PI Reference Architecture

The key objective of this deliverable has been to produce the final blueprint of the architecture required to support PI network operations, as derived from the activities and lessons learned during the previous months of the ICONET project.

The architecture presents the final definitions of the associated connectivity models, architectural modules and data structures. The final reference architecture is sufficiently generic and high-level to be widely applicable and makes use of ontologies for the definition of the relevant data structures. This report also analyses interfacing/integrating with existing logistics platforms and solutions, security and data protection, regulatory compliance and network service level monitoring aspects to ensure a viable and usable model architecture.

In this second and final version of the deliverable, the main focus was on transforming key requirements, events and data required based on a generic scenario, as well as use cases driven by the project Living Labs in a reference architecture that addresses all required capabilities. Data specifications stem from the findings of WP1 deliverables and research conducted in the development of the multiple components of the ICONET project and their interactions. The report also documents service requirements, definition of required inputs and expected outputs as well as dependencies between services, while also providing a more technical oriented approach to the potential architecture of a PI system.

Furthermore, other key findings include the major events, data and decisions that need to be considered throughout the journey of a PI-container in a PI-network, as well as a blueprint for designing and implementing a PI enabled architecture in a decentralized manner, validated by the service development along with the simulated living lab scenarios.

Click here to read the full report

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© 2018 ICONET

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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