• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1797-1801
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• 2005

SLAM(Simultaneous localization and mapping) and AI(Artificial intelligence) have been active research areas in robotics for two decades. In particular, localization is one of the most important issues in mobile robot research. Until now expensive sensors like a laser sensor have been used for the mobile robot's localization. Currently, as the RFID reader devices like antennas and RFID tags become increasingly smaller and cheaper, the proliferation of RFID technology is advancing rapidly. So, in this paper, the smart floor using passive RFID tags is proposed and, passive RFID tags are mainly used to identify the mobile robot's location on the smart floor. We discuss a number of challenges related to this approach, such as RFID tag distribution (density and structure), typing and clustering. In the smart floor using RFID tags, because the reader just can senses whether a RFID tag is in its sensing area, the localization error occurs as much as the sensing area of the RFID reader. And, until now, there is no study to estimate the pose of mobile robot using RFID tags. So, in this paper, two algorithms are suggested to. We use the Markov localization algorithm to reduce the location(X,Y) error and the Kalman Filter algorithm to estimate the pose(q) of a mobile robot. We applied these algorithms in our experiment with our personal robot CMR-P3. And we show the possibility of our probability approach using the cheap sensors like odometers and RFID tags for the mobile robot's localization on the smart floor.

• Transactions on Electrical and Electronic Materials
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• v.16 no.1
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• pp.16-19
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• 2015

A wearable sensing ECG T-shirt for ubiquitous vital signs sensing is proposed. The sensor system consists of a signal processing board and capacitive sensing electrodes which together enable measurement of an electrocardiogram (ECG) on the human chest with minimal discomfort. The capacitive sensing method was employed to prevent direct ECG measurement on the skin and also to provide maximum convenience to the user. Also, low power integrated circuits (ICs) and passive electrodes were employed in this research to reduce the power consumption of the entire system. Small flexible electrodes were placed into cotton pockets and affixed to the interior of a worn tight NIKE Pro combat T-shirt. Appropriate signal conditioning and processing were implemented to remove motion artifacts. The entire system was portable and consumed low power compared to conventional ECG devices. The ECG signal obtained from a 24 yr. old male was comparable to that of an ECG simulator.

• Journal of the Korea Society of Computer and Information
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• v.23 no.9
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• pp.113-122
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• 2018

In this paper, IoT(Internet of things) technology, which is the core of the 4th industrial revolution, was applied to the study of reduction of consumption current. The IoT is a sensor that collects data, a sensor communication, a gateway that processes and stores the collected data. Data application of IoT technology is applied to smart home, smart city, healthcare, smart factory, etc. and it needs to be applied to various industrial fields. By sensing the location of the sensor device, the specific functions of the gateway and the platform are turned ON and OFF to reduce the consumption current of the equipment during the OFF period. When the sensor device accesses the gateway, the specific function of the gateway is turned ON and When the device is separated from the gateway, it senses the sensitivity of the wireless signal and automatically turns off the certain functions. As a resurt, it has reduced the consumption of current. In this paper, we propose a novel system for detecting the location of sensor devices by applying IoT technology. The system implementation is realized by software based, and defines the requirements for the implementation of the sensor device gateway. The gateway automatically detects the location, movement of the device and performs necessary functions. Finally verifies the automatic detection performance of the gateway according to the location of the device. It will contribute greatly to the development of the smart city and office.

• ETRI Journal
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• v.45 no.4
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• pp.603-614
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• 2023

Advancements in remote medical technologies and smart devices have led to expectations of contactless rehabilitation. Conventionally, rehabilitation requires clinicians to perform routine muscle function assessments with patients. However, assessment results are difficult to cross-reference owing to the lack of a gold standard. Thus, the application of remote smart rehabilitation systems is significantly hindered. This study analyzes the factors affecting the real-time evaluation of muscle function based on biometric sensor data so that we can provide a basis for a remote system. We acquired real clinical stroke patient data to identify the meaningful features associated with normal and abnormal musculature. We provide a system based on these emerging features that assesses muscle functionality in real time via streamed biometric signal data. A system view based on the amount of data, data processing speed, and feature proportions is provided to support the production of a rudimentary remote smart rehabilitation system.

• Science of Emotion and Sensibility
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• v.8 no.3
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• pp.213-220
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• 2005

The purpose of this study is to develop a modular model of smart clothing which can integrate various digital devices in clothing, maintaining the inherent attribute of clothing. For achieving this purpose, several technological devices for the smart clothing for listening to music, bio-monitoring, and environment monitoring were developed, through multidisciplinary cooperation. As the result, total four design prototypes of smart sportswear(trekking wear, jogging wear) for the application of entertainment and health care were suggested.

• International journal of advanced smart convergence
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• v.7 no.3
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• pp.23-36
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• 2018

In wireless communication, efficient spectrum usage is an issue that has been an attractive research area for many technologies. Recently new technologies innovations allow compact radios to transmit with power efficient communication over very long distances. For example, Low-Power Wide Area Networks (LPWANs) are an attractive emerging platform to connect the Internet-of-Things (IoT). Especially, LoRa is one of LPWAN technologies and considered as an infrastructure solution for IoT. End-devices use LoRa protocol across a single wireless hop to communicate to gateway(s) connected to the internet which acts as a bridge and relays message between these LoRa end-devices to a central network server. The use of the (ISM) spectrum sharing for such long-range networking motivates us to implement spectrum sensing testbed for cognitive radio network based on LoRa and GNU radio. In cognitive radio (CR), secondary users (SUs) are able to sense and use this information to opportunistically access the licensed spectrum band in absence of the primary users (PUs). In general, PUs have not been very receptive of the idea of opportunistic spectrum sharing. That is, CR will harmfully interfere with operations of PUs. Subsequently, there is a need for experimenting with different techniques in a real system. In this paper, we implemented spectrum sensing for cognitive radio networks based on LoRa and GNU Radio, and further analyzed corresponding performances of the implemented systems. The implementation is done using Microchip LoRa evolution kits, USRPs, and GNU radio.

• IEIE Transactions on Smart Processing and Computing
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• v.3 no.4
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• pp.221-225
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• 2014

Low power RF devices, such as RFID and Zigbee, are important for ubiquitous sensing. These devices, however, are powered by portable energy sources, such as batteries, which limits their use. To mitigate this problem, this study developed RF energy harvesting with W-CDMA for a low power RF device. Diodes are required with a low turn on voltage because the diode threshold is larger than the received peak voltage of the rectifying antenna (rectenna). Therefore, a Schottky diode HSMS-286 was used. A prototype of RF energy harvesting device showed the maximum gain of 5.8dBi for the W-CDMA signal. The 16 patch antennas were manufactured with a 10 dielectric constant PTFT board. In low power RF devices, the transmitter requires a step-up voltage of 2.5~5V with up to 35 mA. To meet this requirement, the Texas Instruments TPS61220 was used as a low input voltage step-up converter. From the evaluated result, the achievable incident power of the rectenna at 926mV to operate Zigbee can be obtained within a distance of 12m.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.06a
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• pp.1034-1039
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• 2005

SALM(Simultaneous localization and mapping) and AI(Artificial intelligence) have been active research areas in robotics for two decades. In particular, localization is one of the most important tasks in mobile robot research. Until now expensive sensors such as a laser sensor have been used for mobile robot localization. Currently, the proliferation of RFID technology is advancing rapidly, while RFID reader devices, antennas and tags are becoming increasingly smaller and cheaper. So, in this paper, the smart floor using passive RFID tags is proposed and, passive RFID tags are mainly used for identifying location of the mobile robot in the smart floor. We discuss a number of challenges related to this approach, such as tag distribution (density and structure), typing and clustering. In the smart floor using RFID tags, the localization error results from the sensing area of the RFID reader, because the reader just knows whether the tag is in the sensing range of the sensor and, until now, there is no study to estimate the heading of mobile robot using RFID tags. So, in this paper, two algorithms are suggested to. The Markov localization method is used to reduce the location(X,Y) error and the Kalman Filter method is used to estimate the heading($\theta$) of mobile robot. The algorithms which are based on Markov localization require high computing power, so we suggest fast Markov localization algorithm. Finally we applied these algorithms our personal robot CMR-P3. And we show the possibility of our probability approach using the cheap sensors such as odometers and RFID tags for mobile robot localization in the smart floor

• Journal of Sensor Science and Technology
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• v.21 no.2
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• pp.103-108
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• 2012

Radiofrequency(RF) signal is a key medium to the most of the present wireless communication devices including RF identification devices(RFID) and smart sensors. However, the most critical barrier to overcome in RFID application is in the failure rate in detection. The most notable improvement in the detection was from the introduction of EPC Class1 Gen2 protocol, but the fundamental problems in the physical properties of the RF signal drew less attention. In this work, we focused on the physical properties of the RF signal in order to understand the failure rate by noting the existence of the ground planes and noise sources in the real environment. By using the mathematical computation software, Maple, we simulated the distribution of the electromagnetic field from a dipole antenna when ground planes exist. Calculations showed that the dark area can be formed by interference. We also constructed a test system to measure the failure rate in the detection of a RFID transponder. The test system was composed of a fixed RFID reader and an EPC Class1 Gen2 transponder which was attached to a scanner to sweep in the x-y plane. Labview software was used to control the x-y scanner and to acquire data. Tests in the laboratory environment showed that the dark area can be as much as 43 %. One who wants to use RFID and smart sensors should carefully consider the extent of the dark area.

• Journal of the Korean Society of Clothing and Textiles
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• v.45 no.4
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• pp.674-684
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• 2021

Recent advances in electronic technology have engendered a need for research on the use of smart materials in clothing. Electro-conductive fibers are expected to be a crucial element of wearable devices. Therefore, in this study, we have attempted to develop electro-conductive threads and cables using silver nanowires. Based on the characteristics of silver nanowire, in which electro-conductivity can be imparted via heat treatment, we prepared conductive threads by coating nylon yarn with silver nanowires and curing at temperatures of 140℃, 150℃, and 160℃. Conductive threads cured at 140℃ had the highest conductivity, followed by threads cured at 160℃ and 150℃ respectively. The order of the electrical conductivity of the threads after tensile testing was consistent with the original order of the conductivity of the threads. When we evaluated the sensing performance of electro-conductive cables fabricated from these threads, the cables manufactured from threads cured at 140℃ and 160℃ were found to function normally within temperature and humidity sensors. All the cables operated normally in illuminance and electrocardiogram sensors. Thus, we believe that threads made of silver nanowire have sufficient electrical conductivity to be utilized as wearable sensors.