• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.10 no.5
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• pp.60-70
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• 2011

Vehicle location detection and wireless communication method have be designed along the same lines as GPS, CDMA and WLAN, which is based upon the selecting factors such as state-of-art technology trend, accuracy, stability, and economic feasibility, in order to select the optimum method of information communication networks for integrated "Transportation-Power-Facilities" on the electric bus. In addition, the key features of each alternative for an efficient linkage have been review and the integration methodology for linking among Transportation Charging Center, Transportation(ITS, BIS) Center and smart Grid Center has been drawn up based on a technical level of difficulty of each alternative, political and administrative difficulties, and expense justification.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.12 no.1
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• pp.109-114
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• 2012

Intelligent Transportation Systems (ITS) is aimed to implement IT(Information Technology) to develop the next-generation transportation system in order to improve traffic conditions. In order to provide traffic information, the methods that provide available traffic informations to the public are needed. In this paper, analysis of the transportation applications in smart-phone and currently available methods of traffic information's sharing and providing were discussed. Finally, OPEN API was discussed and shows its effectiveness for transportation information area especially in smart phone.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.3
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• pp.1510-1532
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• 2017

In smart grid, privacy implications to individuals and their families are an important issue because of the fine-grained usage data collection. Wireless communications are utilized by many utility companies to obtain information. Network coding is exploited in smart grids, to enhance network performance in terms of throughput, delay, robustness, and energy consumption. However, random linear network coding introduces a new challenge for privacy preserving due to the encoding of data and updating of coefficients in forwarder nodes. We propose a distributed privacy preserving scheme for random linear network coding in smart grid that considers the converged flows character of the smart grid and exploits a homomorphic encryption function to decrease the complexities in the forwarder node. It offers a data confidentiality privacy preserving feature, which can efficiently thwart traffic analysis. The data of the packet is encrypted and the tag of the packet is encrypted by a homomorphic encryption function. The forwarder node random linearly codes the encrypted data and directly processes the cryptotext tags based on the homomorphism feature. Extensive security analysis and performance evaluations demonstrate the validity and efficiency of the proposed scheme.

• 한국ITS학회지
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• v.4 no.1
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• pp.7-16
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• 2007

• 한국ITS학회지
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• v.4 no.1
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• pp.25-29
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• 2007

• Journal of Digital Convergence
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• v.16 no.4
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• pp.87-94
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• 2018

Intelligent transportation systems are one of the most important new forms of infrastructure on domestic roads, and is a system that makes possible the most efficient movement of vehicles on a road. The High Pass system, which is a domestic intelligent transportation system, started a little later than in other countries but developed at a rapid pace. With the recent introduction of smart tolling technology, it provided an opportunity to stop and review the tolling system. This study aims to investigate the driving method and results of LDCC for domestic smart towing through case study. Unlike other companies, Lotte Data Communication Company has long invested in payment systems. It has little experience investing in infrastructure, but participated in the Smart Toll System at the Gwangan Bridge in cooperation with the Busan City government, to lead the development of intelligent transportation systems. LDCC, which has made new investments, not only exceeded its existing core competencies, but also upgraded Korea's tolling system's ability to reduce greenhouse gas emissions and improved its financial performance.

• Journal of Information Processing Systems
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• v.14 no.6
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• pp.1464-1479
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• 2018

In face recognition, sometimes the number of available training samples for single category is insufficient. Therefore, the performances of models trained by convolutional neural network are not ideal. The small sample face recognition algorithm based on novel Siamese network is proposed in this paper, which doesn't need rich samples for training. The algorithm designs and realizes a new Siamese network model, SiameseFacel, which uses pairs of face images as inputs and maps them to target space so that the $L_2$ norm distance in target space can represent the semantic distance in input space. The mapping is represented by the neural network in supervised learning. Moreover, a more lightweight Siamese network model, SiameseFace2, is designed to reduce the network parameters without losing accuracy. We also present a new method to generate training data and expand the number of training samples for single category in AR and labeled faces in the wild (LFW) datasets, which improves the recognition accuracy of the models. Four loss functions are adopted to carry out experiments on AR and LFW datasets. The results show that the contrastive loss function combined with new Siamese network model in this paper can effectively improve the accuracy of face recognition.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.5
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• pp.183-196
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• 2022

Public transportation accessibility has been evaluated through minimum level of service for public transportation. However it is evaluated based operators rather than users. This study analyzed the users' accessibility(first-mile, last-mile) to public transportation using altteul transport card data. As a result of user's accessibility of public transportation, rural areas was lower than that in the urban areas. This study calssified type 1 and 2 based average approach time, and average approach time of Type 1 and 2 were more than average approach time of total area. We propsed an efficient introduction of autonomous public transportation on-demand service using delphi survey. As a result of delphi survey, experts agreed on 9 items regarding function, service item, route operation, approach distance, route mileage, punctuality.

• International Journal of Computer Science & Network Security
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• v.23 no.5
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• pp.163-171
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• 2023

The intelligent transportation system has made a huge leap in the level of human services, which has had a positive impact on the quality of life of users. On the other hand, these services are becoming a new source of risk due to the use of data collected from vehicles, on which intelligent systems rely to create automatic contextual adaptation. Most of the popular privacy protection methods, such as Dummy and obfuscation, cannot be used with many services because of their impact on the accuracy of the service provided itself, they depend on changing the number of vehicles or their physical locations. This research presents a new approach based on the shuffling Nicknames of vehicles. It fully maintains the quality of the service and prevents tracking users permanently, penetrating their privacy, revealing their whereabouts, or discovering additional details about the nature of their behavior and movements. Our approach is based on creating a central Nicknames Pool in the cloud as well as distributed subpools in fog nodes to avoid intelligent delays and overloading of the central architecture. Finally, we will prove by simulation and discussion by examples the superiority of the proposed approach and its ability to adapt to new services and provide an effective level of protection. In the comparison, we will rely on the wellknown privacy criteria: Entropy, Ubiquity, and Performance.

• IEIE Transactions on Smart Processing and Computing
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• v.5 no.6
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• pp.430-439
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• 2016

Estimation and analysis of traffic jams plays a vital role in an intelligent transportation system and advances safety in the transportation system as well as mobility and optimization of environmental impact. For these reasons, many researchers currently mainly focus on the brilliant machine learning-based prediction approaches for traffic prediction systems. This paper primarily addresses the analysis and comparison of prediction accuracy between two machine learning algorithms: Naïve Bayes and K-Nearest Neighbor (K-NN). Based on the fact that optimized estimation accuracy of these methods mainly depends on a large amount of recounted data and that they require much time to compute the same function heuristically for each action, we propose an approach that applies multi-threading to these heuristic methods. It is obvious that the greater the amount of historical data, the more processing time is necessary. For a real-time system, operational response time is vital, and the proposed system also focuses on the time complexity cost as well as computational complexity. It is experimentally confirmed that K-NN does much better than Naïve Bayes, not only in prediction accuracy but also in processing time. Multi-threading-based K-NN could compute four times faster than classical K-NN, whereas multi-threading-based Naïve Bayes could process only twice as fast as classical Bayes.