• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.10
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• pp.2177-2184
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• 2012

A different and effective method for indoor positioning system is needed and increased it's importance compare to the outdoor GPS based method. The FingerPrint positioning method is known as a superior method in indoor positioning system that maintains signal strength patterns for RPs(Reference Points) in database and compare the DB with the measured real-time signals on the mobile device. FingerPrint positioning method is necessary to establish an accurate database, but errors can occur by several factors. In this paper, we analyze the signal patterns of each terminal in accordance with connection state of access point and trace that the error in accordance with connection state of access point can be an important error in FingerPrint DB configuration through an experimental case study.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.5
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• pp.1045-1052
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• 2011

Recently, because of complex cultural space, underground space are becoming larger. Therefore, the demand for location-based services is growing. VLC (Visible Light Communication) is based on the LED lighting infrastructure so that suitable LBS (Location-based service) is possible for the targeted places in indoor space. To experiment with indoor LBS by VLC, we measure the identification distance according to variable angles between LED and photo diode. We send the different ASCII code for each LED light, then we found the maximum identification distance is 1.75m from LED lights. From the results of this experiment, we show that indoor navigation is possible.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.3
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• pp.329-334
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• 2011

This paper presents the method for location estimation with obstacle tracking method. A laser scanner is used to implement the system, and we assume that the map information is known. We matches the measurement of the laser scanner to estimate the location of the robot by using sequential monte carlo (SMC) method. After estimating the robot's location, the pose of obstacles are detected and tracked, hence, we can predict the collision risk of them. Finally, we present the experiment results to verify the proposed method.

• 한국IT서비스학회:학술대회논문집
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• 2008.11a
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• pp.567-570
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• 2008

위치 및 지리정보를 활용하여 다양한 정보를 제공하는 위치기반서비스(LBS)가 새롭게 부상하고 있는 가운데 u-City/Town과 더불어 지하 실내 복합문화공간이 활발하게 건설되고 있다. 미래사회에서 얘기하는 물리적 공간의 지능화 유비쿼터스화를 위한 실내 환경에서의 위치기반서비스가 그 중요성을 더해가고 있다. 이에 본 고에서는 위치인식 기술과 더불어 국내 외 위치기반서비스 사업현황을 분석해보고, 실내 환경에 적용 가능한 u-복합문화공간 서비스 모델, 특히 실내 LED 인프라를 이용한 Indoor LBS 서비스를 체계적으로 분석하였다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.10a
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• pp.270-271
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• 2015

Recently, There is Increasing interest in the intelligent services using the Internet of Things indoor positioning technologies that enable the communication of information between the objects. In particular Applications and demand for the indoor location based services using smart devices has made active. An indoor location positioning technology for this purpose BLE (Bluetooth Low Energy) has been a lot of interest in technology increases. If iBeacon of BLE(Bluetooth Low Energy) is made available to provide a signal for the indoor location information measurement then reliability of Indoor location information is lowered by signal interference. In this paper, Proposes a technique for data acquisition method for obtaining reliable position information and reliable position information calculation method from signal information data of iBeacon.

• Journal of Advanced Marine Engineering and Technology
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• v.37 no.8
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• pp.932-938
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• 2013

Recently, the Fingerprint, which is one of the methods of indoor localization using WLAN, has been many studied owing to robustness about ranging error by the diffraction and refraction of radio waves. However, in the signal gathering process and comparison operation for the measured signals with the database, this method requires time consumption and computational complexity. In order to compensate for these problems, this paper presents, based on proposed modified database, WLAN indoor localization algorithm using selective operation of collected signal in real time. The proposed algorithm reduces the configuration time and the size of the data in the database through linear interpolation and thresholding according to the signal strength, the localization accuracy, while reducing the computational complexity, is maintained through selective operation of the signals which are measured in real time. The experimental results show that the accuracy of localization is improved to 17.8% and the computational complexity reduced to 46% compared to conventional Fingerprint in the corridor by using proposed algorithm.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.06a
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• pp.364-367
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• 2007

We combined CC2431(Chipcon, Norway), as the platform for the Indoor Location Tracking, which follows Zigbee/IEEE802.15.4 standards in RSSI (Received Signal Strength Indicator) and Base Station Node and then, embodied Indoor Location Tracking System. CC2431 is composed of the Reference Node that transfer its current position at the designated place and the Blind Node. The Blind node receives the current position(X and Y coordinates) of the Reference Node fields which are being contiguous and also, calculates its current position and transfers it to the Base Station Node. The base station node is used for receiving the current position of blind node and passing its data to the PC as a gateway. We can make sure where is the Blind Node not only from the out-of-the-way place of the server side but from the outside in a real-time.

• 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.

• Proceedings of the Korean Society of Computer Information Conference
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• 2017.07a
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• pp.350-351
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• 2017

스마트폰과 같은 모바일 기기의 발달과 함께 사용자의 위치에 기반한 다양한 서비스가 출현하고 있다. 그중 사용자의 위치를 기준으로하는 길안내 서비스가 가장 대표적이다. GPS에 기반한 실외 중심의 길안내는 다양한 비콘과 WiFi 등의 기술과 함께 실내에서도 길안내 서비스가 가능하도록 해주고 있다. 하지만, 상기의 사용자 위치에 대한 길안내 서비스는 거리에 대한 인식 단계가 세밀하지 못하기에 해당거리별 상세 서비스가 어려운 것이 현실이다. 이에 본 논문에서는 기존 BLE 비콘의 Immediate, Near, Far의 3단계 거리인식을 6단계까지 확장하여 보다 상세한 안내가 가능한 실내 길안내 서비스를 제안한다. 또한 편의적 기능을 위해 목적지 입력 및 길안내가 음성에 기반하여 구동될 수 있도록 구현하였다.

• Proceedings of the KIEE Conference
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• 2009.07a
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• pp.1800_1801
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• 2009

본 논문에서는 실내 환경에서 신호세기를 이용한 RSSI(Received Signal Strength Indication)인식 방법과 신호의 도착 시간 차이를 이용한 TDOA(Time Difference Of Arrival )인식 방법을 이용하여 태그 위치 측정 및 오차 보정 방법을 제안한다. 제안한 방법은 물체 위치 인식을 위해 기존의 제안된 거리에 따라 발생하는 경로손실(Path Loss) 방정식과 신호의 도착 시간차이를 이용하여 태그를 인식한 다음 삼각측량법과 SX 알고리즘을 이용하여 태그의 위치를 측정한다. 또한, 실내 환경의 다양한 오차를 포함하고 있는 태그의 위치 측정 데이터에 대해 확장된 칼만 필터를 사용하여 오차를 보정하는 방법을 제안한다. 마지막으로 몇 개의 시뮬레이션을 통하여 그 응용 가능성을 증명한다.