Project description
The solution to edge intelligence and beyond
The increasing complexity of the Industrial IoT 2.0 demands smarter, more efficient solutions. Current AI systems either rely on resource-heavy cloud processing or limited onboard inference, hindering the transition from ‘connected’ to ‘smart.’ In this context, the EIC-funded Ekkono FLIIoT project is developing Edge Intelligence, an edge machine learning framework that performs learning on super-small, sensor-sized devices. Their unique product trains individual models on each unit, enabling per-device maintenance and optimisation. Furthermore, their federated learning solution, Synthesis, combines device models into supermodels, ushering in a new era of service-centric business models for product original equipment manufacturers in the European industrial manufacturing and automotive sectors. Ekkono FLIIoT is set to disrupt the market and pave the way for a smarter future.
Objective
Ekkono is developing a unique product: Edge Intelligence, an Edge Machine Learning framework that conducts learning on super-small, sensor-sized devices, enabling a transition from ‘connected’ to ‘smart’. It is based on over 7 years of university research, and is materially different from other AI solutions that either run in the cloud or can only perform inference onboard of connected things (IoT). Our product trains an individual model on each unit it runs on, learning how, where and for what the unit is used—enabling per-device maintenance, performance & optimization.
We are pioneering Edge AI in the emerging Industrial IoT 2.0 specializing in the European industrial manufacturing & automotive sectors.
Our ambition is to disrupt the market with our Federated Learning solution, called Synthesis, where individual device models are collected, compared, correlated & combined into supermodels, enabling next-gen sustainability leap & new service-centric business models for product OEMs.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
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Keywords
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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HORIZON.3.1 - The European Innovation Council (EIC)
MAIN PROGRAMME
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Topic(s)
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Funding Scheme
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
HORIZON-EIC-ACC-BF - HORIZON EIC Accelerator Blended Finance
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Call for proposal
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) HORIZON-EIC-2022-ACCELERATOR-01
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Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.
432 74 Traslovslage
Sweden
The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.