scholarly journals Big Data Analytics and Intelligent Transportation Systems

2021 ◽  
Vol 54 (2) ◽  
pp. 216-220
Author(s):  
Jairo R. Montoya-Torres ◽  
Sebastian Moreno ◽  
William J. Guerrero ◽  
Gonzalo Mejía
Keyword(s):  
Big Data ◽  
Intelligent Transportation Systems ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Intelligent Transportation ◽  
Transportation Systems

Big Data Processing and Mining for Next Generation Intelligent Transportation Systems

2013 ◽  
Vol 63 (3) ◽  
Author(s):  
Jelena Fiosina ◽  
Maxims Fiosins, Jörg P. Müller
Keyword(s):  
Big Data ◽  
Data Processing ◽  
Real World ◽  
Intelligent Transportation Systems ◽  
Social Impact ◽  
Intelligent Transportation ◽  
Transportation Systems ◽  
Optimization Techniques ◽  
Next Generation ◽  
Big Data Processing

The deployment of future Internet and communication technologies (ICT) provide intelligent transportation systems (ITS) with huge volumes of real-time data (Big Data) that need to be managed, communicated, interpreted, aggregated and analysed. These technologies considerably enhance the effectiveness and user friendliness of ITS, providing considerable economic and social impact. Real-world application scenarios are needed to derive requirements for software architecture and novel features of ITS in the context of the Internet of Things (IoT) and cloud technologies. In this study, we contend that future service- and cloud-based ITS can largely benefit from sophisticated data processing capabilities. Therefore, new Big Data processing and mining (BDPM) as well as optimization techniques need to be developed and applied to support decision-making capabilities. This study presents real-world scenarios of ITS applications, and demonstrates the need for next-generation Big Data analysis and optimization strategies. Decentralised cooperative BDPM methods are reviewed and their effectiveness is evaluated using real-world data models of the city of Hannover, Germany. We point out and discuss future work directions and opportunities in the area of the development of BDPM methods in ITS.

scholarly journals Big Data analysis: Intelligent Transportation Development Engine

2014 ◽  
Vol 1 (1) ◽  
pp. 11
Author(s):  
Qin Xiao
Keyword(s):  
Big Data ◽  
Intelligent Transportation Systems ◽  
Low Cost ◽  
Information Age ◽  
Large Data ◽  
Intelligent Transportation ◽  
Transportation Systems ◽  
Transportation Demand ◽  
Advantages And Disadvantages ◽  
Transportation Development

<p>With the development of the times, people have unwittingly entered the information age. The information age has become a large amount of data bursting characteristics of the new era. In this feature people still seek to improve the production and quality of life. For the development of intelligent transportation needs of people's lives and make the real world, but in the construction of intelligent transportation among a large number of information data also adds to its change and difficulty, how to build an intelligent era of big data, security, low-cost, efficient and convenient of intelligent transportation systems become today people study. From the era of big data to intelligent traffic changes brought advantages and disadvantages, the era of big data to bring intelligent traffic problems and challenges, as well as the integration platform for massive data intelligent transportation intelligent transportation demand and large data structures has done a simple elaborate, it can provide some suggestions for areas of research that scientists.</p>

scholarly journals Threshold Key Management Scheme for Blockchain-Based Intelligent Transportation Systems

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Tianqi Zhou ◽  
Jian Shen ◽  
Yongjun Ren ◽  
Sai Ji
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Intelligent Transportation Systems ◽  
Key Management ◽  
Intelligent Transportation ◽  
Transportation Systems ◽  
Important Application ◽  
Management Scheme ◽  
Management Schemes ◽  
Key Management Scheme

Intelligent transportation systems (ITS) have always been an important application of Internet of Things (IoT). Today, big data and cloud computing have further promoted the construction and development of ITS. At the same time, the development of blockchain has also brought new features and convenience to ITS. However, due to the endless emergence of increasingly advanced types of attacks, the security of blockchain-based ITS needs more attention from industry and academia. In this paper, we focus on exploring the primitives in cryptography to guarantee the security of blockchain-based ITS. In particular, the authentication, encryption, and key management schemes in cryptography are discussed. Furthermore, we propose two methods for achieving the threshold key management in blockchain-based ITS. The proposed threshold key management scheme (with threshold t ) enables various stakeholders to recover a secret if the number of participated stakeholders is at least t . It should be noted that the proposed threshold key management scheme is efficient and secure for multiple users in blockchain-based ITS, especially for the data-sharing scenario.

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