• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.7B
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• pp.1058-1065
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• 2010

In the recent, the importance of ubiquitous-related technique is increased as many companies and researchers make an effort to create a new service model using ubiquitous computing and network technologies. Especially, the research of indoor location recognition has gained a lot of interest because it is a critical component for supporting ubiquitous services. Nevertheless, the simulation tool for indoor location recognition hardly has studied compared to their importance. In this paper, we propose a Ptolemy-based simulator over UWB channel that provides short-range and high-bandwidth communication. Finally, we conduct experiments using the proposed simulator and analyze the performance of various location recognition algorithms.

• ETRI Journal
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• v.38 no.3
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• pp.560-567
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• 2016

To solve the problem of parameter optimization in image sensor-based visible light positioning systems, theoretical limits for both the location and the azimuth angle of the image sensor receiver (ISR) are calculated. In the case of a typical indoor scenario, maximum likelihood estimations for both the location and the azimuth angle of the ISR are first deduced. The Cramer-Rao Lower Bound (CRLB) is then derived, under the condition that the observation values of the image points are affected by white Gaussian noise. For typical parameters of LEDs and image sensors, simulation results show that accurate estimates for both the location and azimuth angle can be achieved, with positioning errors usually on the order of centimeters and azimuth angle errors being less than $1^{\circ}$. The estimation accuracy depends on the focal length of the lens and on the pixel size and frame rate of the ISR, as well as on the number of transmitters used.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.10a
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• pp.846-849
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• 2008

In recent years there has been growing interest in wireless sensor networks (WSNs) for a variety of indoor applications. In this paper, we present the RSSI-based localization in indoor environments. In order to evaluate the relationship between distance and RSSI, the log-normal path loss shadowing model is used. By tagging users with a sensor node and deploying a number of nodes at fixed position in the building, the RSSI can be used to determine the position of tagged user. This system operates by recording and processing signal strength information at the base stations. It combines Euclidean distance technique with signal strength matrix obtained during real-time measurement to determine the location of user. The experimental results presented the ability of this system to estimate user's location with a accuracy.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.4
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• pp.847-856
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• 2013

This paper presents an AP placement technique considering indoor location-awareness and examines its performance. The proposed AP placement technique is addressed from three performance metrics: location-awareness and AP-based wireless network performance as well as its cost. The proposed AP placement technique consists of meta-heuristic algorithms that yield a near optimal AP configuration for given performance metrics, and deterministic algorithms that improve the fast convergence of the near optimal AP configuration. The performance of the AP placement technique presented in this paper is measured under the environments simulating indoor space, and numerical results obtained by experimental evaluation yield the fast convergence of a near-optimal solution to a given performance metric.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.490-491
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• 2021

Recently, technologies using Wi-Fi fingerprints and deep learning are being studied to provide accurate location-based services in an indoor environment. At this time, the composition of learning data is very important, and it is essential to collect sufficient data necessary for learning. However, the number of specific points for the collection of radio signal data within the area requiring positioning is infinite, and it is impossible to collect all of these data. Therefore, there is a need for a way to make up for insufficient learning data. This study proposes a method of constructing a sufficient number of location data necessary for learning based on insufficiently collected location data.

• Journal of Korean Society for Geospatial Information Science
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• v.17 no.1
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• pp.157-166
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• 2009

There is a growing interest in ubiquitous-related research and applications. Among them, GPS-based LBS have been developed and used actively. Recently, with the increase of large size buildings and disastrous events, indoor spaces are getting attention and related research activities are being carried out. Core technologies regarding indoor applications may include 3D indoor data modeling and localization sensor techniques that can integrate with indoor data. However, these technologies have not been standardized and established enough to be applied to indoor implementation. Thus, in this paper, we propose a method to build a relatively simple 3D indoor data modeling technique that can be applied to indoor location based applications. The proposed model takes the form of 2D-based multi-layered structure and has capability for 2D and 3D visualization. We tested three prototype applications using the proposed model; CA(cellular automata)-based 3D evacuation simulation, network-based routing, and indoor moving objects tracking using a stereo camera.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2006.10a
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• pp.11-12
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• 2006

• Journal of the Korean Society for Precision Engineering
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• v.24 no.6
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• pp.37-44
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• 2007

• Journal of Internet Computing and Services
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• v.7 no.3
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• pp.71-82
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• 2006

This paper propose a realtime tracking algorithm of mobile object in indoor environment. this proposed system selects location data closer to mobile objects in real time that are results of Triangulation method and DCM(Database Correlation Method)method. Also, this system applies adjusted location data selected by using Kalman filter, and in result it improved location accuracy of transfer object. Be studied in existing the Kalman filter have unstable location data until its settlement because of it extracts current values by using the past the information. However, proposed location tracking system don't apply existent Kalman filter to this system and it permits precisional tracking location by uses more effective methods.

• Journal of information and communication convergence engineering
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• v.14 no.4
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• pp.207-214
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• 2016

In this paper, we propose a radial reference map-based location fingerprinting technique with constant spacing from an access point (AP) to all reference points by considering the minimum dynamic range of the received signal strength indicator (RSSI) obtained through an experiment conducted in an indoor environment. Because the minimum dynamic range, 12 dBm, of the RSSI appeared every 20 cm during the training stage, a cell spacing of 80 cm was applied. Furthermore, by considering the minimum dynamic range of an RSSI in the location estimation stage, when an RSSI exceeding the cumulative average by ${\pm}6dBm$ was received, a previously estimated location was provided. We also compared the location estimation accuracy of the proposed method with that of a conventional fingerprinting technique that uses a grid reference map, and found that the average location estimation accuracy of the conventional method was 21.8%, whereas that of the proposed technique was 90.9%.