H2020 5G-INDUCE
Open cooperative 5G experimentation platforms for the industrial sector NetApps
Project Details
- Project no:
101016941
- Type of project: IA – Innovation action
- Call identifier: H2020-ICT-2020-2
- Topic: ICT-41-2020 – 5G PPP – 5G innovations for verticals with third party services
- Duration: 1 January 2021 to 31 December 2023 (36 months)
- CORDIS link:
https://cordis.europa.eu/project/id/101016941
- Official Website: https://www.5g-induce.eu/
Advanced network applications to shape the 5G vision
Europe has taken steps to lead global developments towards 5G (the fifth generation of telecommunication systems), which will be one of the most critical building blocks of our digital economy and society. 5G will provide virtually ubiquitous, ultra-high bandwidth and low latency ‘connectivity’ not only to individual users but also to connected objects. The success of 5G technologies hinges on their ability to attract vertical stakeholders. In this context, the EU-funded 5G-INDUCE project targets the development of an open, ETSI network functions virtualisation-compatible, 5G orchestration platform for the deployment of advanced 5G network applications. The project focus is directed towards the Industry 4.0 service deployment environment.
Show the Project Objective
Objective
The success of 5G technologies depends closely on their ability to attract vertical stakeholders, seeking the move of their services from cloud to the edge to meet unique KPIs. 5G-INDUCE project is based on the belief that such attractiveness requires vertical stakeholders and NetApp developers to be able to smoothly deploy and manage applications in distributed 5G network environments, in a secure fashion and with strict KPI requirements.
5G-INDUCE relies on the deployment of an open ETSI NFV compatible 5G orchestration platform for the deployment of advanced 5G NetApps. The platform’s unique features provide the capability to the NetApp developers to define and modify the application requirements while the underlay intelligent OSS can expose the network capabilities to the end users on the application level without revealing any infrastructure related information. This process enables an application-oriented network management and optimization approach that is in line with the operator’s role as manager of its own facilities, while it offers the operational environment to any developers and service providers through which tailored made applications can be designed and deployed, for the benefit of vertical industries and without any indirect dependency through a cloud provider.
The project focuses on the Industry 4.0 vertical sector, as one of the fastest growing and most impactful sectors in European economy with high potentials for service development SMEs and with the capability to tackle all diverse cases of service requirements. The platform is integrated over 3 5G Experimentation Facilities in Spain, Greece, and Italy, and extended with links towards specific Industries, for the showcasing of NetApps in real 5G environment. The consortium includes all the required stakeholders (MNOs, Industries, System integrators and SMEs) from the benefited business sectors evaluated in the project, while significant part of the work (>50%) is conducted by innovative SMEs.
Our Role in the Project
K3Y is directly focused on the development of the 5G Orchestrator, building on knowledge and technical developments acquired from previous projects, in order to accommodate novel industry 4.0 requirements and use cases in various domains. K3Y is also involved with the development of containerized, easily deployable, scalable and industry-specific applications (NetApps) responsible, with a focus on predictive maintenance in critical infrastructure namely in electrical power generators. Machine learning and various predictive algorithms, combined with advanced smart statistical sampling support the company in developing accurate prediction models for the targeted industry, ensuring smooth operation and minimal disturbances. The developed models and algorithms are capable of considering a spectrum of variables, extracting features and outputting a high-confidence prediction model.