UID:
almahu_9947421596702882
Format:
20 PDFs (xviii, 395 pages)
ISBN:
9781522531777
Content:
"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"--
Note:
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.
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Also available in print.
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Mode of access: World Wide Web.
Additional Edition:
Print version: ISBN 1522531769
Additional Edition:
ISBN 9781522531760
Language:
English
Keywords:
Aufsatzsammlung
DOI:
10.4018/978-1-5225-3176-0
URL:
Chapter PDFs via platform:
URL:
Volltext
(URL des Erstveröffentlichers)
