• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.10a
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• pp.851-853
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• 2013

Recently, location-based service as the developed continuously, interest in positioning technology is increasing. As the most famous indoor positioning technology, WPS is a positioning technology using WiFi, which can complement the limits of the indoor positioning to have a GPS. In this paper, to provide a system for monitoring the position of the inside of the user based on the position information that using the RSSI signal of the wireless AP based WPS technology, they grip the location information of the mobile nodes in the indoor. If using the method proposed, it is expected to be applied to various services it is possible to apply the WPS, this is because it is possible to estimate in real time the location distribution of mobile nodes in the indoor.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2006.04a
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• pp.3-7
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• 2006

Indoor localization is getting more and more importance with the increasing demand for location based service. Location based service necessarily requires the information about customers' locations to provide them the right service according to their changing locations. To satisfy that requirement, GPS is used to achieve outdoor localization. However, there is no leading technology to achieve indoor localization. Indoor localization through UWB wave and TDOA algorithm is considered as the most accurate method until now. In implementing that method, configuration of base stations that serve as control points affects the localization accuracy. Thus, this paper discusses about optimal configuration of base stations. The variation in localization accuracy according to spatial relationship between an object and base stations Is mentioned through SEP also.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.6B
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• pp.888-894
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• 2010

For the indoor positioning, wireless fingerprinting is most favorable because fingerprinting is most accurate among the technique for wireless network based indoor positioning which does not require any special equipments dedicated for positioning. The deployment of a fingerprinting method consists of off-line phase and on-line phase and more efficient and accurate methods have been studied. This paper proposes a bayesian algorithm for wireless fingerprinting and indoor location determination using fuzzy clustering with bayesian learning as a statistical learning theory.

• Journal of the Korea Safety Management & Science
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• v.20 no.1
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• pp.33-40
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• 2018

The rate of fire in buildings is gradually increasing in these days and the damage of property are severely increasing. This study suggests a methodology that provides information of the emergency exits based on indoor location services. The methodology uses determination technology and the latest update of indoor map generation via the built-in sensors of smartphone. This paper enhances the accuracy of indoor localization, and also it is to study how to provide exact indoor layout for rescuing the workers in emergency, such as fires and natural disasters.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38C no.9
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• pp.775-780
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• 2013

Localization, or positioning, is gaining the increasing attention of researchers around the world. The location information, especially the indoor location, is important for navigation systems, heating and air conditioning systems, illumination adjustment, humidity control, robot service, and so on. In this paper, we propose a three-dimensional indoor localization technique using visible light. The main goal of our proposed scheme is to improve the accuracy of VLC-based indoor localization by utilizing multiple VLC transmitters. The simulation results validate the performance of our proposed scheme.

• Journal of Electrical Engineering and Technology
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• v.4 no.1
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• pp.131-134
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• 2009

We have proposed an indoor positioning system for moving objects and/for the blind or visually impaired to play various sports. [ for a blind or visually impaired playing various sports.] This system consists of a wireless heart rate monitor, wireless sensor network and / 4 ultrasound satellites [ configuration with four ultrasound satellite modules) at the corners of the room. This system provides / the real-time measurement of the location and heart rate of the person in the room[ non-invasive measurement method of the heart rate and the location of a person in real time ], and will help the [a] blind or visually impaired enjoy sports more easily.

• KIISE Transactions on Computing Practices
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• v.23 no.4
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• pp.210-216
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• 2017

In the paper we propose and implement a new indoor localization system where the techniques of magnetic field based fingerprinting and pedestrian dead reckoning are combined. First, we determine a target's location by comparing acquired magnetic field values with a magnetic field map containing pre-collected field values at different locations and choosing the location having the closest value. As the target moves, we use pedestrian dead reckoning to estimate the expected moving path, reducing the maximum positioning error of the initial location. The system eliminates the problem of localization error accumulation in pedestrian dead reckoning with the help of the fingerprinting and does not require Wi-Fi AP infrastructure, enabling cost-effective localization solution.

• The Journal of Information Systems
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• v.19 no.1
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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.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.05a
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• pp.863-865
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• 2015

A method for estimating position is AOA, TOA, TDOA, Wi-Fi, Beacon etc. A method for estimating the location in indoor environment is used mainly Wi-Fi, Beacon. The reason is that AOA, TOA and TDOA are unfit to estimate position in indoor environment. To address this problem, this paper presents a AOA algorithm based on AP having a four directional antenna. The algorithm uses only the angle received from the four antennas. This can draw linear equations for signal. And calculate the intersections of the lines. Intersections means the position of user.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.10a
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• pp.457-461
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• 2007

In many applications, received signal strength indicator is used for location tracking and sensor nodes localization. For location finding, the distances between sensor nodes can be estimated by converting received signal's power into distance using path loss prediction model. Many researches have done the analysis of power-distance relationship for radio channel characterization. In indoor environment, the general conclusion is the non-linear variation of RSSI values as distance varied linearly. This has been one of the difficulties for indoor localization. This paper presents works on indoor RSSI characterization based on statistical methods to find the overall trend of RSSI variation at different places and times within the same room From experiments, it has been shown that the variation of RSSI values can be determined by both spatial and temporal factors. This two factors are directly indicated by the two main parameters of path loss prediction model. The results show that all sensor nodes which are located at different places share the same characterization value for the temporal parameter whereas different values for the spatial parameters. Using this relationship, the characterization for location estimation can be more efficient and accurate.