• 제어로봇시스템학회논문지
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• 제12권9호
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• pp.905-911
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• 2006

Smart homes are expected to offer various intelligent services by recognizing the residents' life pattern, health, and feeling. One of the key issues for realizing the smart home is how to detect the locations of residents. Currently, the research effort is focused on two approaches: terminal-based and non-terminal-based method. The terminal-based method employs a type of device that should be carried by the resident while the non-terminal-based method has no such device. This paper presents a novel non-terminal-based approach using an array of pyroelectric infrared sensors (PIRs) that can detect residents. The feasibility of the system is evaluated experimentally on a test bed.

• 한국정보시스템학회지:정보시스템연구
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• 제19권1호
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• pp.1-17
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• 2010

This paper proposes an updating policy of indoor moving object databases (IMODB) for location-based services. our method applies the Ka1man filter on the recently collected measured positions to estimate the moving object's position and velocity at the moment of the most recent measurement, and extrapolate the current position with the estimated position and velocity. If the distance between the extrapolated current position and the measured current position is within the threshold, in other words if they are close then we skip updating the IMODB. When the IMODB needs to know the moving object's position at a certain moment T, it applies the Kalman filter on the series of the measurements received before T and extrapolates the position at T with the estimations obtained by the Kalman filter. In order to verify the efficiency of our updating method, we performed the experiments of applying our method on the series of measured positions obtained by applying the fingerprinting indoor positioning method while we are actually walking through the test bed. In the analysis of the test results, we estimated the communication saving rate of our method and the error increment rate caused by the communication saving.

• Journal of Positioning, Navigation, and Timing
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• 제10권1호
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• pp.49-54
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• 2021

Indoor positioning system becomes of increasing interests due to the demands for accurate indoor location information where Global Navigation Satellite System signal does not approach. Wi-Fi access points (APs) built in many construction in advance helps developing a Wi-Fi Received Signal Strength Indicator (RSSI) based indoor localization. This localization method first collects pairs of position and RSSI measurement set, which is called fingerprint database, and then estimates a user's position when given a query measurement set by comparing the fingerprint database. The challenge arises from nonlinearity and noise on Wi-Fi RSSI measurements and complexity of handling a large amount of the fingerprint data. In this paper, machine learning techniques have been applied to implement Wi-Fi based localization. However, most of existing indoor localizations focus on single position estimation. The main contribution of this paper is to develop multi-target localization by using deep neural, which is beneficial when a massive crowd requests positioning service. This paper evaluates the proposed multilocalization based on deep learning from a multi-story building, and analyses its learning effect as increasing number of target positions.

• Journal of Information Technology Applications and Management
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• 제12권4호
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• pp.93-104
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• 2005

Recently, RFID/USN is one of fundamental technologies in information and communications networks. Low-Rate WPAN, IEEE802.15.4 is a low-cost communication network that allows wireless connectivity in applications with limited Power and relaxed throughput requirements. Its applications are building automation, personal healthcare, industrial control, consumer electronics, and so on. Some applications require location information. Of course location awareness is useful to improve usability of data Low-Rate WPAN Is regarded as a key specification of the sensor network with the characteristics of wireless communication, computing, energy scavenging, self-networking, and etc. Unfortunately ZigBee alliance propose a lot of applications based on location aware technologies, but the specification and low-rate WPAN devices don't support anything about location-based services. RSSI ( Received Signal Strength indication) is for energy detection to associate, channel selection, and etc. RSSI is used to find the location of a potable device in WLAN. In this paper we studied indoor location awareness using vector matching of RSSI in low-Rate wireless PAN. We analyzed the characteristics of RSSI according to distance and experimented location awareness. We implemented sensor nodes with different shapes and configured the sensor network for the location awareness with 4 fixed nodes and a mobile node. We try to contribute developing location awareness method using RSSI in 3-dimension space.

• 한국항행학회논문지
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• 제19권6호
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• pp.558-563
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• 2015

최근 실내 위치측위 기술을 이용하여 다양한 서비스가 이루어지고 있다. 실내 위치측위 방식에는 대표적으로 fingerprinting 방식과 삼변측량 방식이 있으나 활용의 제한성 및 위치추정 오차 등의 문제점이 있다. 이러한 문제점을 해결하기 위해 기존의 측위 방식인 AOA, TOA, TDOA 등의 측위 기술을 응용한 연구가 진행되고 있다. 본 논문에서는 실내 환경에서 RSSI 차이를 이용한 AOA 기반 위치 추정 알고리즘에 대해 연구한다. 4개의 안테나를 가지는 하나의 AP를 가정하여 연구를 진행하며, RSSI를 기반으로 도래각을 추정 후 AOA 알고리즘에 적용한다. RSSI의 보정을 위해 재귀식 평균 필터를 이용하며, 도래각 추정을 위해 보정된 RSSI와 피타고라스 정리를 이용한다. 실험 결과 좁은 간격으로 배치된 4개의 무지향성 안테나의 방사 패턴으로 인하여 18%의 오차율을 보였으며, 지향성 안테나를 이용할 경우 실내 환경에서 AOA 알고리즘을 활용할 수 있을 것으로 판단된다.

• Journal of Communications and Networks
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• 제18권5호
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• pp.837-845
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• 2016

Providing a customer with tailored location-based services (LBSs) is a fundamental problem. For location-estimation techniques with radio-based measurements, LBS applications are widely available for mobile devices (MDs), such as smartphones, enabling users to run multi-task applications. LBS information not only enables obtaining the current location of an MD but also provides real-time push-pull communication service. For indoor environments, localization technologies based on radio frequency (RF) pattern-matching approaches are accurate and commonly used. However, to survey radio information for pattern-matching approaches, a considerable amount of time and work is spent in indoor environments. Consequently, in order to reduce the system-deployment cost and computing complexity, this article proposes an indoor positioning approach, which involves using Asus Xtion to facilitate capturing RF signals during an offline site survey. The depth information obtained using Asus Xtion is utilized to estimate the locations and predict the received signal strength (RF information) at uncertain locations. The proposed approach effectively reduces not only the time and work costs but also the computing complexity involved in determining the orientation and RF during the online positioning phase by estimating the user's location by using a smartphone. The experimental results demonstrated that more than 78% of time was saved, and the number of samples acquired using the proposed method during the offline phase was twice as much as that acquired using the conventional method. For the online phase, the location estimates have error distances of less than 2.67 m. Therefore, the proposed approach is beneficial for use in various LBS applications.

• 한국측량학회지
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• 제29권3호
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• pp.303-309
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• 2011

일상생활에 미치는 영향이 확산되고 있는 상황인식서비는 위치기반서비스와 소셜네트워크서비스로 분류되며, 스마트폰의 GPS 및 전자나침반 기술의 정확도에 따라 상황인식서비스 품질이 달라질 수 있다. 본 연구에서는 상황인식서비스를 이용할 때 가장 중요한 단초가 될 수 있는 GPS, 전자나침반(Digital Compass), 무선통신, 공간정보(Geospatial Web)를 활용함에 있어서의 위치적 정확도에 대하여 분석하였다. 스마트폰을 이용한 위치 및 방향 결정 정확도 실험 결과 실외에 비하여 낮은 실내 위치 및 방향 정확도와 플랫폼으로 활용되는 공간정보가 갖고 있는 오차에 의해 상황인식서비스 이용 시 정확한 정보를 제공 받지 못하는 문제점이 발생하는 것으로 나타났다. 실내 위치 결정 정확도 향상 방안으로 Wi-Fi를 이용한 측위 방법 등이 있으나 실외에서 사용하는 GPS에 비해 많은 보완 사항이 있는 것으로 나타났으며, 상황인식서비스의 플랫폼으로 활용되는 공간정보의 품질 향상을 위하여 DSM을 이용해 폐색영역을 보정한 실감 정사영상의 제작이 필요한 것으로 판단된다.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2015년도 춘계학술대회
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• pp.241-243
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• 2015

최근 인터넷을 기반으로 사물을 연결하여 사람과 사물 간의 정보 소통을 가능하게 하는 지능형 서비스로서 사물 인터넷 서비스(IoT)에 대한 관심이 증가하고 있다. 특히 스마트 기기의 발전과 더불어 실내 위치 기반 서비스에 대한 수요는 급격히 증가하고 있다. 실내 위치 정보 측정을 위해 BLE(Bluetooth Low Energy) 기술의 iBeacon이 제공하는 기본적인 신호만을 이용하면 신호 간섭 등의 다양한 이유로 신뢰할 수 없는 신호 데이터로 인해 실내 위치 정보의 신뢰도는 현격히 낮아지게 된다. 본 논문에서는 iBeacon의 신호 정보로 부터 신뢰성 있는 위치 정보를 얻기 위해 유전 연산을 통해 효과적이고 신뢰도 높은 위치 정보를 얻는 기법을 제안한다.

• 디지털융복합연구
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• 제14권2호
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• pp.217-225
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• 2016

본 연구에서는 배회가능성이 있는 치매환자의 실종예방을 위하여 웨어러블 디바이스(Wearable Device) 형식의 블루투스 비콘을 활용한 치매환자의 실내위치기반 모니터링시스템을 제안하였다. 이 시스템은 치매환자의 관리범위내 존재유무를 확인해 주며 치매환자가 비콘의 신호수신 설정거리를 이탈하면 즉, 지정된 관리구역을 벗어나면 비상메시지가 보호자와 관리자의 스마트 디바이스로 전달되는 시스템이다. 이 시스템의 주요 특성은 비콘을 착용한 치매환자를 특정장소에 설치된 비콘 신호수신용 스마트 기기(AP)에서 신호를 감지하여 환자의 위치를 파악하는 가역적 방법을 적용한 것이다. 본 논문에서 제안하는 블루투스 비콘을 활용한 실내위치기반 치매환자 모니터링 시스템은 요양병원, 재가요양시설 등에서 생활하는 배회가능성이 있는 치매환자의 실종예방에 기여하는 효과적 시스템으로 생각된다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권2호
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• pp.723-743
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• 2016

Indoor positioning is considered an enabler for a variety of applications, the demand for an indoor positioning service has also been accelerated. That is because that people spend most of their time indoor environment. Meanwhile, the smartphone integrated powerful camera is an efficient platform for navigation and positioning. However, for high accuracy indoor positioning by using a smartphone, there are two constraints that includes: (1) limited computational and memory resources of smartphone; (2) users' moving in large buildings. To address those issues, this paper uses the TC-OFDM for calculating the coarse positioning information includes horizontal and altitude information for assisting smartphone camera-based positioning. Moreover, a unified representation model of image features under variety of scenarios whose name is FAST-SURF is established for computing the fine location. Finally, an optimization marginalized particle filter is proposed for fusing the positioning information from TC-OFDM and images. The experimental result shows that the wide location detection accuracy is 0.823 m (1σ) at horizontal and 0.5 m at vertical. Comparing to the WiFi-based and ibeacon-based positioning methods, our method is powerful while being easy to be deployed and optimized.