especially, to improve the quality of real-time video clip, a camera housing is developed, it can significantly reduce the vibration effect and prevent from coolant and chip. The collected information are transferred to the monitoring terminals in remote sites using OPC and TCP/IP protocol over Ethernet, which give us convenience of development and interoperability.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2004.04a
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• pp.107-112
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• 2004

Corresponding to the importance of real-time position tracing in the customs free zone, the logistics monitoring system utilizing GPS and PDA correctly confirms the position of the logistics at real time. Information obtained through the use of bluetooth is transmitted into the control station that controls the flow of the logistics. This logistics monitoring system can efficiently identify the movement of the logistics all the time.

• The Journal of Society for e-Business Studies
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• v.13 no.2
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• pp.101-115
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• 2008

Recently in the human society, the crime using small arms has increased. Also, many accidents happen because of incomplete management of chemicals and radiation. Accordingly, it is necessary to manage dangerous objects by tracing the position of dangerous objects and rapidly providing the correct information for them. This paper presents a web-based system for real-time monitoring of dangerous objects using RFID in order to overcome the limitations and problems of current dangerous objects management techniques. In this paper, we define the architecture for web-based dangerous objects monitoring system and the scheme for storing information of a dangerous object in the RFID tag. We also implement the web-based monitoring system and present the execution result of the system. The proposed real-time monitoring system is composed of the dangerous objects monitoring server which manages information of dangerous objects and controls them, the dangerous objects monitoring middleware which is mediator between dangerous objects and the server, the RFID reader which reads information of dangerous objects from RFID tags attached to the objects and the database which stores information, status and position of dangerous object. The proposed system manages diverse dangerous objects such as small arms, radiation and harmful chemicals based on the position of them using RFID, so the user can check dangerous objects when they are checked in and checked out and the user can acquire the real-time position information of them through the system. Furthermore, the user can visually monitor dangerous objects through web browser from any where and at any time because the system is web-based system and it provides graphical user interface.

• Proceedings of the KOSOMBE Conference
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• v.1996 no.05
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• pp.31-35
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• 1996

This paper presents a real time algorithm for monitoring of the arrythmia of ECG signal. A real time monitoring, following by detecting a QRS complex, is the most important. Using 2-dimensional time-delay coordinates which are reconstructed by the phase portrait plotting special trajectory, we detect QRS complexes. In this study, arrythmias are detected by matching the past standard template with tile present pattern when changing abruptly In order to matching with each other, we propose modified chain coding algorithm which applies vetor table consisting of eight orthonormal code(=binary code) to the phase portraits. This algorithm using logical function increases the weight if exceeding to the threshold determinded by correlation value and the distance from a straight line(y=x). Evaluating the performance of the proposed algorithm, we use standard MIT/BIH database. The results are fellowing, 1) Improve the speed of matching template than that of cross-correlation ever has been used. 2) Because the proposed algorithm is robust to varing fiducial point, it is possible to monitor the ECG signal with irregular RR interval. 3) In spite of baseline wandering owing to the low frequency noise, monitoring performance is not reduced.

• Journal of Korea Multimedia Society
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• v.25 no.4
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• pp.583-599
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• 2022

Although the object detection accuracy with a single image has been significantly improved with the advance of deep learning techniques, the detection accuracy for pig monitoring is challenged by occlusion problems due to a complex structure of a pig room such as food facility. These detection difficulties with a single image can be mitigated by using a video data. In this research, we propose a method in pig detection for video monitoring environment with a static camera. That is, by using both image processing and deep learning techniques, we can recognize a complex structure of a pig room and this information of the pig room can be utilized for improving the detection accuracy of pigs in the monitored pig room. Furthermore, we reduce the execution time overhead by applying a pruning technique for real-time video monitoring on an embedded board. Based on the experiment results with a video data set obtained from a commercial pig farm, we confirmed that the pigs could be detected more accurately in real-time, even on an embedded board.

• Journal of Korean Society of Environmental Engineers
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• v.38 no.4
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• pp.184-192
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• 2016

A profiling monitoring system has been developed to monitor the water quality variations according to each water depth and applied for a test-bed. The key parameters were derived to disclose the aquatic ecology and environment of river systems, and the real-time monitoring techniques to profile the variations of each parameter were verified. Monitoring parameters were configured to include water quality, hydrodynamic, and weather conditions. Considering the water depth of the 4 major rivers in Korea, a profiling monitoring system with 1.0 m water depth interval for each monitoring has been established. To understand the real-time variation properties in the Han river, the monitoring system has been installed and operated at the YangHwa-Dock as a test-bed. Based on the results of the detailed analyses on the spring season, as the characteristic diurnal and water-depth-related variations for water temperature, pH, dissolved oxygen (DO), and chlorophyll-a were observed, it could be concluded that the real-time water-depth profiling monitoring system is a very effective tool for the proper management of river environment.