AI Factory for Railway (AIF/R)
AIF/R’s goal is to create value for its stakeholders via establishment of a reliable and resilient platform for data sharing and analytics. The platform consists of a set of services and governing structures, which enables railway stakeholders, nationally and internationally, to provide and consume data and services securely.
The ongoing digitalisation and implementation of AI-technologies in railway is highly dependent on availability and accessibility of data for a geographically distributed system. AIF/R is facilitating this by providing a platform for data sharing. AIF/R is a set of smart cloud/edge-based data services that are aimed to accelerate digitalisation in railway. AIF/R’s services provide capabilities such as acquisition, integration, transformation, and processing of railway related data across endpoints, e.g. authorities, industries, academia, and SME:s. AIF/R’s integrated services can be invoked on-premises or in multiple cloud-based environments.
AIF/R provides digital pipelines between data providers and data consumers. Each pipeline represents a set of orchestrated activities aimed to extract, transfer, load, and process datasets between the provider and the consumer. AIF/R’s pipelines are configurable entities, which can utilise a palette of technologies for e.g. communication, storage, and processing, to enable context-adaptability and fulfil the users’ requirements. Selection of appropriate technologies for each pipeline will be based on the context specific requirements such as requirements on scalability, authentication, and authorisation. It is believed that a generic data factory for railway should be hosted as a neutral open platform , which is governed by a body with focus on research and innovation.
AIFR/R achievements :
- AIF/R team: 16 (researchers, master, coordinators)
- Coordination platform (cloud/edge-based) established
- Development platform (cloud/edge-based) established
- 17 use cases identified
- Integration:
- Several external data sources integrated
- Several data lakes and analytics services connected
- Demonstrators: 8 demos in different UC:s
- 34 conducted seminars/workshops (dissemination)
- PhD:s recruited
- A Roadmap for the future
- Special issue in the Journal of Sustainability
- Book proposal: ‘AI Factory’
- OECD report on ‘Data-Driven Approach’ Transport
Researchers: Ramin Karim (PL), Miguel Castano, Veronica Jägare, Jaya Kumari, Adithya Thaduri, Cecilia Glover, Uday Kumar, Amit Patwardhan, Ravdeep Kour, Diego Galar, Kevin Karim, Emil Lindh.
Sponsor: Vinnova, JVTC, Trafikverket, Association of Swedish Train Operating Companies, Infranord, Norrtåg, Alstom, Bombardier, Damill, Omicold, Sweco, Transitio
Duration: 2019-2022
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