• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.5
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• pp.713-718
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• 2014

DC urban railway power system consists of DC power network and AC power network. The DC power network supplies electric power to railway vehicles and the AC power network supplies electric power to station electric equipment. Recently, because of power consumption reduction and peak load shaving, intelligent measurement of regenerative energy and renewable energy adapted on DC urban railway is required. For this reason, DC smart metering system for DC power network shall be developed. Therefore, in this paper, DC voltage sensor, current sensor, and DC smart meter were developed and evaluated by performance test. DC voltage sensor was developed for measuring standard voltage range of DC urban railway, and DC current sensor was developed as hall effect split core type in order to install in existing system. DC smart meter possesses function of general intelligent electric power meter, such as measuring electricity and wireless communication etc. And, DC voltage sensor showed average 0.17% of measuring error for 2,000V/50mA, and current sensor showed average 0.21% of measuring error for ${\pm}2,000V/{\pm}4V$ in performance test. Also DC smart meter showed maximum 0.92% of measuring error for output of voltage sensor and current sensor. In similar environment for real DC power network, measuring error rate was under 0.5%. In conclusion, accuracy of DC smart metering system was confirmed by performance test, and more detailed performance will be verified by further real operation DC urban railway line test.

• Electronics and Telecommunications Trends
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• v.34 no.5
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• pp.14-25
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• 2019

As the Internet of Things, artificial intelligence and big data have received a lot of attention as key growth engines in the era of the fourth industrial revolution, data acquisition and utilization in mobile, automotive, robotics, manufacturing, agriculture, health care and national defense are becoming more important. Due to numerous data-based industrial changes, demand for sensor technologies is exploding, especially for intelligent sensor technologies that combine control, judgement, storage and communication functions with the sensors's own functions. Intelligent sensor technology can be defined as a convergence component technology that combines intelligent sensor units, intelligent algorithms, modules with signal processing circuits, and integrated plaform technologies. Intelligent sensor technology, which can be applied to variety of smart IT convergence services such as smart devices, smart homes, smart cars, smart factory, smart cities, and others, is evolving towards intelligent and convergence technologies that produce new high-value information through recognition, reasoning, and judgement based on artificial intelligence. As a result, development of intelligent sensor units is accelerating with strategies for miniaturization, low-power consumption and convergence, new form factor such as flexible and stretchable form, and integration of high-resolution sensor arrays. In the future, these intelligent sensor technologies will lead explosive sensor industries in the era of data-based artificial intelligence and will greatly contribute to enhancing nation's competitiveness in the global sensor market. In this report, we analyze and summarize the recent trends in intelligent sensor technologies, especially those for four core technologies.

• The Journal of the Korea Contents Association
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• v.17 no.12
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• pp.138-147
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• 2017

In this paper, we introduce smart multi-sensor and environment monitoring system for managing growth and development of the agricultural produces. This system is able to help to collect the sensor information about the growing environment and to monitor in wired and wireless environments. Existing systems installed each kinds of sensor to gather information. In this case, installation cost was incurred about each sensor and the position of sensor set up manually. Therefore, this paper designed and implemented smart multi-sensor that simplify sensors in order to minimize the cost for installing each sensor. In addition, this system is able to monitor position and data information of smart multi-sensor using RFID communication

• Journal of the Korea Society of Computer and Information
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• v.21 no.5
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• pp.127-133
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• 2016

In this paper, an intelligent dimming control system is designed and implemented with the human visual response function using CDS sensor, PIR sensor and temperature sensor, etc. The proposed system is designed to detect a moving object by PIR sensor and to control the LED dimming considering the human visual response. Also, the dimming of LED light can modulate on the app, and simultaneously control dimming in real-world environments with smart phone app. A high-temperature warning or a fire hazard information is transmitted to user's smart phone according to sensor values and Data graph are provided as part of data visualization. Connecting the hardware controller, the proposed intelligent smart dimming control system is expected to contribute to the power reduction interior LED, smart grid building and saving home combining with internet of things.

• Journal of Sensor Science and Technology
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• v.26 no.5
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• pp.301-305
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• 2017

This paper presents a wearable human health-monitoring band. The band consists of a body temperature detector (BTD) and a hear rate detector (HRD). The BTD and HRD are realized using an inkjet-printed flexible temperature sensor and a commercial heart rate sensor module, respectively. The sensitivity of the fabricated BTD was found to be $-31/^{\circ}C$ with a linearity of 99.82%. The HRD using the commercial heart rate sensor module has a good performance with a standard deviation of 0.85 between the data of a commercial smart watch and the fabricated HRD.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.10a
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• pp.861-864
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• 2014

Recently, the growth control of crops is developed as one of essential factors for smart agriculture based on ubiquitous sensor network. It is reason of easiability for control of product quantity and management of product quality. In this paper, scenario of smart agriculture is investigated for domestic and foreign countries and currently used sensor data technologies is compared to support a series of technological systemization works for sensor data field of smart agriculture. The results of this paper can be used as basic data for smart agriculture standardizations which is currently under progress at domestic and abroad.

• IEIE Transactions on Smart Processing and Computing
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• v.6 no.2
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• pp.71-75
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• 2017

In this paper, a smart optical fingerprint sensor technology that is robust against faked fingerprints. A new lens and prism accurately detect fingerprint ridges and valleys that are needed to express a fingerprint's intrinsic characteristics well. The proposed technology includes light path configuration and an optical fingerprint sensor that can effectively identify faked fingerprint features. Results of simulation show the smart optical fingerprint sensor classifies the characteristics of faked fingerprints made from silicone, gelatin, paper, and rubber, and show that the proposed technology has superior detection performance with faked fingerprints, compared to the existing infrared discrimination method.

• Journal of Multimedia Information System
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• v.5 no.3
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• pp.215-220
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• 2018

This work presents a smart water quality sensor for hydroponic plant growing applications. The proposed sensor can effectively measure pH level and electrical conductivity of the water solution. The micro-controller incorporated in the sensor processes the raw sensor data, and converts it into a readable format. In addition, through the mobile interface realized using a WiFi module, the sensor can send data to the web server database that collects and stores the data. The data stored in the web server can be accessed by a personal computer or smart phone. The prototype sensor has been implemented, and the operations have been verified under an actual hydroponic plant growing application.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2006.04a
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• pp.21-28
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• 2006

Structural health monitoring (SHM) is a new technology that will be increasingly applied at the industrial field as a potential approach to improve cost and convenience of structural inspection. Recently, the development of smart sensor is very active for real application. This study has focused on preparation and application study of SAL sensor. In order to detect elastic wave, smart piezoelectric sensor, SAL, is fabricated by using a piezoelectric element, shielding layer and protection layer. This protection layer plays an important role in a patched network of distributed piezoelectric sensor and shielding treatment. Four types of SAL sensor are designed/prepared/tested, and these details will be discussed in the paper. In this study, SAL sensor can be feasibly applied to perform structural health monitoring and to detect damage sources which result in elastic waves.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.15 no.3
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• pp.73-81
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• 2006

This paper describes our primary study for a new method of recognizing materials, which is need for precision work system. This is a study of dynamic characteristics of smart sensors, new method$(R_{SAI})$ has the sensing ability of distinguishing materials. Experiment and analysis are executed for finding the proper dynamic sensing condition. First, we developed advanced smart sensor. We made smart sensors for experiment. The type of smart sensor is HH type. The smart sensor was developed for recognition of material. Second, we develop new estimation methods that have a sensing ability of distinguish materials. Dynamic characteristics of sensor are evaluated through new recognition index$(R_{SAI})$ that ratio of sensing ability index. Distinguish of object is executed with $R_{SAI}$ method relatively. We can use the $R_{SAI}$ method for finding materials. Applications of this method are finding abnormal condition of object (auto-manufacturing), feeling of object(medical product), robotics, safety diagnosis of structure, etc.