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5G-DATA is a project funded by Business Innovation Greece programme, which is financed by the EEA Grants and managed by Innovation Norway. Business Innovation Greece is a programme that aims to increase value creation and sustainable growth in the Greek business sector.

The overall goal of 5G-DATA project is to develop a solution that optimizes the management of streaming sequences of values over time – commonly referred to as time -series data – and eases the task of fetching, maintaining and utilizing network information in the control plane of the Software Defined Networking (SDN) architecture.

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5G Traffic is a project related mainly to 5G and machine learning technologies. The project is scheduled for a 36 months time period, aiming to develop a framework that optimizes the performance of 5G networks, with software that runs on the control plane and automates the management of forwarding rules at the data plane. The basic innovation of 5G-Traffic project is the use of machine learning to classify traffic and predict its volume within 5G Networks, so that the most appropriate forwarding rules are immediately applied for packets in the network flow.

Find out more at 5G-Traffic





5G-SOLUTIONS is a HORIZON 2020 three-year-duration project, held and run by 26 partners, supporting the EC’s 5G policy by implementing the last phase of the 5G cPPP roadmap. It aims to prove and validate that 5G provides prominent industry verticals with ubiquitous access to a wide range of forward-looking services with orders of magnitude of improvement over 4G, thus bringing the 5G vision closer to realisation. This will be achieved through conducting advanced field-trials of innovative use cases, directly involving endusers across five significant industry vertical domains: Factories of the Future, Smart Energy, Smart Cities, Smart Ports,Media & Entertainment.



A Νovel Customer Experience Analytics Tool, “CxPRESS”

The CxPress Tool is a co-operation project of three research participants: AppArt S.A. and Exodus S.A., ICT sector experts, and the National Technical University of Athens (NTUA) and aiming to develop a tool analyzing customers’ experience data, based on an innovative method, tested and certified on real datasets. CxPress will support: (a) CxP Strategy design with targets on areas of improvement and differentiation vs. competition, (b) action plan prioritization and verification against strategy targets and (c) fast detection of customer dissatisfaction issues in CxP operation.

Coordinator: National Technical University of Athens (NTUA)
Scientific person in charge of the project: Nikolaos Doulamis, NTUA
EPAnEK 2014-2020 Operational Programme, Competitiveness, Entrepreneurship, Innovation


mHealth System for Self-Management of Type 1 Diabetes Based on Adaptive Machine Learning of Glucose Metabolism

GlucoseML is a joint project held by four parties: AppArt S.A., Feac Engineering Private Company, and the University of Ioannina (UOI). GlucoseML’s main objective is the provision of a Type-1 Diabetes real-time self-care method, based on the predictive modeling of glucose metabolism. Using a multi-factorial group of data and machine learning algorithms, the project aims to assist with the everyday management of diabetes, by providing guidelines structured upon the personal data collected and analyzed, also enforcing patients’ independence as to how pursuing a treatment.

Coordinator: University of Ioannina (UOI)
Scientific person in charge of the project: Prof. Dimitris Fotiadis, UOI
EPAnEK 2014-2020 Operational Programme, Competitiveness, Entrepreneurship, Innovation


A HORIZON 2020 European three-year program aiming to achieve management of patients suffering from Heart Failure (HF), towards developing a multi-stakeholder patient centered mHealth ecosystem. HEARTEN's goal was to design, develop and validate an ICT co-operative environment that would enable the HF patients to achieve sustainable behavior change regarding their drug adherence and compliance, using biosensors that would be integrated into smart devices, feeding a database leveraged by all parties interested in a HF patient's treatment.

Coordinator: UNIVERSITE LYON 1 CLAUDE BERNARD (UCBL), President, François-Noël GILLY

TelcoSNA image

TelcoSNA is a project related to telecommunications social network analysis and machine learning technology and is scheduled for a period of 36 months. The goal of TelcoSNA is to strengthen the predictive capacity of the mechanisms currently used by Telecommunication Operators to identify in time its customers who are likely to leave their service.

Find out more TelcoSNA

EPAnEK 2014-2020 Operational Programme, Competitiveness, Entrepreneurship, Innovation

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