Study on route division for ship energy efficiency optimization based on big environment data

Kai Wang, Xinping Yan, Yupeng Yuan, Xiaoli Jiang, Gabri Lodewijks, Rudy Negenborn

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

9 Citations (Scopus)
274 Downloads (Pure)

Abstract

In the case of the global energy crisis and the higher sound of energy saving and emission reduction, how to take effective management measures of ship energy efficiency to achieve the goal of energy saving and emission reduction, put forward a new challenge for the development of shipping technology. The application of big data technology provides a new idea for the research of ship energy efficiency optimization management. The energy efficiency management level of the operating ship can be improved by the analysis and mining of the big data. In this paper, a big data analysis platform for ship energy efficiency management based on the widely used Hadoop platform architecture is designed. Afterward, due to the huge amount of involved data on the energy efficiency management which has exceeded the processing ability of traditional solutions, the big data analysis method is used to achieve the route division according to environmental factors, thus to lay the foundation for speed optimization in different segments of a route. Finally, a simple decision-making method of optimal engine speed based on the result of route division is proposed, which could improve ship energy efficiency and hence reduce CO2 emission.
Original languageEnglish
Title of host publicationProceedings of the 4th International Conference on Transportation Information and Safety (ICTIS 2017)
EditorsWeiming Ma
Place of PublicationPiscataway, NJ, USA
PublisherIEEE
Pages111-116
ISBN (Print)978-1-5386-0437-3
DOIs
Publication statusPublished - 2017
EventICTIS 2017: 4th International Conference on Transportation Information and Safety - Banff, Canada
Duration: 8 Aug 201710 Aug 2017

Conference

ConferenceICTIS 2017: 4th International Conference on Transportation Information and Safety
CountryCanada
CityBanff
Period8/08/1710/08/17

Bibliographical note

Accepted Author Manuscript

Keywords

  • Marine vehicles
  • Big Data
  • Energy efficiency
  • Optimization
  • Environmental factors
  • Navigation
  • Algorithm design and analysis

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