• Information and Communications Magazine
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• v.20 no.2
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• pp.77-85
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• 2003

• Spatial Information Research
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• v.21 no.1
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• pp.87-100
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• 2013

Recently, the use of locational information is growing rapidly. GPS technology has been adopted generally for obtaining locational information in outdoor spaces. In the other hand, the researches on indoor positioning have been carried out applying WLAN, RFID or Bluetooth technology because of the multi-path interference of GPS signal caused by the physical obstacles such as walls or columns in buildings. However, such technologies for indoor positioning cost too much to build sensing infrastructure and compute-intensive processes are involved. Furthermore, the accuracy of location estimation is variable caused by interior structures in buildings. In this study, to make up for the limitations, descriptive data such as phone number, unique room numbers, or business names readily available in mixed-use buildings is used for extracting location information. Furthermore, during the process, a geocoding method using character matching is applied to this study enabling prompt location estimation and sublating the fluctuation of accuracy caused by interior structures. Based on the proposed method in this study, an architecture is designed, and three-dimensional viewer program is developed for the implementation of this study. Also, this research is quantitatively analyzed through match rate and processing time of proposed method.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.05a
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• pp.288-290
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• 2017

Recently, interest and demand of Augmented Reality(AR) contents are increasing as an application field of AR. Generally, when the AR contents are served in the outdoor environment, the position information using the GPS signal is used to control the display of the object on the AR screen, or a marker based on the image of the object is used. However, there is a problem that location information can not be used in an indoor environment. If the service is provided using only the marker, there is a problem that the recognition of the marker due to the moving obstacle in the vicinity is unstable. and there is a problem that information displayed on the AR screen is not displayed in a fixed state at a specific position, it moves according to the movement of the camera. In this paper, we have studied the object control method for displaying the object to be displayed on the AR screen by using iBeacon using indoor location recognition and specific markers.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.45 no.12
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• pp.97-104
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• 2008

Location-based services provide customized information or services according to the user's location. The existing localization schemes for outdoor environment are not applicable to the indoor localization system which requires higher accuracy of location estimation than that of the outdoor localization system. In this paper, we employ the received signal strength(RSS) to approximate the distance between a moving target and a reference point and use the triangulation method to estimate the location of the moving target for the indoor localization system in IEEE 802.15.4 wireless PAN(personal area network). For the indoor localization system, we propose a scheme which selects the best reference points to enhance the localization accuracy and adaptively reflects the changes in propagation environments of a moving target to the distance approximation. Through the implementation of the localization system, we have verified the performance of the proposed scheme in terms of the estimation accuracy.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.45 no.5
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• pp.38-47
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• 2008

The most commonly used location recognition system is the GPS-based approach. However, the GPS is inefficient for an indoor or urban area where high buildings shield the satellite signals. To overcome this problem, this paper propose the indoor positioning method using wavelet and neural network. The basic idea of proposed method is estimated the location using the received signal strength from wireless APs installed in the indoor environment. Because of the received signal strength of wireless radio signal is fluctuated by the environment factors, a feature that is strength of signal noise and error and express the time and frequency domain is need. Therefore, this paper is used the wavelet coefficient as the feature. And the neural network is used for estimate the location. The experiment results indicate 94.6% an location recognition rate.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.3
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• pp.117-123
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• 2022

Unlike the satellite-based outdoor positioning system, the indoor positioning system utilizes various wireless technologies such as BLE, Wi-Fi, and UWB. BLE-based beacon technology can measure the user's location by periodically broadcasting predefined device ID and location information and using RSSI from the receiving device. Existing BLE-based indoor positioning system studies have many studies comparing the error between the user's actual location and the estimated location at a single point. In this paper, we propose a technique to evaluate the positioning accuracy according to the movement path or area by applying the entropy analysis model. In addition, simulation results show that calculated entropy results for different paths can be compared to assess which path is more accurate.

• Nuclear Engineering and Technology
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• v.55 no.8
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• pp.3030-3038
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• 2023

Nowadays, mobile robots have been used to search for uncontrolled radioactive source in indoor environments to avoid radiation exposure for technicians. However, in the indoor environments, especially in the presence of obstacles, how to make the robots with limited sensing capabilities automatically search for the radioactive source remains a major challenge. Also, the source search efficiency of robots needs to be further improved to meet practical scenarios such as limited exploration time. This paper proposes an automatic source search strategy, abbreviated as ACA: the location of source is estimated by a convolutional neural network (CNN), and the path is planned by the A-star algorithm. First, the search area is represented as an occupancy grid map. Then, the radiation dose distribution of the radioactive source in the occupancy grid map is obtained by Monte Carlo (MC) method simulation, and multiple sets of radiation data are collected through the eight neighborhood self-avoiding random walk (ENSAW) algorithm as the radiation data set. Further, the radiation data set is fed into the designed CNN architecture to train the network model in advance. When the searcher enters the search area where the radioactive source exists, the location of source is estimated by the network model and the search path is planned by the A-star algorithm, and this process is iterated continuously until the searcher reaches the location of radioactive source. The experimental results show that the average number of radiometric measurements and the average number of moving steps of the ACA algorithm are only 2.1% and 33.2% of those of the gradient search (GS) algorithm in the indoor environment without obstacles. In the indoor environment shielded by concrete walls, the GS algorithm fails to search for the source, while the ACA algorithm successfully searches for the source with fewer moving steps and sparse radiometric data.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2007.11a
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• pp.53-54
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• 2007

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2010.05a
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• pp.763-764
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• 2010

• Journal of Korea Multimedia Society
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• v.15 no.1
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• pp.71-80
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• 2012

LBS (Location Based Service) services are very useful to our daily life and it should be available inside a building: a huge building, a shopping mall, a large scale underground shopping center, and so on where GPS (Global Positioning System) signal is not available. An LBS which is provided inside a building is called an ILBS (Indoor Location Based Service). One of the most important techniques for ILBS development is indoor positioning. Among the indoor positioning techniques, APs (access points) of WLAN based ones are most economical because WLAN is available almost everywhere. Meanwhile, the web service has been proved to be an excellent practice of software reuse. Therefore, if indoor positioning is provided in the form of web service to programmers then development of ILBS would be greatly accelerated. This paper introduces the AP based trilateration and K-NN indoor positioning and RFID based indoor positioning web services we have developed.