Data Analytics for Intelligent Transportation Systems

Data Analytics for Intelligent Transportation Systems

ISBN-10:
0128097159
ISBN-13:
9780128097151
Pub. Date:
04/04/2017
Publisher:
Elsevier Science
ISBN-10:
0128097159
ISBN-13:
9780128097151
Pub. Date:
04/04/2017
Publisher:
Elsevier Science
Data Analytics for Intelligent Transportation Systems

Data Analytics for Intelligent Transportation Systems

$130.0
Current price is , Original price is $130.0. You
$130.00 
  • SHIP THIS ITEM
    Temporarily Out of Stock Online
  • PICK UP IN STORE
    Check Availability at Nearby Stores
  • SHIP THIS ITEM

    Temporarily Out of Stock Online

    Please check back later for updated availability.

Temporarily Out of Stock Online


Overview

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.


Product Details

ISBN-13: 9780128097151
Publisher: Elsevier Science
Publication date: 04/04/2017
Edition description: New Edition
Pages: 344
Product dimensions: 7.50(w) x 9.25(h) x (d)

About the Author

Mashrur Chowdhury is Eugene Douglas Mays Chaired Professor of Transportation in the Glenn Department of Civil Engineering at Clemson University. He is the Director of USDOT Center for Connected Multimodal Mobility and Co-Director of the Complex Systems, Analytics, and Visualization Institute at Clemson. His research focuses on connected and automated vehicles with an emphasis on their integration within smart cities.

Dr. Amy Apon has been Professor and Chair of the Computer Science Division in the School of Computing at Clemson University since 2011. She was on leave from Clemson as a Program Officer in the Computer Network Systems Division of the National Science Foundation during 2015, working on research programs in Big Data, EXploiting Parallelism and Scalability, and Computer Systems Research. Apon established the High Performance Computing Center at the University of Arkansas and directed the center from 2005 to 2011. She has more than 100 scholarly publications in areas of cluster computing, performance analysis of high performance computing systems, and scalable data analytics. She is a Senior Member of the Association for Computing Machinery and a Senior Member of the Institute of Electrical and Electronics Engineers. Apon holds a Ph.D. in Computer Science from Vanderbilt University.

Kakan Dey is Assistant Professor and Director of the Connected and Automated Transportation Systems (CATS) Lab at the West Virginia University. His primary research area is intelligent transportation systems, which include connected and automated vehicle technology, data science, cyber-physical systems, and smart cities.

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

What People are Saying About This

From the Publisher

This informative guide demonstrates how data analytics can improve transportation-related management decisions, mobility, efficiency, and environmental impacts

From the B&N Reads Blog

Customer Reviews