• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.10a
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• pp.432-434
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• 2013

본 논문의 실내위치측위시스템은 무선랜 환경에서 AP의 RSSI 신호를 수신하여 Friis 공식을 통해 거리로 산출되고, 산출된 거리는 삼각측량법에 의해 (x, y)좌표로 변환되어 현재의 위치를 나타낸다. 여기서 RSSI 신호는 신호잡음을 포함하고 신호잡음으로 인하여 실제 위치 측위 시 오차가 발생한다. 이러한, 오차를 보정하고 실내위치측위 정확도를 향상하기 위해 비선형시스템에서 사용하는 확장칼만필터를 적용하여 실험하였다. 본 실내위치측위시스템의 시스템모델은 선형이고 측정모델은 비선형이므로 효율적인 보정알고리즘인 확장칼만필터를 선택하고 실험은 MATLAB로 수행하였다. 실험결과 실내위치측위시스템의 정확도가 향상되었다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.1C
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• pp.130-137
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• 2010

An uplink indoor positioning system is proposed in the present work, where the acoustic signals are solely used for positioning. The underlying acoustic signals include whistle, finger snap, and hands-clapping. In the proposed method, positioning is achieved by finding the time-difference-of-arrivals using several self-generating sounds. To evaluate the feasibility of the signals and their positioning accuracies, the database of 100 persons about self-generating acoustic signals is built up. The results show that the hands-clapping sound is the most suitable for acoustic-based indoor positioning.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.10a
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• pp.436-439
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• 2008

위치기반 서비스(LBS : Local Based Service)는 단연 GPS가 그 중심이라 할 수 있다. 그러나 실외가 아닌 실내에서의 측위는 GPS신호가 도달할 수 없고, 또한 기존에 연구 중인 실내측위 기술들은 여러 가지 문제점을 갖고 있다. 따라서 다양한 서비스가 구현 가능한 ZigBee 기반의 USN내에서 기존의 다양한 센서들이 구동되면서 ZigBee 노드 간의 신호의 세기인 RSSI(Received Signal Strength Indicator)를 활용한 위치측위시스템을 구현한다. 또한 기존의 RSSI를 활용한 실내측위의 문제점들을 보완하기 위하여 신경회로망을 이용한 위측측위 알고리즘을 제안하여 보다 정확하고 안정적인 위치정보 시스템을 구현한다. 따라서 실내위치측위가 필요한 다양한 공공장소에 적합한 위치기반 서비스가 도입될 수 있는 가능성을 제시한다.

• The Journal of Korean Institute of Next Generation Computing
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• v.14 no.6
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• pp.57-65
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• 2018

Conventional RF signal-based indoor localization techniques such as BLE or Wi-Fi based fingerprinting method show considerable localization errors even in small-scale indoor environments due to unstable received signal strength(RSS) of RF signals. Therefore, it is difficult to apply the existing RF-based fingerprinting techniques to large-scale indoor environments such as airports and department stores. In this paper, instead of RF signal we use the geomagnetic sensor signal for indoor localization, whose signal strength is more stable than RF RSS. Although similar geomagnetic field values exist in indoor space, an object movement would experience a unique sequence of the geomagnetic field signals as the movement continues. We use a deep neural network model called the recurrent neural network (RNN), which is effective in recognizing time-varying sequences of sensor data, to track the user's location and movement path. To evaluate the performance of the proposed geomagnetic field based indoor positioning system (IPS), we constructed a magnetic field map for a campus testbed of about $94m{\times}26$ dimension and trained RNN using various potential movement paths and their location data extracted from the magnetic field map. By adjusting various hyperparameters, we could achieve an average localization error of 1.20 meters in the testbed.

• Proceedings of the Korean Society of Computer Information Conference
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• 2021.01a
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• pp.307-308
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• 2021

2020년 7월 정부는 포스트 코로나 시대를 선언하며, 한국판 뉴딜 정책을 발표하였다. 한국판 뉴딜은 디지털인프라 구축, 비대면 산업육성, SOC 디지털화를 기본방향으로 내세웠으며 빅데이터, 인공지능(AI), 사물인터넷(IoT) 등 4차산업 핵심기술의 육성방안을 제시하였다. 최근 인천공항은 한국판 뉴딜 정부정책에 부응하기 위해 인천공항 K-뉴딜 프로젝트를 추진 중이며, 세부 전략과제로 자산관리의 디지털전환을 위한 IoT기반 스마트 자산관리시스템을 구축 중이다. IoT기반 스마트자산관리시스템은 인천공항에 위치한 실내외 이동형 자산에 대해 끊김없는 위치정보를 제공하는 시스템으로 기존 시스템(RFID) 대비 약 4억 원의 인적, 물적 자원을 절감하는 효과를 나타낼 것으로 예상된다. 본 논문에서는 IoT기반 스마트 자산관리시스템의 핵심기술인 실내외 연속측위 스마트 트래커와 네트워크의 구성, 저전력 위치정보 제공방법을 제시한다.

• 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.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.7 no.1
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• pp.1-9
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• 2008

According to the ubiquitous trend, the needs for the context based application service have been increased. These services take on Location Based Service which is based on the current location of users. It is widely used that localization techniques use GPS or ground wave and more efficient and accurate methods have been studied. Recently, not only services which targeted outdoor but also services which targeted indoor, for example home services and facility guidance of the building come into the spotlight. In case of the outdoor positioning area, COTH (Commercial Off-The-Shelf) has been released and used but relatively it doesn't produce an outcome in the indoor positioning area. Therefore, this paper Proposes the indoor positioning technique using wireless LAN (Local Area Network) which is one of the widely used wireless communication technique. It analyzes the typical WLAN location positioning methodology has been studied and their advantage and disadvantage also suggests how to design and implement the specific WLAN positioning system. In addition, it suggests new methods that progress the accuracy of the existing systems and improve the efficient computation.