• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.1
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• pp.43-55
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• 2019

Smart phone based navigation applications are very useful in everyday life. Cost-effective and user friendly navigation can be provided to the user by many applications available in market. Using the Smart phone these navigation applications provide accurate navigation for outdoor locations. But providing an accurate navigation underground space such as subway station is still a challenge. It is hence more convenient and appropriate for mobility services if the visitors could simply view the guidance of the subway station on their mobile phone, wherever and whenever it is needed. This study develops a algorithm for indoor navigation with the help of Augmented Reality(AR) and QR marker code from the entrance to the train platform for users. This indoor navigation uses AR and QR maker codes for two purposes: to provide the user link to the subway station location and to provide the current guidance details to the user. This Smart phone algorithm that uses a smart phone optical tool to decode the QR marker to determine the location information and provide guidance to the AR without indoor Maps. This algorithm also provides a module to guide mobility vulnerable to the Barrier Free route to destination.

• The Journal of Korea Robotics Society
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• v.2 no.1
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• pp.40-47
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• 2007

Recently, with the development of service robots and with the new concept of ubiquitous world, the position estimation of mobile objects has been raised to an important problem. As pre-liminary research results, some of the localization schemes are introduced, which provide the absolute location of the moving objects subjected to large errors. To implement a precise and convenient localization system, a new absolute position estimation method for a mobile robot in indoor environment is proposed in this paper. Design and implementation of the localization system comes from the usage of active beacon systems (based upon RFID technology). The active beacon system is composed of an RFID receiver and an ultra-sonic transmitter: 1. The RFID receiver gets the synchronization signal from the mobile robot and 2. The ultra-sonic transmitter sends out the traveling signal to be used for measuring the distance. Position of a mobile robot in a three dimensional space can be calculated basically from the distance information from three beacons and the absolute position information of the beacons themselves. Since it is not easy to install the beacons at a specific position precisely, there exists a large localization error and the installation time takes long. To overcome these problems, and provide a precise and convenient localization system, a new auto calibration algorithm is developed in this paper. Also the extended Kalman filter has been adopted for improving the localization accuracy during the mobile robot navigation. The localization accuracy improvement through the proposed auto calibration algorithm and the extended Kalman filter has been demonstrated by the real experiments.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.11
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• pp.3950-3969
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• 2021

Radio Frequency (RF)-based indoor localization technologies play significant roles in various Internet of Things (IoT) services (e.g., location-based service). Most such technologies require that all the devices comply with a specified technology (e.g., WiFi, ZigBee, and Bluetooth). However, this requirement limits its application scenarios in today's IoT context where multiple devices complied with different standards coexist in a shared environment. To bridge the gap, in this paper, we propose a cross-technology localization approach, which is able to localize target nodes using a different type of devices. Specifically, the proposed framework reuses the existing WiFi infrastructure without introducing additional cost to localize Non-WiFi device (i.e., ZigBee). The key idea is to leverage the interference between devices that share the same operating frequency (e.g., 2.4GHz). Such interference exhibits unique patterns that depend on the target device's location, thus it can be leveraged for cross-technology localization. The proposed framework uses Principal Components Analysis (PCA) to extract salient features of the received WiFi signals, and leverages Dynamic Time Warping (DTW), Gradient Boosting Regression Tree (GBRT) to improve the robustness of our system. We conduct experiments in real scenario and investigate the impact of different factors. Experimental results show that the average localization accuracy of our prototype can reach 1.54m, which demonstrates a promising direction of building cross-technology technologies to fulfill the needs of modern IoT context.

• Journal of Korean Society for Geospatial Information Science
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• v.17 no.1
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• pp.113-120
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• 2009

Through the automatic sensing of the environment, USN technology can give the best services. In this work, we have developed an active RFID system and examined its performance. By implementing it into water quality sensors, we constructed a system that can detect diverse indoor/outdoor environment and provide information about the pollution level obtained from the temperature and PH sensors. Our RF system had an internal Print-on-PCB antenna for the miniaturization of the tag. We used a RF transceiver CC2510 chipset of TI company to realize the active RFID function. By using RSSI constants obtained, we performed the evaluation of real time location accuracy with a software written in Labview. Among 10 arbitrary locations, we obtained average measurement errors of 1.69 m in x axis and 1.66 m in y axis. This technology can be applied to logistics, environmental monitoring, prevention of missing children and various applications.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.12
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• pp.2792-2799
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• 2012

Multilateration that consists of three or more fixed nodes has been widely used in the field of indoor real time location system(RTLS). However, when one or two among fixed nodes are partially out of communication reachability due to obstruction and unstable node, it is difficult to obtain an efficient location information. In order to improve the challenges of poor ranging measurements and fluctuations in these environment, this paper presents, based on TOF(Time of Flight), a new algorithm which can reduce the inherent ranging measurements errors in the conventional multilateration using a vector prediction algorithm for the displacement estimation of mobile node and Kalman filter for an efficient distance average. Even if a person moves with mobile node and then it fails ranging measurement from some of fixed nodes, the proposed algorithm using a present and previous measurement value can predict the distance between mobile node and fixed node which fails ranging measurement. The experimental results are shown that the proposed system improves the localization accuracy and efficiency compared with conventional method, respectively.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.4
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• pp.670-691
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• 2013

In RSSI-based RFID(Radio Frequency IDentification) indoor localization system, the signal path loss model of each sub-region is different from others in the whole localization area due to the influence of the multi-path phenomenon and other environmental factors. Therefore, this paper divides the localization area into many sub-regions and constructs separately the signal path loss model of each sub-region. Then an improved LANDMARC method is proposed. Firstly, the deployment principle of RFID readers and tags is presented for constructing localization sub-region. Secondly, the virtual reference tags are introduced to create a virtual signal strength space with RFID readers and real reference tags in every sub-region. Lastly, k nearest neighbor (KNN) algorithm is used to locate the target object and an error compensating algorithm is proposed for correcting localization result. The results in real application show that the new method enhances the positioning accuracy to 18.2% and reduces the time cost to 30% of the original LANDMARC method without additional tags and readers.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2010.07a
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• pp.6-8
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• 2010

최근 들어 위치 기반 서비스(Location Based Service)는 치안, 인명 구조, 물류 추적, 길안내 등 다양한 분야로 적용 가능성 때문에 많은 관심을 받고 있는 기술이다. 스마트 폰과 같은 모바일 단말기의 보급이 가속화되면서 사용자는 위치 정보를 이용한 각종 서비스에 대한 요구가 늘어나고 관련 산업의 사업성이 폭발적으로 증가하고 있는 추세다. 실외 위치 추적 기법은 인공위성을 이용한 GPS(Global Positioning System) 기법이 시장을 거의 평정하여 이에 수렴해 가고 있는 상황이고 실제로 많은 상용 제품이 존재하고 있다. 하지만 실내에는 인공위성 신호가 직접 전해 지지 못하는 상황이기 때문에 이와 다른 기법이 존재하나 아직 상용화하기에 그 정확도와 기술력이 부족한 것이 현실이다. 본 논문에서는 건물 밖에 존재하는 GPS 기능이 탑재된 모바일 단말기를 이용하여 실내에 존재하는 모바일 단말기와 협력 통신(Cooperative Communication)하여 위치를 추적하는 기법을 제안한다. 최근 들어 GPS 장비의 단가 하락으로 이 기능을 가지고 있는 모바일 단말기가 증가하고 있는 추세이기 때문에 실내 위치 추적 시스템을 구축하기 위해 별도의 장비를 설치하지 않아도 된다는 것이 이 기법의 가장 큰 장점이다. 시뮬레이션의 결과를 통해 본 기법의 효용성을 확인해보았다.

• Proceedings of the Korea Information Processing Society Conference
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• 2015.10a
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• pp.377-378
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• 2015

실내형 자율 주행 로봇에서의 가장 중요한 기술력은 IGS(indoor GPS System)라 할 수 있다. 재난로봇이나 정찰로봇, 경계로봇등 새로운 로봇의 영역이 늘어남에 따라 실내에서 로봇을 안전하게 구동시키는 연구가 활발히 진행되고 있다. 기존 GPS를 사용할 수 없는 실내에서, LED 조명으로 통신이 가능한 가시광통신은 실내위치 정보를 정밀히 파악하기에 적합하다. 이에 가시광통신을 이용하여 LED 조명별 기준위치를 파악하는 서로 다른 16진수의 데이터를 전송하고, 그 위치를 파악하여 LED 조명의 위치를 식별할 수 있음을 확인한다. 이러한 실험결과를 통하여 가시광통신을 이용해 실내형 자율 주행 로봇의 실내 위치 추정 시스템을 제안한다.

• The Journal of the Korea institute of electronic communication sciences
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• v.14 no.3
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• pp.573-578
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• 2019

Recently, the development of indoor positioning technology, base station positioning, Wi - Fi positioning, and Bluetooth beacon positioning technology have been introduced in buildings and underground space. This paper introduces a technique that enables user-oriented ultra-high precision positioning by adopting a lenticular positioning technology, which is a method in which a user directly locates a user's moving line based on a provider-oriented positioning system and service. Through the study on the implementation of coverage using lenticular stickers, we will discuss how to implement coverage of lenticular stickers, which is one of the most important parts of lenticular positioning technology.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.59-61
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• 2022

Among indoor positioning system techniques using wireless APs, fingerprint techniques collect Mac information and reception strength of APs before performing positioning, build a radio map, and compare it with AP information collected during positioning. However, the existing Radio Map construction method has a problem in that signal interference occurs due to collisions of numerous APs depending on the indoor environment, and the signal strength search result is not always constant. Therefore, this paper compares the existing fixed radio map construction method and the variable radio map construction technique that actively analyzes and constructs the measurement area itself according to signal strength.