New H2020 Project ICONET Launched September 2018

New ICT infrastructure and reference architecture to support Operations in future PI Logistics NETworks (ICONET) project started officially on the 1st of September 2018.

ICONET is a 30 month project and will significantly extend the state of the art research and development around the Physical Internet (PI) concept in pursuit of a new networked architecture for interconnected logistics hubs by focusing on the following:

  • Research, under the PI umbrella, into new business models that underpin intermodal transport, warehousing and ecommerce fulfilment
  • Development of an experimental ICT proof of concept (PoC) Infrastructure Platform to support the simulation and testing of the PI concepts
  • Development of representative PI solutions for each of the three Focus Areas for the corresponding Living Labs.

The project will liaise closely with the ALICE developments and projects to link up and join forces with all projects in this area contributing to the formation of the European PI.

Demonstrators

Three Living Labs (Warehousing as a service, E-commerce fulfillment as a service and Synchromodality as a service) will demonstrate realistic and compelling solutions through industry reference implementations at representative scale with the goal to deliver a key stepping stone to the EU’s Green agenda.

Partners

Inlecom is the project coordinator and the partners are:

  • CLMS
  • CONSORZIO NAZIONALE INTERUNIVERSITARIO PER LE TELECOMUNICAZIONI
  • EBOS TECHNOLOGIES LIMITED
  • ELUPEG BV
  • EUROPEAN COUNCIL OF TRANSPORT USERS (EUROPEAN SHIPPERS COUNCIL)
  • IBM IRELAND LIMITED
  • ELECTRONIC GERMAN LINK GMBH
  • UNION INTERNATIONALE DES SOCIETES DE TRANSPORT COMBINE RAIL-ROUTE SCRL
  • NEW GENERATION SENSORS SRL
  • PROCTER & GAMBLE SERVICES COMPANY NV
  • SONAE CENTER SERVICOS II S.A.
  • STOCKBOOKING
  • INSTITUTO TECNOLOGICO DE ARAGON
  • HAVENBEDRIJF ANTWERPEN
  • VLTN GCV

 

 

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© 2018 ICONET

EU-flag-(high-resolution)

This project is funded from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 769119

The views expressed by the ICONET Consortium do not necessarily represent the views of the EU Commission/INEA.
The Consortium and the EU Commission/INEA are not responsible for any use that may be made of the information it contains
EU-flag-(high-resolution)

This project is funded from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 769119

The views expressed by the ICONET Consortium do not necessarily represent the views of the EU Commission/INEA.
The Consortium and the EU Commission/INEA are not responsible for any use that may be made of the information it contains