• Proceedings of the KIEE Conference
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• 1995.11a
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• pp.95-98
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• 1995

In this paper, a good fault location algorithm will be presented, which uses novel signal processing techniques and takes a new paradigm to overcome some drawbacks of the conventional methods. The main feature of the method is that it uses the high frequency components in fault signal and considers the influence of the source network by using a traveling wave concept.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.2
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• pp.163-168
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• 2008

Navigation system based on indoor location estimation is one of the core technologies in mobile robot systems. Wireless sensor network has great potential in the indoor location estimation due to its characteristics such as low power consumption, low cost, and simplicity. In this paper we present an algorithm to estimate the indoor location of mobile robot based on wireless sensor network and fuzzy modeling. ZigBee-based sensor network usually uses RSSI(Received Signal Strength Indication) values to measure the distance between two sensor nodes, which are affected by signal distortion, reflection, channel fading, and path loss. Therefore we need a proper correction method to obtain accurate distance information with RSSI. We develop the fuzzy distance models based on RSSI values and an efficient algorithm to estimate the robot location which applies to the navigation algorithm incorporating the time-varying data of environmental conditions which are received from the wireless sensor network.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.10A
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• pp.796-806
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• 2009

This paper presents the method of emergency warning system operation based on T-DMB and the design of T-DMB AEAS receiver model. The proposed receiver model compares the geographical location of emergency with the location of DMB transmitting station from T-DMB broadcasting signal and classifies the receiver location into alert region, neighboring region and non-alert region and transmits the emergency alert message according to each region. The geographical location of emergency can be obtained from FIG 5/2 EWS data field for AEAS message and the location of DMB transmitting station can be estimated from either the latitude and the longitude in main identifier and sub identifier in FIG 0/22 data filed for TII(Transmitter Identification Information) or TII distribution database. In our experiment, we implemented the proposed receiver model with display section, storage section, DMB module for receiving broadcasting signal and control section and performed test emergency alert broadcasting using T-DMB signal generator.

• Journal of Korea Multimedia Society
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• v.11 no.2
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• pp.182-196
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• 2008

The location estimation using sensor network has been considerably researched. The methods taking the differences of the forms of location estimation between indoors and outdoors into consideration have been studied. While it is possible for outdoor location to be estimated because outdoor location estimation has a consistent distribution during unit period through the value of RSSI(Received Signal Strength Indication) on outdoor location estimation, Indoor location estimation is difficult since multi-path and interference indoors are higher than those outdoors and indoor location estimation can be affected by other factors. In this paper, we revise the information of RSSI changed by multi-path and interference through the Moving Average method and K-means algorithm and propose the method of estimation for the value of RSSI with reliability in the group of signals received during unit period. We also suggest the way to put some weights on fixed nodes in network using a snooping node on location estimation and then evaluate the efficiency of location awareness as compared with the existing method by implementing proposed method on system through the reconfiguration of network.

• Journal of Korea Society of Industrial Information Systems
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• v.17 no.4
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• pp.1-7
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• 2012

This paper proposes a new indoor location recognition system using a ZigBee network and a global positioning system(GPS). The proposed location recognition system applies GPS values that are mainly used for outdoor location recognition, to indoor location recognition; hence the techniques conventionally separated for the indoor and outdoor location recognition are integrated into one location recognition technique. The proposed system recognizes a location using the distance between nodes. Although the distance between nodes can be calculated by measuring the strength of the received ZigBee signals, generally the measured distance is not accurate and has high error rates since the strength of the ZigBee signals is different depending on the distance. In order to reduce the error rate, we have subdivided the output power of the received ZigBee signals into five levels. When a moving node generates a signal, each fixed node transmits the received signal strength and its own GPS information to other nodes, so the moving node can find its own accurate location in terms of the received signals.

• Journal of Digital Convergence
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• v.20 no.5
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• pp.317-322
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• 2022

In general, life jackets are worn by people in critical situations on the water to rise to the surface without falling into water, and life jackets simply serve to prevent sinking, but do not actively help rescue disaster areas in critical situations early. In order to solve this problem, a device that automatically generates a distress signal in an emergency situation was developed. When the survivor is in hand for a while, the distress signal generator is automatically separated from the life jacket, allowing information such as location values and other information to be transmitted wirelessly and a rescue signal using LED light. As a result of the experiment, when submerged in water, the life jacket and the distress signal generator were automatically separated, and the result of wireless transmission of the coordinate value of the location received by the GPS was confirmed. By using this, the location of the distress or missing person can be identified, which can be quickly replaced in case of an emergency

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.05a
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• pp.345-347
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• 2016

Recently location based services is being expanded into the indoor service that can not access to the outdoor location informations, such as GPS. Thus, the research and development of an indoor positioning system with BLE(Bluetooth Low Energy) iBeacon technology has expanded. However, RSSI (Received Signal Strength Indicator) that is used as the distance information between the terminal and for positioning iBeacon signal has a problem in that distortion occurs, information such as the signal attenuation and the delay due to the characteristics of radio waves. In this paper, we propose a reliable method of verifying iBeacon signal with the signal distortion problems for reliable indoor positioning systems.

• Journal of IKEEE
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• v.14 no.1
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• pp.25-32
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• 2010

In this paper, we analyze the location accuracy of real-time locating systems (RTLS) in multipath environments, where the RTLS complies with an ISO/IEC 24730-2 international standard. RTLS readers should have an ability not only to recover the transmitted signal but also provide arrival timing information from the received signal. In the multipath environments, in general, the transmitted signal goes through both direct and indirect paths, and then it becomes some distorted form of the transmitted signal. Such multipath components have a critical effect on deciding the first arrival timing of the received signal. To analyze the location error of the RTLS in the multipath environments, we assume two multipath components without considering an additive white Gaussian noise. Through the simulation and real test results, we confirm that the location error does not occur when the time difference between two paths is more than 1.125Tc, but the location error of about 2.4m happens in case of less than 0.5Tc. In particular, we see that the resolvability of two different paths depends largely on the phase difference for the time difference of less than 1Tc.

• Journal of the Korean Society for Railway
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• v.19 no.5
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• pp.585-591
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• 2016

Recently, indoor location detection has become an important area in the IoT (Internet of Things) environment for various indoor location-based services. In this paper, our proposed method shows that a virtual region can be divided electromagnetically according to specific facilities or services in various IoT application areas called zones. The MLP (Multi-Layer Perceptron) method is applied to recognize the service zone at the current position. The MLP utilized an RSSI (Received Signal Strength Indicator) signal of the BLE (Bluetooth Low Energy) Beacon as input data and made decisions to affiliate the zone of the current region as output. In order to verify the proposed method, we constructed an experimental environment similar in size to an actual rail station using four of the beacon and two zones.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.45 no.5
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• pp.38-47
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• 2008

The most commonly used location recognition system is the GPS-based approach. However, the GPS is inefficient for an indoor or urban area where high buildings shield the satellite signals. To overcome this problem, this paper propose the indoor positioning method using wavelet and neural network. The basic idea of proposed method is estimated the location using the received signal strength from wireless APs installed in the indoor environment. Because of the received signal strength of wireless radio signal is fluctuated by the environment factors, a feature that is strength of signal noise and error and express the time and frequency domain is need. Therefore, this paper is used the wavelet coefficient as the feature. And the neural network is used for estimate the location. The experiment results indicate 94.6% an location recognition rate.