Innovative applications of big data in the railway industry:
"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 techn...
Gespeichert in:
| Weitere Verfasser: | , , , |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Hershey, Pennsylvania (701 E. Chocolate Avenue, Hershey, Pennsylvania, 17033, USA) :
IGI Global,
[2018]
|
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Zusammenfassung: | "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"-- |
| Beschreibung: | 20 PDFs (xviii, 395 pages) Also available in print. |
| Format: | Mode of access: World Wide Web. |
| Bibliographie: | Includes bibliographical references and index. |
| ISBN: | 9781522531777 |
| Zugangseinschränkungen: | Restricted to subscribers or individual electronic text purchasers. |
Internformat
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| 245 | 0 | 0 | |a Innovative applications of big data in the railway industry |c Shruti Kohli, A.V. Senthil Kumar, John M. Easton and Clive Roberts, editors. |
| 264 | 1 | |a Hershey, Pennsylvania (701 E. Chocolate Avenue, Hershey, Pennsylvania, 17033, USA) : |b IGI Global, |c [2018] | |
| 300 | |a 20 PDFs (xviii, 395 pages) | ||
| 336 | |a text |2 rdacontent | ||
| 337 | |a electronic |2 isbdmedia | ||
| 338 | |a online resource |2 rdacarrier | ||
| 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. | |
| 530 | |a Also available in print. | ||
| 538 | |a Mode of access: World Wide Web. | ||
| 588 | |a Description based on title screen (IGI Global, viewed 11/07/2017). | ||
| 650 | 0 | |a Big data. | |
| 650 | 0 | |a Railroads |x Management. | |
| 650 | 0 | |a Railroads |x Technological innovations. | |
| 700 | 1 | |a Easton, John M., |e editor. | |
| 700 | 1 | |a Kohli, Shruti |d 1978- |e editor. | |
| 700 | 1 | |a Kumar, A. V. Senthil |d 1966- |e editor. | |
| 700 | 1 | |a Roberts, Clive, |e editor. | |
| 710 | 2 | |a IGI Global, |e publisher. | |
| 776 | 0 | |c (Original) |w (DLC)2017016448 | |
| 776 | 0 | 8 | |i Print version: |z 1522531769 |z 9781522531760 |w (DLC) 2017016448 |
| 856 | 4 | 0 | |l FWS01 |p ZDB-98-IGB |q FWS_PDA_IGB |u http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-5225-3176-0 |3 Volltext |
| 912 | |a ZDB-98-IGB | ||
| 049 | |a DE-863 | ||
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| author2 | Easton, John M. Kohli, Shruti 1978- Kumar, A. V. Senthil 1966- Roberts, Clive |
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| author_facet | Easton, John M. Kohli, Shruti 1978- Kumar, A. V. Senthil 1966- Roberts, Clive |
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| contents | 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. |
| ctrlnum | (CaBNVSL)slc19726194 (OCoLC)1010954240 |
| dewey-full | 385.0285/57 |
| dewey-hundreds | 300 - Social sciences |
| dewey-ones | 385 - Railroad transportation |
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| id | ZDB-98-IGB-00179837 |
| illustrated | Not Illustrated |
| indexdate | 2024-11-26T14:51:52Z |
| institution | BVB |
| isbn | 9781522531777 |
| language | English |
| oclc_num | 1010954240 |
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| physical | 20 PDFs (xviii, 395 pages) Also available in print. |
| psigel | ZDB-98-IGB |
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| spelling | Innovative applications of big data in the railway industry Shruti Kohli, A.V. Senthil Kumar, John M. Easton and Clive Roberts, editors. Hershey, Pennsylvania (701 E. Chocolate Avenue, Hershey, Pennsylvania, 17033, USA) : IGI Global, [2018] 20 PDFs (xviii, 395 pages) text rdacontent electronic isbdmedia online resource rdacarrier 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"-- Provided by publisher. Also available in print. Mode of access: World Wide Web. Description based on title screen (IGI Global, viewed 11/07/2017). Big data. Railroads Management. Railroads Technological innovations. Easton, John M., editor. Kohli, Shruti 1978- editor. Kumar, A. V. Senthil 1966- editor. Roberts, Clive, editor. IGI Global, publisher. (Original) (DLC)2017016448 Print version: 1522531769 9781522531760 (DLC) 2017016448 FWS01 ZDB-98-IGB FWS_PDA_IGB http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-5225-3176-0 Volltext |
| spellingShingle | Innovative applications of big data in the railway industry 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. Big data. Railroads Management. Railroads Technological innovations. |
| title | Innovative applications of big data in the railway industry |
| title_auth | Innovative applications of big data in the railway industry |
| title_exact_search | Innovative applications of big data in the railway industry |
| title_full | Innovative applications of big data in the railway industry Shruti Kohli, A.V. Senthil Kumar, John M. Easton and Clive Roberts, editors. |
| title_fullStr | Innovative applications of big data in the railway industry Shruti Kohli, A.V. Senthil Kumar, John M. Easton and Clive Roberts, editors. |
| title_full_unstemmed | Innovative applications of big data in the railway industry Shruti Kohli, A.V. Senthil Kumar, John M. Easton and Clive Roberts, editors. |
| title_short | Innovative applications of big data in the railway industry |
| title_sort | innovative applications of big data in the railway industry |
| topic | Big data. Railroads Management. Railroads Technological innovations. |
| topic_facet | Big data. Railroads Management. Railroads Technological innovations. |
| url | http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-5225-3176-0 |
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