• Journal of the Korea Safety Management & Science
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• v.14 no.1
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• pp.217-224
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• 2012

Location-Based Services(LBS) is a service that provide location information by using communication network or satellite signal. In order to provide LBS precisely and efficiently, we studied how we can reduce the error on location determination of objects such people and things. We focus on using the least square method and triangulation positioning method to improves the accuracy of the existing location determination method. Above two methods is useful if the distance between the AP and the tags can be find. Though there are a variety of ways to find the distance between the AP and tags, least squares and triangulation positioning method are wildely used. In this thesis, positioning method is composed of preprocessing and calculation of location coordinate and detail of methodology in each stage is explained. The distance between tag and AP is adjusted in the preprocessing stage then we utilize least square method and triangulation positioning method to calculate tag coordinate. In order to confirm the performance of suggested method, we developed the test program for location determination with Labview2010. According to test result, triangulation positioning method showed up loss error than least square method by 38% and also error reduction was obtained through adjustment process and filtering process. It is necessary to study how to reduce error by using additional filtering method and sensor addition in the future and also how to improve the accuracy of location determination at the boundary location between indoor and outdoor and mobile tag.

• 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.

• Journal of Korea Spatial Information System Society
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• v.10 no.2
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• pp.49-62
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• 2008

This paper proposes an indoor location positioning system for the image recognition based LBS. The proposed system is a vision-based location positioning system that is implemented the augmented reality by overlaying the location results with the view of the user. For implementing, the proposed system uses the pattern matching and location model to recognize user location from images taken by a wearable mobile PC with camera. In the proposed system, the system uses the pattern matching and location model for recognizing a personal location in image sequences. The system is estimated user location by the image sequence matching and marker detection methods, and is recognized user location by using the pre-defined location model. To detect marker in image sequences, the proposed system apply to the adaptive thresholding method, and by using the location model to recognize a location, the system can be obtained more accurate and efficient results. Experimental results show that the proposed system has both quality and performance to be used as an indoor location-based services(LBS) for visitors in various environments.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2022.11a
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• pp.47-48
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• 2022

The positioning technology that measures the position of a person or object is a key technology to deal with the location of the real coordinate system or converge the real and virtual worlds, such as digital twins, augmented reality, virtual reality, and autonomous driving. In estimating the location of a person or object at an indoor construction site, there are restrictions that it is impossible to receive location information from the outside, the communication infrastructure is insufficient, and it is difficult to install additional devices. Therefore, this study tested the direct sparse odometry algorithm, one of the visual Simultaneous Localization and Mapping (vSLAM) that estimate the current location and surrounding map using only image information, at an indoor construction site and analyzed its applicability as an indoor positioning technology. As a result, it was found that it is possible to properly estimate the surrounding map and the current location even in the indoor construction site, which has relatively few feature points. The results of this study can be used as reference data for researchers related to indoor positioning technology for construction sites in the future.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.4 no.3
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• pp.595-602
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• 2000

This paper is aimed at developing an location tracking system of mobile station based on currently available mobile communication network or mobile Phone and PCS(Personal Communication System). When the location tracking of mobile stations is in services, Emergency-119, all of crime investigation, effective urban traffic management and the safety protection of Alzheimer＇s patients can be available. In order to track the location of the mobile and base station, assumption in this paper is to use the statistic characteristics of LOS when modeling the standard noise in case that radio path is LNOS environment. The standard variation of the standard noise is $\pm150$. First, location is estimated by the positioning algorithms of TOA and TDOA and compared each other. Second, after canceling the standard noise by Kalman filter, location is estimated by the above two positioning algorithms. Finally, the location by the Kalman filter and two positioning algorithms is estimated by smoothing method. As a result, 2 dimensional average location error is imvoved by 51.2m in TOA and 34.8m in TDOA when Kalman filer and two positioning algorithms are used, compared with the two positioning algorithm used. And there is 3 more meter improvement after smoothing than Kalman filer and two positioning algorithms used.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.5
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• pp.1951-1972
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• 2018

Wi-Fi Access Point (AP) optimization approaches are used in indoor positioning systems for signal coverage enhancement, as well as positioning precision improvement. Although the huge power consumption of the AP optimization forms a serious problem due to the signal coverage requirement for large-scale indoor environment, the conventional approaches treat the problem of power consumption independent from the design of indoor positioning systems. This paper proposes a new Fast Water-filling algorithm Group Power Constraint (FWA-GPC) based Wi-Fi AP optimization approach for indoor positioning in which the power consumed by the AP optimization is significantly considered. This paper has three contributions. First, it is not restricted to conventional concept of one AP for one candidate AP location, but considered spare APs once the active APs break off. Second, it utilizes the concept of water-filling model from adaptive channel power allocation to calculate the number of APs for each candidate AP location by maximizing the location fingerprint discrimination. Third, it uses a fast version, namely Fast Water-filling algorithm, to search for the optimal solution efficiently. The experimental results conducted in two typical indoor Wi-Fi environments prove that the proposed FWA-GPC performs better than the conventional AP optimization approaches.

• Journal of Positioning, Navigation, and Timing
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• v.10 no.3
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• pp.207-214
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• 2021

A new positioning technique for positioning of LTE base stations is proposed. The positioning information of the base station is absolutely necessary for model-based wireless positioning, and is required in some of the various merhodologies for estimating signals in an uncorrected area when construnting a database for fingerprinting-based positioning. Using the acquired location-based Reference Signal Received Power (RSRP) information to estimate the location of the base station, it is impossible with the existing trilateration methods. Therefore, in this paper, a method using reference particles is proposed. Particles are randomly generated in the application area, and signal propagation modeling is performed assuming that a base station is located in each particle. Based on this, the errors of measurements are calculated. The particle group with the minimum measurement errors is selected, the position of the base station is estimated through weighted summation, and the signal propagation model of the corresponding base station is built at the same time. The performance of the proposed technology is verified using data acquired in Seocho-dong, Seoul.

• Journal of Korea Multimedia Society
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• v.9 no.9
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• pp.1222-1230
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• 2006

Location-Based Service (LBS) is a service provided to the user based on the user's current geographic location. Since LBS provides a higher value-added service, LBS has been applied on various businesses, industries and even on personal lives. Positioning users is the essential technology in building an LBS system. Thanks to GPS (Global Positioning System), Positioning outdoor is successfully used in practice. However, there is not a general solution for indoor positioning yet, even though many strategies for indoor positioning have been introduced. One of the reasons for the lack of successful indoor positioning is that most of the existing indoor positioning strategies require special equipments dedicated for positioning. This paper introduces an indoor positioning strategy that does not require any additional equipments. Integrating our indoor positioning strategy with GPS-based outdoor positioning, we have implemented an indoor-outdoor positioning system. Experimental results of the system is also introduced.

• International Journal of Advanced Culture Technology
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• v.9 no.4
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• pp.302-306
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• 2021

Indoor localization is one of the basic elements of Location-Based Service, such as indoor navigation, location-based precision marketing, spatial recognition of robotics, augmented reality, and mixed reality. We propose a Voxel Labeling-based visual positioning system using object simultaneous localization and mapping (SLAM). Our method is a method of determining a location through single image 3D cuboid object detection and object SLAM for indoor navigation, then mapping to create an indoor map, addressing it with voxels, and matching with a defined space. First, high-quality cuboids are created from sampling 2D bounding boxes and vanishing points for single image object detection. And after jointly optimizing the poses of cameras, objects, and points, it is a Visual Positioning System (VPS) through matching with the pose information of the object in the voxel database. Our method provided the spatial information needed to the user with improved location accuracy and direction estimation.

• Journal of Industrial Technology
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• v.28 no.A
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• pp.97-104
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• 2008

Recently, interests on positioning system for location-based services have been significantly increased. Many indoor environment systems using fingerprint scheme have been designed to take more accuracy of positioning, but they are inefficient in adapting to change of environments. In this paper, we focus on a client-based positioning system over WLAN for decreasing installation cost and adapting to change of environments. In the proposed system, APs with stable RSSI are selected as base APs independently for each reference point. Experimental results show that proposed system expands service area approximately 20% much than traditional systems using K-NN algorithm and needs only 20% modification process to fingerprint data compare with traditional systems whenever environment conditions are changed.