• The Transactions of the Korean Institute of Electrical Engineers P
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• v.59 no.1
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• pp.71-76
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• 2010

This paper is focused on implementing a real-time data acquisition system that checks power facility status by applying network based technology to Urban Transit substation power facilities and the results of its on-field tests. This system is composed of a sensor part, a measurement part, a transceiver part, a host computer, and a power source part. The system is designed to collect, save, analyze, and display the online state power facility AI (Analog Input). This system measures voltage and current from positive feeders and negative feeders where it is possible to check abnormalities of the substation‘s main power facilities. By monitoring abnormal data of the Urban Transit power facilities real-time and analyzing stored data, establishing procedures of optimized maintenance is possible.

• Proceedings of the KIEE Conference
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• 2007.04a
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• pp.160-162
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• 2007

The systems for assisted living and convenience of user real-time requirement in data communication among devices. therefore, it system was requirement to implementation of the hardware which guarantees the real-time to load the high-performance processor with suitable Operation System. This paper apply to operated intelligence robot in USN(Ubiquitous Sensor Network) environment, particularly, it is architecture research for guarantees the real-time of a sink-node that collect various sensor information from sensors and sending to main control unit.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.9
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• pp.2213-2231
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• 2013

Compressed sensing is a novel technology used in the field of wireless communication and sensor networks for channel estimation, signal detection, data gathering, network monitoring, and other applications. It plays a significant role in highly secure, real-time, well organized, and cost-effective data communication in smart-grid (SG) systems, which consist of multi-tier network standards that make it challenging to synchronize in power management communication. In this paper, we present a multi-layer communication model for SG systems and propose compressed-sensing based data transmission at every layer of the SG system to improve data transmission performance. Our approach is to utilize the compressed-sensing procedure at every layer in a controlled manner. Simulation results demonstrate that the proposed monitoring devices need less transmission power than conventional systems. Additionally, secure, reliable, and real-time data transmission is possible with the compressed-sensing technique.

• Proceedings of the IEEK Conference
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• 2007.07a
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• pp.133-134
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• 2007

The effective data processing mechanism in the sensor network means data stream model and real-time query processing model for real-time processing of stream data. This mechanism can improve satisfaction of users and reduce delay rate of data processing. In this paper, we explain the problem which is occurred when users need to search certain information among information of stream data and describe reduction model of delay rate according to data transmission.

• Journal of Korea Spatial Information System Society
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• v.10 no.4
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• pp.97-102
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• 2008

A wireless sensor network consists of many sensors that collect and transmit physical or environmental conditions at different locations to a server continuously. Many researches mainly focus on processing continuous queries on real-time data stream. However, they do not concern the problem of storing the historical data, which is mandatory to the historical queries. In this paper, we propose two time-based storage methods to store the sensor data stream and reduce the managed tuples without any loss of information, which lead to the improvement of the accuracy of query results.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.1249-1252
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• 1996

With the expansion of research and development for the CIM and the IMS, the importance of introducing the communication network is being increased. This paper presents an implementation of robot workcell by using Fieldbus and investigates data operation of the robot workcell. Through experiments, the operations of periodic and real-time data, and non-periodic real-time data are studied. Also, the relationship between the network transmission rate and the monitoring results from the sensor is analyzed.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10b
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• pp.112-117
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• 1992

The Real-time Distributed Control Systems(RDCS) consist of several distributed control processes which share a network medium to exchange their data. Performance of feedback control loops in the RDCS is subject to the network-induced delays from sensor to controller and from controller to actuator. The network-induced delays are directly dependent upon the data sampling times of the control components which share a network medium. In this study, a scheduling algorithm of determining data sampling times is developed using the window concept, where the sampling data from the control components dynamically share a limited number of windows.

• Journal of Wellbeing Management and Applied Psychology
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• v.6 no.2
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• pp.27-31
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• 2023

Purpose: Establishment of a real-time monitoring system for odor control in traditional markets in Gangwon-do and a system for linking prevention facilities. Research design, data and methodology: Build server and system logic based on data through real-time monitoring device (sensor-based). A temporary data generation program for deep learning is developed to develop a model for odor data. Results: A REST API was developed for using the model prediction service, and a test was performed to find an algorithm with high prediction probability and parameter values optimized for learning. In the deep learning algorithm for AI modeling development, Pandas was used for data analysis and processing, and TensorFlow V2 (keras) was used as the deep learning library. The activation function was swish, the performance of the model was optimized for Adam, the performance was measured with MSE, the model method was Functional API, and the model storage format was Sequential API (LSTM)/HDF5. Conclusions: The developed system has the potential to effectively monitor and manage odors in traditional markets. By utilizing real-time data, the system can provide timely alerts and facilitate preventive measures to control and mitigate odors. The AI modeling component enhances the system's predictive capabilities, allowing for proactive odor management.

• Proceedings of the KIEE Conference
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• 2007.04a
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• pp.436-438
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• 2007

As the sensors and communication technology get advance, the remote health diagnosis for patients and senior persons at home are possible now without visiting doctors in hospitals. A low-power ubiquitous health check device was developed adapting Real-Time Embedded Linux is developed. This ubiquitous device is consisted of three sensors. The wrist type health checking terminal acquires periodically the health data by using a blood pressure sensor, a pulse sensor and a body temperature sensor. It transmits the health data to the access point located at the home center through the ZigBee wireless communication modem. This health data collector or access point device sends the data again to the main server operated in a hospital or health care organization. The health server control continuously the input data and sends an alarm signal to the assigned. doctor and responsible persons using cellular SMS when any dangerous events occur. This wrist type health check device has an embedded linux OS using Intel PAX255 MPU. The developed U-Health system is applicable for checking patients health in remote at home. And their family or related persons in remote site can check the patients health status at any time. They can be assured by receiving SMS record and alarm of emergency case which is transmitted from the health server.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2019.05a
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• pp.238-241
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• 2019

In this paper, a "Vehicle Analysis System(VAS) using cloud and data mining" is proposed that store all the sensor data measured in the vehicle in the cloud, analyze the stored data using the classification model, and provide the analyzed data in real time to the driver's display. The VAS consists of two modules. First, Sensor Data Communication Module(SDCM) stores the sensor data measured in the vehicle in a table of the cloud server and transfers the stored data to the analysis module. Second, Sensor Data Analysis Module(SDAM) analyzes the received data using the genetic algorithm and provides analyzed result to the driver in real time. The VAS stores sensor data collected in the vehicle in the cloud server without accumulating it in the vehicle, and stored data is analyzed in the cloud server, so that the sensor data can be quickly and efficiently managed without overloading the vehicle. In addition, the information desired by the driver can be visualized on the display, thereby increasing the stability of the autonomous vehicle.