Journal of the Korean Society of Manufacturing Process Engineers (한국기계가공학회지)

The Korean Society of Manufacturing Process Engineers (한국기계가공학회)
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Detection of Abnormal Ship Operation using a Big Data Platform based on Hadoop and Spark

하둡 및 스파크 기반 빅데이터 플랫폼을 이용한 선박 운항 효율 이상 상태 분석

  • Lee, Taehyeon (Dept. of Precision Mechanical Engineering, Kyungpook Nat'l UNIV.) ;
  • Yu, Eun-seop (Dept. of Precision Mechanical Engineering, Kyungpook Nat'l UNIV.) ;
  • Park, Kaemyoung (e-Navigation TFT, Korean Register of Shipping) ;
  • Yu, Seongsang (e-Navigation TFT, Korean Register of Shipping) ;
  • Park, Jinpyo (Softhills) ;
  • Mun, Duhwan (Dept. of Precision Mechanical Engineering, Kyungpook Nat'l UNIV.)
  • 이태현 (경북대학교 정밀기계공학과) ;
  • 유은섭 (경북대학교 정밀기계공학과) ;
  • 박개명 (한국선급e-Navigation TFT) ;
  • 유성상 (한국선급e-Navigation TFT) ;
  • 박진표 ((주)소프트힐스) ;
  • 문두환 (경북대학교 정밀기계공학과)
  • Received : 2019.03.26
  • Accepted : 2019.05.13
  • Published : 2019.06.30
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Abstract

To reduce emissions of marine pollutants, regulations are being tightened around the world. In the shipbuilding and shipping industries, various countermeasures are being put forward. As there are limits to applying countermeasures to ships already in operation, however, it is necessary for these vessels to use energy efficiently. The sensors installed on ships typically gather a very large amount of data, and thus a big data platform is needed to manage and analyze the data. In this paper, we build a big data analysis platform based on Hadoop and Spark, and we present a method to detect abnormal ship operation using the platform. We also utilize real ship operation data to discuss the data analysis experiment.

Keywords

References

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