Today’s vehicles process ~4000 CAN bus signals/sec, compared to very few signals in smartphones and the like. This large amount of continuously collected vehicle data represents a huge Big Data business potential, not only for the automotive industry, but especially for cross-sector industries with interdisciplinary applications. With today’s proprietary approaches focused on bringing services to vehicles and applied ignorance of customer privacy concerns, this large business potential is still closed because the automotive industry has not yet been able to establish an open service ecosystem equivalent to that of the smartphone industry.
The core intention of the AutoMat project is to create an open ecosystem for vehicle Big Data, which will materialize in the form of a cross-border marketplace for vehicle Big Data that leverages the currently untapped information from connected vehicles. The interface to the marketplace will be derived from a common vehicle information model that makes processed and anonymous vehicle data from various OEMs accessible to cross-industry service providers. Given the vast amount of volatile vehicle data, the AutoMat ecosystem builds heavily on current trends in Big Data. Example service scenarios driven by service providers seeking to generate tangible business from the AutoMat ecosystem are being developed in the context of meteorological data based on hyperlocal and extended innovative enterprise service areas.
By defining an open value chain, the proposed AutoMat ecosystem enables and stimulates parties from different sectors to focus on their core business and enhance collaboration with other partners. AutoMat can therefore serve as an incubator for new business opportunities and strengthen Europe’s position as a provider of innovative cross-sector and cross-border Big Data services. The latter aspect will be actively stimulated during the project through an open service competition based on the AutoMat Big Data ecosystem.
More information unter: https://cordis.europa.eu/project/id/644657
