Data analytics for intelligent transportation systems /

Data Analytics for Intelligent Transportation Systems provides in-depth coverage of data-enabled methods for analyzing intelligent transportation systems that includes detailed coverage of the tools needed to implement these methods using big data analytics and other computing techniques. The book e...

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Bibliographic Details
Corporate Authors: Elsevier Science & Technology.
Group Author: Chowdhury, Mashrur A.; Apon, Amy; Dey, Kakan
Published: Elsevier,
Publisher Address: Amsterdam :
Publication Dates: [2017]
©2017
Literature type: eBook
Language: English
Subjects:
Online Access: https://www.sciencedirect.com/science/book/9780128097151
Summary: Data Analytics for Intelligent Transportation Systems provides in-depth coverage of data-enabled methods for analyzing intelligent transportation systems that includes detailed coverage of the tools needed to implement these methods using big data analytics and other computing techniques. The book examines the major characteristics of connected transportation systems, along with the fundamental concepts of how to analyze the data they produce. It explores collecting, archiving, processing, and distributing the data, designing data infrastructures, data management and delivery systems, and the required hardware and software technologies. Users will learn how to design effective data visualizations, tactics on the planning process, and how to evaluate alternative data analytics for different connected transportation applications, along with key safety and environmental applications for both commercial and passenger vehicles, data privacy and security issues, and the role of social media data in traffic planning.
Carrier Form: 1 online resource : illustrations
Bibliography: Includes bibliographical references and index.
ISBN: 9780128098516
0128098511
Index Number: TE228
CLC: U491
Contents: 1. Characteristics of Intelligent Transportation Systems and Its Relationship With Data Analytics -- 2. Data Analytics: Fundamentals -- 3. Data Science Tools and Techniques to Support Data Analytics in Transportation Applications -- 4. The Centrality of Data: Data Lifecycle and Data Pipelines -- 5. Data Infrastructure for Intelligent Transportation Systems -- 6. Security and Data Privacy of Modern Automobiles -- 7. Interactive Data Visualization -- 8. Data Analytics in Systems Engineering for Intelligent Transportation Systems -- 9. Data Analytics for Safety Applications -- 10. Data Analytics for Intermodal Freight Transportation Applications -- 11. Social Media Data in Transportation -- 12. Machine Learning in Transportation Data Analytics.