• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.35.4-35
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• 2001

Image detection system for road traffic data analysis is a real time detection system using image processing techniques to get the real-time traffic information which is used for traffic control and analysis. One of the most important functions in this system is to match the coordinates of real world and that of image on video camera. When there in no way to know the exact position of camera and it´s height from the object. If some points on the road of real world are known it is possible to calculate the coordinates of real world from image.

• Geotechnical Engineering
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• v.26 no.9
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• pp.33-47
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• 2010

Underground constructions continue to provide challenges to Geotechnical Engineers yet they pose the best opportunities for development and deployment of advance technologies for analysis, design and construction. The reason for this is that, by virtue of the nature of underground constructions, more data and information on ground characteristics and response become available as the construction progresses. However, due to several barriers, these data and information are rarely, if ever, utilized to modify and improve project design and construction during the construction stage. To enable the use of evolving realtime data and information, and adaptively modify and improve design and construction, the paper presents an analysis and design system, called AMADEUS, for underground projects. AMADEUS stands for Adaptive, real-time and geologic Mapping, Analysis and Design of Underground Space. AMADEUS relies on recent advances in IT (Information Technology), particularly in digital imaging, data management, visualization and computation to significantly improve analysis, design and construction of underground projects. Using IT and remote sensors, real-time data on geology and excavation response are gathered during the construction using non-intrusive techniques which do not require expensive and time-consuming monitoring. The real-time data are then used to update geological and geomechanical models of the excavation, and to determine the optimal, construction sequences and stages, and structural support. Virtual environment (VE) systems are employed to allow virtual walk-throughs inside an excavation, observe geologic conditions, perform virtual construction operations, and investigate stability of the excavation via computer simulation to steer the next stages of construction.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.34 no.6
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• pp.569-578
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• 2016

With the recent advancement of surveying and technology, the spatial data acquisition rates and precision have been improved continually. As the updates of spatial data are rapid, and the size of data increases in line with the advancing technology, the LOD (Level of Detail) algorithm has been adopted to process data expressions in real time in a streaming format with spatial data divided precisely into separate steps. The existing GRID analysis utilizes the single DEM, as it is, in examining and analyzing all data outside the analysis area as well, which results in extending the analysis time in proportion to the quantity of data. Hence, this study suggests a method to reduce analysis time and data throughput by acquiring and analyzing DEM data necessary for GRID analysis in real time based on the area of analysis and the level of precision, specifically for streaming DEM data, which is utilized mostly for 3D geographic information service.

• Journal of the Korean Solar Energy Society
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• v.30 no.3
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• pp.25-32
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• 2010

A real-time monitoring system was developed for transfer, receive, backup and analysis of wind power data at three wind farm(Hang won, Hankyung and Sung san) in Jeju. For this monitoring system a communication system analysis, a collection of data and transmission module development, data base construction and data analysis and management module was developed, respectively. These modules deal with mechanical, electrical and environmental problem. Especially, time series graphic is supported by the data analysis and management module automatically. The time series graphic make easier to raw data analysis. Also, the real-time monitoring system is connected with wind power forecasting system through internet web for data transfer to wind power forecasting system's data base.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.05a
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• pp.165-166
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• 2017

It is demanding to receive information of data in real time anywhere and analyze it with meaningful data. Research on the platform for such analysis is actively underway. In this paper, we try to find out what are important factors in solving the problems of collecting and analyzing IoT data in real time. How much better than existing data collection methods and analytical methods can be the basis for judging the value of the data. It is important to accurately collect and store data more quickly and quickly from many sensors in real time in real time, and analytical methods that can derive values from the stored data. Therefore, an important requirement of the analysis platform in the IoT environment is to process large amount of data in real time and to centralize and manage it.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.10
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• pp.1361-1367
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• 2013

This paper describes and suggests the data visualization for real time power system operation based on energy management system. Because real time power system operation performs analysis of the vast amount of on-line data, the operators need intuitive data visualization to find out useful information in the big data. Especially, in emergency situation, the data visualization is able to assist the operators in handling the crisis quickly and efficiently. Therefore, this paper aims to improve displays of output of real time power system operation by visualizing on-line big data. Through this study, we can develop improved visualization technique for real time power system operation, which has highly readable displays of output and intuitive information.

• International Journal of Internet, Broadcasting and Communication
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• v.13 no.1
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• pp.134-142
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• 2021

This paper proposes a probabilistic method in analyzing timing measurements to determine the periodicity of real-time tasks. The proposed method fills a gap in existing techniques, which either concentrate on the estimation of worst-case execution times, or do not consider the stochastic behavior of the real-time scheduler. Our method is based on the Z-test statistical analysis which calculates the probability of the measured period to fall within a user-defined standard deviation limit. The distribution of the measured period should satisfy two conditions: its center (statistical mean) should be equal to the scheduled period of the real-time task, and that it should be symmetrical with most of the samples focused on the center. To ensure that these requirements are met, a data adjustment process, which omits any outliers in the expense of accuracy, is presented. Then, the Z-score of the distribution according to the user-defined deviation limit provides a probability which determines the periodicity of the real-time task. Experiments are conducted to analyze the timing measurements of real-time tasks based on real-time Linux extensions of Xenomai and RT-Preempt. The results indicate that the proposed method is able to provide easier interpretation of the periodicity of real-time tasks which are valuable especially in comparing the performance of various real-time systems.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.7
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• pp.720-725
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• 2008

This paper proposes a system architecture for USN with a service robot to provide more active assisted living services for elderly persons by monitoring their mental and physical well-being with USN environments at home, hospital, or silver town. Sensors embedded in USN are used to detect preventive measures for chronic disease. Logged data are transferred to main controller of a service robot via wireless channel in which the analysis of data is performed. For the purpose of handling emergency situations, it needs real-time processing on gathering variety sensor data, routing algorithms for sensor nodes to a moving sink node and processing of logged data. This paper realized multi-hop sensor network to detect user movements with biometric data transmission and performed algorithms on Xenomai, a real-time embedded Linux. To leverage active sensing, a mobile robot is used of which task was implemented with a priority to process urgent data came from the sink-node. This software architecture is anticipated to integrate sensing, communication and computing with real-time manner. In order to verify the usefulness of a proposed system, the performance of data transferring and processing on a real-time OS with non real-time OS is also evaluated.

• Journal of Korea Society of Industrial Information Systems
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• v.28 no.5
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• pp.89-108
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• 2023

This study provides a comprehensive analysis of recent studies conducted on the topic of nowcasting in order to enhance the accuracy and promptness of official statistical data. Furthermore, we propose an alternative approach involving the utilization of real-time data and its corresponding collection methods to effectively operate a real-time nowcasting model capable of accurately capturing the current economic condition. We explore high-frequency real-time data that can predict economic indicators in both the public and private sectors and propose a pipeline for data collection processing and modeling that is based on cloud platforms. Furthermore we validate the essential elements required for the implementation of real-time nowcasting, as well as their data management protocols to ensure the reliability and consistency needed for accurate forecasting of official statistical indicators.

• International journal of advanced smart convergence
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• v.4 no.2
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• pp.46-53
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• 2015

This paper suggests a method of real time confidence interval estimation to detect abnormal states of sensor data. For real time confidence interval estimation, the mean square errors of the exponential smoothing method and moving average method, two of the time series analysis method, were compared, and the moving average method with less errors was applied. When the sensor data passes the bounds of the confidence interval estimation, the administrator is notified through alarms. As the suggested method is for real time anomaly detection in a ship, an Android terminal was adopted for better communication between the wireless sensor network and users. For safe navigation, an administrator can make decisions promptly and accurately upon emergency situation in a ship by referring to the anomaly detection information through real time confidence interval estimation.