• International Journal of Advanced Culture Technology
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• v.2 no.2
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• pp.1-6
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• 2014

In this paper, we propose an intelligent streetlight system that has a complex sensor module of temperature, humidity, luminance and motion detection and controlled by the fuzzy logic based central monitoring system in order to get flexible and precise manipulation of the streetlight system in USN environment. The proposed streetlight system provides low power consumption and high efficiency by using sensed data from the complex sensor module, which were collected, processed, and analyzed by the fuzzy logic based central monitoring system. The performance of the proposed streetlight system is to be evaluated by a simulation study in terms of power savings and safety at the fields constructed as a test-bed under several suggested scenarios. Finally, we know that the proposed intelligent streetlight system can maximize the energy savings efficiently with the fuzzy logic based central monitoring system and selective remote dimming control by connecting it to the wireless ubiquitous sensor network (USN) using a Zigbee module.

• Proceedings of the KIEE Conference
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• 2006.10c
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• pp.470-472
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• 2006

Sensor networks are the results of convergence of very important technologies such as wireless communication and micro electromechanical systems. In recent years, sensor networks found a wide applicability in various fields such as environment and health, industry scene system monitoring, etc. A very important step for these many applications is pattern classification and recognition of data collected by sensors installed or deployed in different ways. But, pattern classification and recognition are sometimes difficult to perform. Systematic approach to pattern classification based on modem learning techniques like Multivariate Gaussian mixture models, can greatly simplify the process of developing and implementing real-time classification models. This paper proposes a new recognition system which is hierarchically composed of many sensor nodes having the capability of simple processing and wireless communication. The proposed system is able to perform context classification of sensed data using the Multivariate Gaussian function. In order to verify the usefulness of the proposed system, it was applied to intelligent dust collecting system.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.54 no.7
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• pp.437-442
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• 2005

In order to realize the speed control of an induction motor, the information of the rotor speed is needed. So the speed sensor as an encoder or a pulse generator is used to obtain it. But the use of speed sensor occur the some problems in the control system of an induction motor. To solve the problems, the appropriate speed estimation algorithm is used instead of the speed sensor. Also there is the limitation to improve the speed control performance of an induction motor using the existing speed estimation algorithm. Therefore, in this paper, intelligent speed estimator using Fuzzy-Neural systems as adaptive laws in Model Reference Adaptive System is proposed so as to improve the existing estimation algorithm and ,using the rotor speed estimated by the Proposed estimator, the speed control of an induction motor without speed sensor is performed. The computer simulation and the experiment is executed to prove the performance of the speed control system usinu the proposed speed estimator.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.5
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• pp.481-486
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• 2007

Wireless Sensor Network(WSNs) consists of small sensor nodes with sensing, computation, and wireless communication capabilities. The large number of sensor nodes in a WSN means that there will often be some nodes which give erroneous sensor data owing to several reasons such as power shortage and transmission error. Generally, these sensor data are gathered by a sink node to monitor and diagnose the current environment. Therefore, this can make it difficult to get an effective monitoring and diagnosis. In this paper, to overcome the aforementioned problems, intelligent sensor data validation method based on PCA(Principle Component Analysis) is utilized. Furthermore, a practical implementation using embedded system is given to show the feasibility of the proposed scheme.

• Current Optics and Photonics
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• v.6 no.3
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• pp.297-303
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• 2022

Multiple fiber Bragg gratings (FBGs) have been proposed and demonstrated for gas-flow measurements in a flow channel, using the temperature-difference method. This sensor consists of two FBG temperature sensors and two coil heaters. Coil heaters are used to heat the FBGs. The flow rate of the gas can be obtained by monitoring the difference in the Bragg-wavelength shifts of the two FBGs, which has features that exclude the effect of temperature fluctuations. In this study, experiments are conducted to measure the wavelength shift based on the flow rate, and to evaluate the gas-flow rate in a gas tube. Experimental results show that the sensor has a linear characteristic over a flow-rate range from 0 to 25 ℓ/min. The measured sensitivity of the sensor is 3.2 pm/(ℓ/min) at a coil current of 120 mA.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2011.05a
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• pp.831-834
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• 2011

This paper is intended as performance verification of efficient container door Open/Closed detection mechanism for Container Security Device(ConTracer) to container cargo transportation. Container door Open/Closed detection mechanism using Reed sensor is important to satisfies the US Department of homeland security customs and border protections requirements to many types of container door. Also, Verify that the container door is configured correctly and that you can check the illegal opening. In this article, Performance valuation of this Contacer on reed sensor has been verified through field test for each other 30 containers. Once the improvement has been made, we are suggest that propose skills will meet the highest standards for container security safety.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2008.06a
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• pp.685-686
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• 2008

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2009.10a
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• pp.297-298
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• 2009

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.10
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• pp.1051-1056
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• 2014

In this paper, we introduce an intelligent robotic arc welding system which exploits sensors like as LVS (Laser Vision Sensor), Hall effect sensor, voltmeter and so on. The use of industrial robot is saturated because of its own limitation, and one of the major limitations is that industrial robot cannot recognize the environment. Lately, sensor-based environmental awareness research of the industrial robot is performed actively to overcome such limitation, and it can expand application field and improve productivity. We classify the sensor-based intelligent arc welding robot system by the goal and the sensing data. The goals can be categorized into detection of a welding start point, tracking of a welding line and correction of a torch deformation. The Sensing data can be categorized into welding data (i.e. current, voltage and short circuit detection) and displacement data (i.e. distance, position). This paper covers not only the explanation of the each category but also its advantage and limitation.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2007.11a
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• pp.386-390
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• 2007

센서 네트워크 시스템은 한정된 자원을 갖는 센서노드들을 광대한 영역에 설치하여 새로운 정보를 수집 하고 모니터링 하는 기능을 한다. 센서 노드와 센서의 고장(Sensor node faulty or Sensor faulty)은 열악한 설치 환경이나 제한된 리소스에 의해 종종 발생 되는데 이들 고장은 네트워크 내에서 요구되는 양질의 서비스 제공에 많은 문제를 가져온다. 본 논문에서는 센서 노드의 고장 검출 알고리즘으로 알려져 있는 Consensus 알고리즘과 센서노드에서 사용되는 센서의 고장을 검출할 수 있는 localized faulty sensor detection 알고리즘을 혼합하여 시스템에 안정된 서비스를 제공할 수 있는 방법을 제안하며 실제 시뮬레이션과 제작된 실험장치에 적용함으로써 그 유용성을 확인하고자 한다.