• Proceedings of the Korea Information Processing Society Conference
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• 2009.04a
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• pp.585-588
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• 2009

건물내의 열을 온도 센서를 통해 모니터링함으로써 발생되는 온도 데이터의 양은 온도 센서의 정밀도가 향상되고 센서의 수가 증가함에 따라 기존의 화재감시시스템이나 공기조화냉동시스템에서 발생하는 것과는 비교할 수 없이 증가하게 된다. 이 과정에서 화재를 감시하기 위하여 유용한 데이터만을 처리해 데이터베이스화하고, 화재 예방에 활용하기 위해 온도 데이터의 효과적인 처리 방법을 연구함으로써 보다 작은 시스템의 구축으로도 안정적인 화재 감시 및 예방이 가능한 방안을 제시한다.

• Journal of IKEEE
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• v.22 no.2
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• pp.250-257
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• 2018

In this paper, a smart bus system that automates public bus traffic payment by applying beacon and computer vision and provides bus route information, real-time location information, getting off alarm is proposed. By using the beacon to recognize busses near the stop and to board the bus to be boarded, this system automatically processes the payment when boarding by using the distance from the beacon and the information provided by the beacon and the face comparison. After the payment processing, the system provides the route information of the boarded bus and the real-time bus location information to the user, and when the user sets an alarm using these informations, the alarm is activated when the bus leaves the bus stop.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2488-2491
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• 2000

A Neural network is possible to nonlinear function mapping and parallel processing. Therefore It has been developing for a Diagnosis system of nuclear plower plant. In general Neural Networks is a static mapping but Dynamic Neural Network(DNN) is dynamic mapping. When a fault occur in system, a state of system is changed with transient state. Because of a previous state signal is considered as a information. DNN is better suited for diagnosis systems than static neural network. But a DNN has many weights, so a real time implementation of diagnosis system is in need of a rapid network architecture. This paper presents a algorithm for RCP monitoring Alarm diagnosis system using Self Dynamic Neural Network(SDNN). SDNN has considerably fewer weights than a general DNN. Since there is no interlink among the hidden layer. The effectiveness of Alarm diagnosis system using the proposed algorithm is demonstrated by applying to RCP monitoring in Nuclear power plant.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.05a
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• pp.411-414
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• 2009

Many victims and property damages are caused in fires every year. In this paper, intelligent fire-detection systems with embedded fire-detection algorithms for early fire detection and alarm is proposed to reduce fire damages by using image processing technique, high speed digital signal processor(DSP) technique, and information technique. The fire detection algorithms used for the proposed systems consist of flame and smoke detection algorithms. If flame or smoke is detected respectively, the corresponding alarm signal can be transferred to management computer. And if flame and smoke is detected simultaneously, the fire alarm signal shall be generated. Through several experiments in the physical environment, it is shown that the proposed system works well without malfunction.

• The Journal of the Acoustical Society of Korea
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• v.15 no.1E
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• pp.5-19
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• 1996

This paper proposes a loose part monitoring system (LPMS) design with a signal processing method based on fuzzy logic. Considering fuzzy characteristics of metallic impact waveform due to not only interferences from various types of noises in an operating nuclear power plant but also complex wave propagation paths within a monitored mechanical structure, the proposed LPMS design incorporates the comprehensive relation among impact signal features in the fuzzy rule bases for the purposes of alarm discrimination and impact diagnosis improvement. The impact signal features for the fuzzy rule bases include the rising time, the falling time, and the peak voltage values of the impact signal envelopes. Fuzzy inference results based on the fuzzy membership values of these impact signal features determine the confidence level data for each signal feature. The total integrated confidence level data is used for alarm discrimination and impact diagnosis purposes. Through the perpormance test of the proposed LPMS with mock-up structures and instrumentation facility, test results show that the system is effective in diagnosis of the loose part impact event(i.e., the evaluation of possible impacted area and degree of impact magnitude) as well as in suppressing false alarm generation.

• Journal of the Institute of Convergence Signal Processing
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• v.19 no.4
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• pp.192-198
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• 2018

Recently, the use of drone has been increasing rapidly in many ways. A drone can capture remote objects efficiently so it is suitable for surveillance and security systems. This paper discusses three methods for detecting moving vehicles using a drone. We compare three target detection methods using a background frame, preceding frames, or moving average frames. They are subtracted from a current frame. After the frame subtraction, morphological filters are applied to increase the detection rate and reduce the false alarm rate. In addition, the false alarm region is removed based on the true size of targets. In the experiments, three moving vehicles were captured by a drone, and the detection rate and the false alarm rate were obtained by three different methods and the results are compared.

• Proceedings of the Korean Institute of Communication Sciences Conference
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• 1986.04a
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• pp.169-176
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• 1986

The function of administration and maintenance on the TDX-1 digital switching system, which have been developed in ETRI(Electrotechnology and Telecommunications Research Institute), are reported. In administration, the functions of charging, statistics, data handling, man-mechine communication and I/0 device control are described. In maintenance, the function of fault detection and processing, status handling and alarm described.

• Proceedings of the Korea Information Processing Society Conference
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• 2015.10a
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• pp.1078-1079
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• 2015

본 논문에서는 신호 시제 논리 명세를 통하여 민방위 경보음을 정형적으로 명세한다. 논리를 기반으로 한 정형 명세는 비정형 명세에 비하여 분명하고, 간결하며, 기계처리가 가능한 이점을 제공한다. 민방위 경보음에 대한 시간의 흐름에 따른 주파수의 변화를 그래프로 그린 후에 이를 신호시제 논리로 명세하고자 한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2010.11a
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• pp.1506-1509
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• 2010

사용자가 버스정류장과 알람반경을 선택하면 미리 설정한 옵션에 따라 소리 또는 진동으로 사용자에게 알려준다. 안드로이드 2.1 플랫폼에서 GPS센서와 SQLite3 DataBase, Wifi 등을 컨트롤 할 수 있는 API 들을 사용하여 개발하였다.

• Journal of the Institute of Electronics and Information Engineers
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• v.49 no.9
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• pp.172-180
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• 2012

In multi-static sonar for detecting an underwater target, received signals contain the target echo, reverberation and clutter. Clutter and reverberation are main causes of increasing the false alarm rate. MRAL classifies received signals according to the spatial similarity, and it regards classified signal as reflected signals from a reflector. MRAL reduces the false alarm rate this way. However, the results of MRAL can have localization errors. In this paper, an MRAL post processing algorithm is proposed to reduce the localization errors with the least square (LS) method.