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Driving Safety & Awareness Cooperative Business Model exploiting the 5GMETA platform

Authors: Canova, Clara; Pacella, Francesca; Brevi, Daniele; Apruzzese, Michela; Cavicchioli, Roberto;

Driving Safety & Awareness Cooperative Business Model exploiting the 5GMETA platform

Abstract

The introduction of the 5G in the automotive sector paves the way to new business opportunities and stakeholders collaboration, thanks to the availability of new connected vehicles technologies. To emphasise the opportunities of improved data sharing, different business modelling approaches exist, depending on the phase of the data value chain that technologies are able to cover. The 5GMETA open platform aims to leverage CCAM-based captured data to stimulate, facilitate and feed innovative products and services exploring the possibilities enabled by collaborative business models. This paper describes a new business model which focuses on a Use Case (UC) on "Driving Safety and Awareness" that exploit the 5GMETA platform, and highlight its business innovation. In this context, the value proposition relies in the ability to increase road safety thanks to a better driving-misbehaviour detection, thus providing benefits to a wide range of potential stakeholders. The UC has its foundation in the real-time data collected, in a scalable and reliable way, by the platform. The main innovation that the adoption of such business model will bring is the creation of new partnerships that may be enforced by a clear definition of the profit-sharing strategy between the actors involved.

Country
Italy
Keywords

Business Model; 5G; MEC; CCAM

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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