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 language | English |
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Title of host publication | Proceedings of the 4th International Conference on Transportation Information and Safety (ICTIS 2017) |
Editors | Weiming Ma |
Place of Publication | Piscataway, NJ, USA |
Publisher | IEEE |
Pages | 111-116 |
ISBN (Print) | 978-1-5386-0437-3 |
DOIs | |
Publication status | Published - 2017 |
Event | ICTIS 2017: 4th International Conference on Transportation Information and Safety - Banff, Canada Duration: 8 Aug 2017 → 10 Aug 2017 |
Conference
Conference | ICTIS 2017: 4th International Conference on Transportation Information and Safety |
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Country/Territory | Canada |
City | Banff |
Period | 8/08/17 → 10/08/17 |
Bibliographical note
Accepted Author ManuscriptKeywords
- Marine vehicles
- Big Data
- Energy efficiency
- Optimization
- Environmental factors
- Navigation
- Algorithm design and analysis