Data Analytics for Intelligent Transportation Systems - Chowdhury, Mashrur; Dey, Kakan; Apon, Amy; (ed.) - Prospero Internet Bookshop

 
Product details:

ISBN13:9780443138782
ISBN10:0443138788
Binding:Paperback
No. of pages:472 pages
Size:234x190 mm
Weight:450 g
Language:English
693
Category:

Data Analytics for Intelligent Transportation Systems

 
Edition number: 2
Publisher: Elsevier
Date of Publication:
 
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EUR 113.00
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Long description:

Data Analytics for Intelligent Transportation Systems, Second Edition provides in-depth coverage of data-enabled methods for analyzing intelligent transportation systems (ITS), including 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. Other sections provide extensive coverage of existing and forthcoming intelligent transportation systems and data analytics technologies. All fundamentals/concepts presented in this book are explained in the context of ITS. Users will learn everything from the basics of different ITS data types and characteristics to how to evaluate alternative data analytics for different ITS applications. In addition, they will discover 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.

Table of 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 13. Quantum Computing in Data Analytics, Mashrur Chowdhury 14. Society and Environment in ITS Data Analytics