• Journal of the Korea Society of Computer and Information
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• v.27 no.1
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• pp.77-82
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• 2022

The research study was conducted for development of the advanced image analysis service system based on deep learning. CNN(Convolutional Neural Network) is built in this system to extract learning data collected from Google and Instagram. The service gets a place image of Jeju as an input and provides relevant location information of it based on its own learning data. Accuracy improvement plans are applied throughout this study. In conclusion, the implemented system shows about 79.2 of prediction accuracy. When the system has plenty of learning data, it is expected to predict various places more accurately.

• Journal of the Korea Society of Computer and Information
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• v.14 no.12
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• pp.89-96
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• 2009

A lot of information is contained in an image or a movie rather than in a text, and it is very important thing to extract context from them. In this study, we propose a method to detect an open/closed eye and determine the location of a pupil in an eye image which is extracted from a movie. The image is normalized using transformation into bipolarization with white and black color and horizontalizing, and we measure width and height of an eye. With these information, we can determine the open or closed eye and the location of the pupil. Experiments were done with 52 images of eyes from movies using this method, and we get good results with 98% of correctness in detection of open/closed eyes and 95% in detection of pupil's location.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.456-457
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• 2021

Recently, in order to more accurately provide indoor location-based services, technologies using Wi-Fi fingerprints and deep learning are being studied. Among the deep learning models, an RNN model that can store information from the past can store continuous movements in indoor positioning, thereby reducing positioning errors. When using an RNN model for indoor positioning, the collected training data must be continuous sequential data. However, the Wi-Fi fingerprint data collected to determine specific location information cannot be used as training data for an RNN model because only RSSI for a specific location is recorded. This paper proposes a region clustering technique for sequential input data generation of RNN models based on Wi-Fi fingerprint data.

• Journal of Cadastre & Land InformatiX
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• v.48 no.2
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• pp.109-119
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• 2018

Point of interest (POI) of the city is a special place that has what importance to the user. For example, it is such landmark, restaurants, museums, hotels, and theaters. Because of its role in the social and economic life of us, these have attracted a lot of interest in location-based applications such as social networks and online map. However, while it can easily be obtained through the Web, the basic information of POI such as geographic location, another effort is required to obtain detailed information such as Wi-Fi, accepting credit cards, opening hours, romper room and the assessment and evaluation of other users. To solve these problems, a new method for correcting position error is required to link location-based social network service (LBSNS) data and POIs. This paper attempts to propose a position error correction method of POI and LBSNS data to enrich POI information from the vast information that is accumulated in LBSNS. Through this study, we can overcome the limitation of individual POI information via the information fusion method of LBSNS and POI, and we have discovered the possibility to be able to provide additional information which users need. As a result, we expect to be able to collect a variety of POI information quickly.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.11 no.2
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• pp.231-236
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• 2011

In recent years, LBS(Location Based Service) is applied in many different fields. Therefore, various location-aware schemes have been studied. In the location awareness system using time dependent algorithm, TOA(Time of Arrival) or TDOA(Time Difference of Arrival) algorithm, distortion of a signal by AWGN(Additive White Gaussian Noise) and multi-path effects cause the degradation of location awareness performance. In this paper, the unexpected noise is eliminated by averaging multiple pulses in order to overcome the degradation of performance. Also, we research the technique for improving the performance of the location awareness by detecting direct-path signal with adjusting threshold.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.5
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• pp.1909-1928
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• 2020

Predicting human mobility has always been an important task in Location-based Social Network. Previous efforts fail to capture spatial dependence effectively, mainly reflected in weakening the location topology information. In this paper, we propose a neural network-based method which can capture spatial-temporal dependence to predict the next location of a person. Specifically, we involve a graph convolutional network (GCN) based on a seq2seq framework to capture the location topology information and temporal dependence, respectively. The encoder of the seq2seq framework first generates the hidden state and cell state of the historical trajectories. The GCN is then used to generate graph embeddings of the location topology graph. Finally, we predict future trajectories by aggregated temporal dependence and graph embeddings in the decoder. For evaluation, we leverage two real-world datasets, Foursquare and Gowalla. The experimental results demonstrate that our model has a better performance than the compared models.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.5
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• pp.1951-1966
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• 2020

Recent advancements in mobile device technology have enabled real-time positioning so that mobile patterns of people and favorable locations can be identified and related researches have become plentiful. One of the fields of research is the relationship between the object properties and the favored location to visit. The object properties of a person include personality, which is a major property jobs, income, gender, and age. In this study, we analyzed the relationship between the human personality and the preference of the location to visit. We used Spearman's Rank correlation coefficient, one of the many methods that can be used to determine the correlation between two variables. Instead of using actual data values, Spearman's Rank correlation coefficient deals with the ranks of the two data sets. In our research, the personality and the location data sets are used. Our personality data is ranked in five ranks and the location data is ranked in 8 ranks. Spearman's Rank correlation coefficient showed better results compared to Pearson linear correlation coefficient and Kendall rank correlation coefficient. Using Spearman's correlation coefficient, the degree of the relationship between the personality and the location preference is found to be 43%.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.2
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• pp.1162-1179
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• 2017

In this paper, we propose indoor location tracking method using RSSI(Received Signal Strength Indicator) value received from BLE(Bluetooth Low Energy) beacon. Due to the influence of various external environmental factors, it is very difficult to improve the accuracy in indoor location tracking. In order to solve this problem, we propose a novel method of reducing the noise generated in the external environment by using a double Gaussian filter. In addition, the value of the RSSI signal generated in the BLE beacon is different for each device. In this study, we propose a method to allocate additional weights in order to compensate the intensity of signal generated in each device. This makes it possible to improve the accuracy of indoor location tracking using beacons. The experiment results show that the proposed method effectively decrease the RSSI deviation and increase location accuracy. In order to verify the usefulness of this study, we compared the Kalman filter algorithm which is widely used in signal processing. We further performed additional experiments for application area for indoor location service and find that the proposed scheme is useful for BLE-based indoor location service.

• Journal of Information Processing Systems
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• v.7 no.1
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• pp.121-136
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• 2011

With the rapid growth of GPS-enable Smartphones, the interest on using Location Based Services (LBSs) has increased significantly. The evolution in the functionalities provided by those smartphones has enabled them to accurately pinpoint the location of a user. Because location information is what all LBSs depend on to process user's request, it should be properly protected from attackers or malicious service providers (SP). Additionally, maintaining user's privacy and confidentiality are imperative challenges to be overcome. A possible solution for these challenges is to provide user anonymity, which means to ensure that a user initiating a request to the SP should be indistinguishable from a group of people by any adversary who had access to the request. Most of the proposals that maintain user's anonymity are based on location obfuscation. It mainly focuses on adjusting the resolution of the user's location information. In this paper, we present a new protocol that is focused on using cryptographic techniques to provide anonymity for LBSs users in the smartphone environment. This protocol makes use of a trusted third party called the Anonymity Server (AS) that ensures anonymous communication between the user and the service provider.

• Journal of information and communication convergence engineering
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• v.3 no.2
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• pp.80-83
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• 2005

At present, GML becomes the global standard for the XML encoding of geographic information and is the foundation for the Geo-Web. GML is being applied to a wide range of geographic applications including GIS and location-based services, telematics and intelligent transportation systems. In this paper, we propose the tourism information system for supporting the location based service application. We made an effort to design and implement a GIS computing environment by thin client for mobile web mapping service. We are interested in the GML applications that include traditional GIS system for navigation service and location finder for points of interest (POI) services. This paper summarizes the Tourism information system for location based service of a small area (Han-Ok Village with the Korean traditional houses in Jeonju-city), in which moving travelers can obtain proper information services at the current location associated with traditional monuments, cultural products, food, and conveniences. In the paper, we report on the design of the thin client/server system for a mobile environment. This paper is divided into three parts. First, we give a general overview of the organization of the system and of the important concerns of our design. Second we focus on our system supports for location and POI determination, and design concerns. Finally, we show the graphic user interface of PDA, the procedures involved in the service, and the executed results.