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Data analytics for intelligent transportation systems / edited by Mashrur Chowdhury, Amy Apon, Kakan Dey.

Contributor(s): Material type: TextTextPublisher: Amsterdam : Elsevier, [2017]Copyright date: ©2017Description: 1 online resource : illustrationsContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9780128098516
  • 0128098511
Subject(s): Genre/Form: Additional physical formats: Print version:: Data analytics for intelligent transportation systems.DDC classification:
  • 388.3/12 23
LOC classification:
  • TE228.3 .D38 2017eb
Online resources:
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.
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.Includes case studies in each chapter that illustrate the application of concepts coveredPresents extensive coverage of existing and forthcoming intelligent transportation systems and data analytics technologiesContains contributors from both leading academic and commercial researchersExplains how to design effective data visualizations, tactics on the planning process, and how to evaluate alternative data analytics for different connected transportation applications.”--Publisher’s description.
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Item type Home library Collection Call number Materials specified Status Date due Barcode
Electronic-Books Electronic-Books OPJGU Sonepat- Campus E-Books EBSCO Available

Includes bibliographical references and index.

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.

“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.Includes case studies in each chapter that illustrate the application of concepts coveredPresents extensive coverage of existing and forthcoming intelligent transportation systems and data analytics technologiesContains contributors from both leading academic and commercial researchersExplains how to design effective data visualizations, tactics on the planning process, and how to evaluate alternative data analytics for different connected transportation applications.”--Publisher’s description.

Print version record.

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