A big data system design to predict the vehicle slip

  • Joohyoung Jeon*
  • , Woosik Lee
  • , Hyo Joo Cho
  • , Hongchul Lee
  • *Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this paper, we propose a system storing sensor data generated from the vehicle using Big data system and analyzing real-time sensor output to predict the car slip. A large amount of data will be distributed and stored by MongoDB which is one of NoSQL Database, and analyzed to control the vehicle by Hadoop Map/Reduce. The proposed system can be applied to general vehicle and also to the field of driverless vehicle or driverless vehicle platooning.

Original languageEnglish
Title of host publicationICCAS 2015 - 2015 15th International Conference on Control, Automation and Systems, Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages592-596
Number of pages5
ISBN (Electronic)9788993215090
DOIs
Publication statusPublished - 2015 Dec 23
Event15th International Conference on Control, Automation and Systems, ICCAS 2015 - Busan, Korea, Republic of
Duration: 2015 Oct 132015 Oct 16

Publication series

NameICCAS 2015 - 2015 15th International Conference on Control, Automation and Systems, Proceedings

Other

Other15th International Conference on Control, Automation and Systems, ICCAS 2015
Country/TerritoryKorea, Republic of
CityBusan
Period15/10/1315/10/16

Bibliographical note

Publisher Copyright:
© 2015 Institute of Control, Robotics and Systems - ICROS.

Keywords

  • Big data
  • Car-Slip
  • Extended Kalman Filter
  • NoSQL

ASJC Scopus subject areas

  • Control and Systems Engineering

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