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Innovative applications of big data ...

Easton, John M.,

Innovative applications of big data in the railway industry

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Innovative applications of big data in the railway industryShruti Kohli, A.V. Senthil Kumar, John M. Easton and Clive Roberts, editors.
其他作者:	Kohli, Shruti,
出版者:	Hershey, Pennsylvania :IGI Global,[2018]
面頁冊數:	1 online resource (xviii, 395 p.)
標題:	RailroadsManagement.
電子資源:	http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-5225-3176-0
ISBN:	9781522531777 (ebook)

Innovative applications of big data in the railway industry
Innovative applications of big data in the railway industry[electronic resource] /Shruti Kohli, A.V. Senthil Kumar, John M. Easton and Clive Roberts, editors. - Hershey, Pennsylvania :IGI Global,[2018] - 1 online resource (xviii, 395 p.)

Includes bibliographical references and index.

Section 1. Concepts and approaches. Chapter 1. Big data in railway O&M: a dependability approach ; Chapter 2. Blockchains: a distributed data ledger for the rail industry ; Chapter 3. Visual and lidar data processing and fusion as an element of real time big data analysis for rail vehicle driver support systems ; Chapter 4. Wayside train monitoring systems: origin and application -- Section 2. Innovations and technologies. Chapter 5. Scalable software framework for real-time data processing in the railway environment ; Chapter 6. Predicting behavior of passengers using data collected through smart cards ; Chapter 7. Dynamic behavior analysis of railway passengers ; Chapter 8. Intelligent transport systems services in vanets and case study in urban environment -- Section 3. Big data and text mining. Chapter 9. Study and analysis of delay factors of Delhi metro using data sciences and social media: automatic delay prediction system for Delhi metro ; Chapter 10. Social media as a tool to understand behaviour on the railways ; Chapter 11. Big data and natural language processing for analysing railway safety: analysis of railway incident reports -- Section 4. Applications and use cases. Chapter 12. Evolution of Indian railways through IOT ; Chapter 13. Application of big data technologies for quantifying the key factors impacting passenger journey in a multi-modal transportation environment ; Chapter 14. Big data analytics for train delay prediction: a case study in the Italian railway network.

Restricted to subscribers or individual electronic text purchasers.

"This book explores how big data technologies can address the operational challenges in the railway industry. It assists academics working in the big data domain to gain an understanding of the problems faced by the rail industry, enabling them to start developing their existing tools and technologies to meet the needs of this dynamic new application domain"--

ISBN: 9781522531777 (ebook)Subjects--Topical Terms:

775741
Railroads
--Management.

LC Class. No.: TF507 / .I537 2018e

Dewey Class. No.: 385.0285/57

Innovative applications of big data in the railway industry
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504 $a Includes bibliographical references and index.
505 0 $a Section 1. Concepts and approaches. Chapter 1. Big data in railway O&M: a dependability approach ; Chapter 2. Blockchains: a distributed data ledger for the rail industry ; Chapter 3. Visual and lidar data processing and fusion as an element of real time big data analysis for rail vehicle driver support systems ; Chapter 4. Wayside train monitoring systems: origin and application -- Section 2. Innovations and technologies. Chapter 5. Scalable software framework for real-time data processing in the railway environment ; Chapter 6. Predicting behavior of passengers using data collected through smart cards ; Chapter 7. Dynamic behavior analysis of railway passengers ; Chapter 8. Intelligent transport systems services in vanets and case study in urban environment -- Section 3. Big data and text mining. Chapter 9. Study and analysis of delay factors of Delhi metro using data sciences and social media: automatic delay prediction system for Delhi metro ; Chapter 10. Social media as a tool to understand behaviour on the railways ; Chapter 11. Big data and natural language processing for analysing railway safety: analysis of railway incident reports -- Section 4. Applications and use cases. Chapter 12. Evolution of Indian railways through IOT ; Chapter 13. Application of big data technologies for quantifying the key factors impacting passenger journey in a multi-modal transportation environment ; Chapter 14. Big data analytics for train delay prediction: a case study in the Italian railway network.
506 $a Restricted to subscribers or individual electronic text purchasers.
520 3 $a "This book explores how big data technologies can address the operational challenges in the railway industry. It assists academics working in the big data domain to gain an understanding of the problems faced by the rail industry, enabling them to start developing their existing tools and technologies to meet the needs of this dynamic new application domain"-- $c Provided by publisher.
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700 1 $a Kumar, A. V. Senthil, $d 1966- $3 582122
700 1 $a Easton, John M., $e editor. $3 808135
700 1 $a Roberts, Clive, $e editor. $3 808136
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