• 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.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.10
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• pp.2579-2585
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• 2014

Location-Based Services can be defined as services that integrated a mobile network device's position with other information so as to provide added value to users. One of the most important elements in the LBS is the ability to locate objects. In this paper, the positioning techniques using radio signal were introduced, and the positioning principles and accuracies for LBS of smart phone were analyzed. As a result, the some techniques for improving user security were suggested.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.9
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• pp.2961-2975
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• 2022

The Location-Based Service (LBS) is one of the most well-known services on the Internet. Positioning is the primary association with LBS services. This study proposes an intelligent LoRa-based positioning system, called AI@LBS, to provide accurate location data. The fingerprint mechanism with the clustering algorithm in unsupervised learning filters out signal noise and improves computing stability and accuracy. In this study, data noise is filtered using the DBSCAN (Density-Based Spatial Clustering of Applications with Noise) algorithm, increasing the positioning accuracy from 95.37% to 97.38%. The problem of data imbalance is addressed using the SMOTE (Synthetic Minority Over-sampling Technique) technique, increasing the positioning accuracy from 97.38% to 99.17%. A field test in the NTUST campus (www.ntust.edu.tw) revealed that AI@LBS system can reduce average distance error to 0.48m.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.42 no.1
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• pp.9-15
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• 2005

Most of location systems use RF signal. Because multipath is too severe at indoor environment, RF signal are usually used in outdoor positioning such as GPS. To overcome the difficulty at indoor positioning, m positioning is recently developed and is being vigorously studied. Some standardizations on UWB are in progress at IEEE 802.15 committee. In developing UWB positioning system, we should consider the synchronization of sensor network, positioning algorithm, sensor allocation, and so on. This paper presents a comparison of TDOA positioning algorithms that are widely used in location systems. Two algorithms are compared; one is derived by linearization, and the other is by analytic solution(CH algorithm). Simulation results show that the CH algorithm is superior to the linearized least square at indoor environment in that CH algorithm shows consistent positioning performance regardless of the visibility and geometry of basestations.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.1
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• pp.251-256
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• 2006

In the work package 'Integrated Positioning' of the research project NAVIO (Pedestrian Navigation Systems in Combined Indoor/Outdoor Environements) we are dealing with the navigation and guidance of visitors of our University. Thereby start points are public transport stops in the surroundings of the Vienna University of Technology and the user of the system should be guided to certain office rooms or persons. For the position determination of the user different location sensors are employed, i.e., for outdoor positioning GPS and dead reckoning sensors such as a digital compass and gyro for heading determination and accelerometers for the determination of the travelled distance as well as a barometric pressure sensor for altitude determination and for indoor areas location determination using WiFi fingerprinting. All sensors and positioning methods are combined and integrated using a Kalman filter approach. Then an optimal estimate of the current location of the user is obtained using the filter. To perform an adequate weighting of the sensors in the stochastic filter model, the sensor characteristics and their performance was investigated in several tests. The tests were performed in different environments either with free satellite visibility or in urban canyons as well as inside of buildings. The tests have shown that it is possible to determine the user's location continuously with the required precision and that the selected sensors provide a good performance and high reliability. Selected tests results and our approach will be presented in the paper.

• Journal of Positioning, Navigation, and Timing
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• v.11 no.4
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• pp.369-379
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• 2022

In weighted k-nearest neighbor (WkNN)-based Fingerprinting positioning step, a process of comparing the requested positioning signal with signal information for each reference point stored in the fingerprint DB is performed. At this time, the higher the number of matched base station identifiers, the higher the possibility that the terminal exists in the corresponding location, and in fact, an additional weight is added to the location in proportion to the number of matching base stations. On the other hand, if the matching number of base stations is small, the selected candidate reference point has high dependence on the similarity value of the signal. But one problem arises here. The positioning signal can be compared with the repeater signal in the signal information stored on the DB, and the corresponding reference point can be selected as a candidate location. The selected reference point is likely to be an outlier, and if a certain weight is applied to the corresponding location, the error of the estimated location information increases. In order to solve this problem, this paper proposes a WkNN technique including an outlier removal function. To this end, it is first determined whether the repeater signal is included in the DB information of the matched base station. If the reference point for the repeater signal is selected as the candidate position, the reference position corresponding to the outlier is removed based on the clustering technique. The performance of the proposed technique is verified through data acquired in Seocho 1 and 2 dongs in Seoul.

• Journal of the Korea Society of Computer and Information
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• v.16 no.8
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• pp.147-155
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• 2011

Map rendering, positioning, database managements are key elements of location based services. Google map and GPS (Global Positioning System) have become a very popular solution for map rendering and positioning, respectively. They are very effective and yet free of charge. However, they cannot be used for an indoor location based service system. We cannot render a building drawing with Google map, we cannot determine a moving object's position when it is indoor. This paper introduces our web services of rendering drawings, indoor positioning, and multimedia contents up-loading and playing so that any programmers can use them in developing indoor location based service systems. In order to experimentally show the efficiency of our web services, we have built a location based contents displaying system for museum visitors with them.

• Journal of Korea Multimedia Society
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• v.21 no.5
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• pp.583-591
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• 2018

With the development of ICT(Information and Communication Technology), the number of smart devices is rapidly increasing. LBS(Location Based Service) applications that provide user's location based service are used in various fields. There is also a growing demand for indoor precision positioning technology to provide seamless services. In this paper, we propose an indoor positioning system that estimates the location of a smartphone user. The proposed algorithm determines whether the received signal is LOS(Line-of-Sight) or NLOS(Non-Line of-Sight) in order to decrease multipath effect by the indoor environment. The proposed positioning algorithm is very simple and requires only the AP(Access Point) coordinates. In addition, it requires only two APs for estimating the location of a smartphone user. The proposed algorithm is a practically applicable technology without any additional hardware and kernel modification in the smartphone. In the experiment results, the reliability of the positioning system was found to be within 0.83 m.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.1
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• pp.70-75
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• 2015

With the development of communication technologies and smartphone, requirements of positioning accuracy for LBS (Location Based Service) are becoming increasingly important. LBS is a service which offers the information or entertainment based on a location to users. Therefore, positioning is very important for LBS. Among many positioning methods, IEEE 802.11 WLAN positioning measures the distance using the RSSI (Received Signal Strength Indicator) attenuation log model. Thus in order to enhance positioning, we modify the IEEE 802.11 RSSI attenuation log model by adaptive weighting method. In this paper, we propose improved IEEE 802.11 RSSI attenuation log model for enhanced indoor positioning.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.564-567
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• 2007

GPS(Global Positioning System) data has a high accuracy at outdoor positioning generally, but its accuracy decreases in the urban areas with dense buildings. Moreover insufficient number of satelllites prevent us GPS positioning at inside of buildings. To complement these shortcomings of GPS, RFID(Radio Frequency IDentification) has been studied on indoor positioning parts. In Ubiquitous environment, LBS(Location Based Service) which can be used anytime and anywhere is an essential component. We use kalman filter to estimate the real location in GPS and RFID handover area. This study's purpose is to make a continuous positioning system using interlocking RFID and GPS.