• 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.

• 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.

• Journal of the Korean Society of Visualization
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• v.20 no.2
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• pp.21-27
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• 2022

Air purifiers can be placed where the air cleaning is required, making it easy to manage indoor air quality. The position of the air purifier affects the indoor airflow pattern, resulting in different air cleaning efficiency. Many efforts and strategies have been examined through numerical simulations and experiments to find the proper location of the air purifier, but problems still remain due to the various geometrical indoor spaces and arrangements. Herein, we develop an artificial intelligence model to predict the performance of an air purifier depending on the installation location. To obtain the training data, numerical simulations were performed on the different locations of the air purifiers and airflow patterns. The trained artificial intelligence model predicted the air exchange performance depending on the installation location of the air purifier with a prediction accuracy of 92%.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.05a
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• pp.241-243
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• 2015

Recently, There is increasing interest in the IoT(Internet of Thing) as intelligent information service that enables communication between people and things based on internet. In particular the demand for indoor location-based services with the development of smart devices is rapidly increasing. If iBeacon of BLE(Bluetooth Low Energy) is made available to provide a basic signal for the indoor location information measurement then reliability of Indoor location information for unreliable signal data for a variety of reasons, such as signal interference is significantly lowered. In this paper, Proposes a technique for obtaining an effective and reliable location information via genetic operations in order to obtain reliable location information from the iBeacon signal information.

• 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.

• Spatial Information Research
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• v.23 no.3
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• pp.113-122
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• 2015

Recently, according to developing advanced construction technologies, buildings has been enlarged such as high-rise buildings or complex buildings associated with underground facilities. The number of indoor activity population has increased very quickly. Because of that, technical requirements for Indoor location based service (Indoor LBS) also have been increased. Although indoor networks have to be constructed for efficient LBSs in indoor space based on OGC IndoorGML, it is not suitable for large and complex space to apply the simple network structure to constructing indoor navigation networks. The indoor navigation network has to be constructed according to logical, physical, and functional constraints for indoor space. In order to do that, subspacing methods are required to partition large and complex indoor space into proper size of subspace. In this paper, we proposed the basic requirements of subspacing in indoor space for creating efficient indoor network, as well the work process of subspacing in indoor space.

• Smart Media Journal
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• v.4 no.2
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• pp.68-76
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• 2015

Recently, research on indoor locating techniques using smart device sensors has been conducted actively, Owing to the exponential increase in the use of various smart devices. However, in order to develop indoor location techniques, there are limitations due to the requirement that the tracking system has to function without GPS. In this paper, we propose an accurate indoor locating system that does not require additional infrastructure. The proposed scheme is developed based on the idea that the advantages and disadvantages of "Wi-Fi Fingerprinting" and "Step Detection" techniques are complementary. In the proposed scheme, we track users with "Step Detection," and correct errors with "Wi-Fi Fingerprinting." In this paper, we demonstrate the effectiveness and feasibility of our proposed scheme through experiments.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.4
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• pp.1611-1629
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• 2016

Recently, deploying WiFi access points (APs) for facilitating indoor localization has attracted increasing attention. However, most existing mechanisms in this aspect are typically simulation based and further they did not consider how to jointly utilize pre-existing APs in target environment and newly deployed APs for achieving high localization performance. In this paper, we propose a measurement-based AP deployment mechanism (MAPD) for placing APs in target indoor environment for assisting fingerprint based indoor localization. In the mechanism design, MAPD takes full consideration of pre-existing APs to assist the selection of good candidate positions for deploying new APs. For this purpose, we first choose a number of candidate positions with low location accuracy on a radio map calibrated using the pre-existing APs and then use over-deployment and on-site measurement to determine the actual positions for AP deployment. MAPD uses minimal mean location error and progressive greedy search for actual AP position selection. Experimental results demonstrate that MAPD can largely reduce the localization error as compared with existing work.

• Journal of Advanced Navigation Technology
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• v.19 no.6
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• pp.558-563
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• 2015

There have recently been various services that use indoor location estimation technologies. Representative methods of location estimation include fingerprinting and triangulation, but they lack accuracy. Various kinds of research which apply existing location estimation methods like AOA, TOA, and TDOA are being done to solve this problem. In this paper, we study the location estimation algorithm based on AOA using a RSSI difference in indoor environments. We assume that there is a single AP with four antennas, and estimate the angle of arrival based on the RSSI value to apply the AOA algorithm. To compensate for RSSI, we use a recursive averaging filter, and use the corrected RSSI and the Pythagorean theorem to estimate the angle of arrival. The results of the experiment, show an error of 18% because of the radiation pattern of the four non-directional antennas arranged at narrow intervals.

• Journal of Advanced Marine Engineering and Technology
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• v.36 no.6
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• pp.850-856
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• 2012

Bilateration using two fixed nodes has been used in the field of the real time indoor location system in the narrow space such as building or ship passage. However, as the distance between the fixed nodes increases or any obstructions exist in their zone, it is difficult to detect the location of mobile node(user) due to the degradation of its reception ratio. In order to compensate for these problems, this paper presents, based on IEEE 802.15.4a chirp signal, a new real time indoor location system using stride measurement algorithm which can calculate the location through sensors attached to user. The proposed system consists of an ultrasonic sensor to measure the leg length, a geomagnetic sensor to recognize the user's orientation, and an inertial sensor to obtain the angle between the legs. The experimental results are shown that the proposed system has twice or more accurate output compared with conventional indoor location method in the section which is partially out of communication reachability.