期刊
FRONTIERS OF ENGINEERING MANAGEMENT
卷 4, 期 4, 页码 428-436出版社
HIGHER EDUCATION PRESS
DOI: 10.15302/J-FEM-2017048
关键词
railway; intelligent asset management; collaborative learning; big data; hybrid cloud; Bayesian
资金
- Lulea Railway Research Centre (Jarnvagstekniskt Centrum, Sweden)
- Swedish Transport Administration (Trafikverket)
- NSFC [71731008]
In the EU Horizon 2020 Shift2Rail Multi-Annual Action Plan, the challenge of railway maintenance is generating knowledge from data and/or information. Therefore, we promote a novel concept called IN2CLOUD, which comprises three sub-concepts, to address this challenge: 1) A hybrid cloud, 2) an intelligent cloud with hybrid cloud learning, and 3) collaborative management using asset-related data acquired from the intelligent hybrid cloud. The concept is developed under the assumption that organizations want/need to learn from each other (including domain knowledge and experience) but do not want to share their raw data or information. IN2CLOUD will help the movement of railway industry systems from local to global optimization in a collaborative way. The development of cutting-edge intelligent hybrid cloud-based solutions, including information technology (IT) solutions and related methodologies, will enhance business security, economic sustainability, and decision support in the field of intelligent asset management of railway assets.
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