• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.28 no.1
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• pp.13-20
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• 2010

Currently, GPS data process software appears different results that according to user's skills or software. Also, lots of time and efforts are necessary for using GPS data process software to general user, not a specialist On the other band, on-line GPS data process service have a merit that can cony out GPS data process without technical efforts and time. In this study, permanent GPS site's observation data of NGII(National Geographic Information Institute) was processed by on-line GPS data process service, and utilization assessment of on-line GPS data process service was performed by comparing this result with notified coordinates by the NGII in order to analyze positional accuracy. 10 permanent GPS sites of NGII including Suwon which is registered in IGS(International GNSS Service) were selected and these GPS observation data was processed by AUSPOS and CSRS-PPP.

• Journal of Korean Society for Geospatial Information Science
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• v.18 no.4
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• pp.31-39
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• 2010

In this study, the performance of the online GPS processing services provided by diverse institutions was compared so that domestic GPS users in geodesy and surveying can easily get precise coordinates using those services. In order to evaluate the accuracy of each online GPS processing service, we calculated coordinates of seven GPS permanent stations located in Korea and foreign countries using APPS, CSRS-PPP, AUSPOS and OPUS. And the results were compared with published coordinates by IERS and National Geographic Information Institute. In the cases of foreign stations, the mean value of the horizontal errors was 9.3 mm and the descending order of accuracies was APPS, AUSPOS, OPUS and CSRS-PPP. In the cases of Korean stations, the mean value of the horizontal errors was 37.6 mm, although the order of accuracy was similar to the foreign cases; AUSPOS, APPS, OPUS and CSRS-PPP. Also, the average value of 3-D errors in Korean cases was about 3 cm larger than that of foreign cases and a bias of 3 cm was observed in the north direction.

• Journal of the Korean Association of Geographic Information Studies
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• v.14 no.2
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• pp.138-146
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• 2011

With the increased use of GPS in the field of various applications including surveying, the request for fast and precise positional information has increased. Several countries such as USA, Canada, and Australia have already been operating Internet-based automatic GPS data analysis system using e-mail and FTP. Expanding GPS market, it is necessary to establish automatic GPS baseline processing system that is accessible via Internet. The system developed in this study is operating on the web, and it allows the users to access easily regardless of time and place. The main processing engines are Bernese V5.0 and PAGES. They process user data with three GPS CORS(Continuously Operating Reference Station), and then send the report to the users through e-mail. This system allows users to process high accurate GPS data easily. It is expected that this system will be used for various GPS applications such as monitoring large-scale structures and providing spatial information services in private sector.

• Journal of Information Processing Systems
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• v.13 no.4
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• pp.951-969
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• 2017

In this paper, we newly propose a traffic information service model that collects traffic information sensed by an individual vehicle in real time by using a smart device, and which enables drivers to share traffic information on all roads in real time using an application installed on a smart device. In particular, when the driver requests traffic information for a specific area, the proposed driver-personalized service model provides him/her with traffic information on the driving directions in advance by predicting the driving directions of the vehicle based on the learning of the driving records of each driver. To do this, we propose a traffic information management model to process and manage in real time a large amount of online-generated traffic information and traffic information requests generated by each vehicle. We also propose a road node-based indexing technique to efficiently store and manage location-based traffic information provided by each vehicle. Finally, we propose a driving learning and prediction model based on the hidden Markov model to predict the driving directions of each driver based on the driver's driving records. We analyze the traffic information processing performance of the proposed model and the accuracy of the driving prediction model using traffic information collected from actual driving vehicles for the entire area of Seoul, as well as driving records and experimental data.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.9
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• pp.603-614
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• 2013

The popularity of mobile devices provides their users with a circumstance that services and information can be accessed wherever and whenever users need. Accordingly, various studies have been proposed personalized methods to improve accessibility of mobile users to information. However, since these personalized methods require users' private information, they gives rise to problems on security. An efficient way to resolve security problems is to estimate user information by using their online and offline behavior. In this paper, for this purpose, it is proposed a novel user information identification system that identifies users' personal and social information by using both his/her behavior on social network services and proximity patterns obtained from GPS data. In the proposed system, personal information of a user like age, gender, and so on is estimated by analyzing SNS texts and POI (Point of Interest) patterns, while social information between a pair of users like family and friend is predicted with proximity patterns between the users. Each identification module is efficiently designed to handle the characteristics of user data like much noise in SNS texts and missing signals in GPS data. In experiments to evaluate the proposed system, our system shows its superiority against ordinary identification methods. This result means that the proposed system can efficiently reflect the characteristics of user data.