SOURCE-LINKED INTELLIGENCE

Magnetic neural Network for predictive maintenance

CORDIS · observation · Publication date unknown

bricate a prototype that extends this unique ability to other types of analog signals, and apply it for predictive maintenance in the manufacturing industry. The present solutions based on mainstream artificial intelligence (AI) struggle, because the problems at hand are too fragmented: the training data is too scarce and the model engineering relies on very specific expert knowledge. Our Solution, frugal in terms of data and resources, based on a “task-agnostic” generic device, is able to identify unusual patterns in the analog signals. Our bio-mimicking approach should imitate the ability of human technicians, which assess the state of their machines by the sound. On the long term, our technology could be adapted for a variety of AI applications requiring low energy consumption or full privacy. The EIC Transition call corresponds exactly to our present needs: accelerate the development and the market readiness of our technology. Moreover, we address explicitly the requirements for Green Digital Devices. By working “on the edge”, our device reduces the energy and resources requi

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recordType

award

status

SIGNED

region

EU

value

2499999

unit

EUR