Project description
Integrating AI and edge computing to automatically detect machine failures
Machines have moving parts that produce sound and vibration. These outputs change when the machine is not working properly. The Czech SME NEURONSW has developed advanced monitoring and control ‘brainware’ for mechanical machines that integrates artificial intelligence and machine learning to analyse sound and other parameters, such as a diagnostic auditory cortex. The hardware is integrated with embedded edge computing and connected to a cloud-based platform for automatic detection of machine failures with nearly 100 % accuracy. The EIC-funded Neuron Soundware (NSW) project will support the team in optimising the platform and bringing it to market to support an AI-powered revolution in Industry 4.0 automated anomaly detection.
Objective
NSW is an AI-based acoustic and vibration diagnostic technology for early detection of broken machines and process monitoring, providing unparalleled insight into the operation of mechanical systems. Combined with its large-scale applicability and ease of use, it disrupts the way machines are diagnosed, facilitating industrial sustainability and catering to the needs of Industry 4.0. Our technology acts as an auditory cortex, understanding audio signals and detecting salient problems, delivering highly reliable results with 99.6% accuracy. NSW's integrated hardware with embedded edge software and cloud-based software platform automatically detects machine faults before other methods, preventing costly downtime and unnecessary maintenance. Our detection process utilizes our proprietary audio dataset, which contains terabytes of data and is continuously expanded with each new anomaly, improving the accuracy of the algorithms, the faults addressed and the types of machines.
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.
- natural sciences computer and information sciences internet internet of things
- natural sciences computer and information sciences software
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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.
147 00 Praha 4
Czechia
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.