elmug4future
KI für energieeffiziente Sensorsysteme – Effiziente Überwachung von Maschinen und Anlagen
Sebastian Uziel
Abstract:
The presentation shows how neural networks have to be adapted to run on microcontrollers. Moving such algorithms from the cloud to the sensor reduces the energy consumption for the transmission and calculation of the data in the cloud. The procedure is illustrated by an example from predictive maintenance:
At IMMS, algorithms for embedded systems were designed, optimised and implemented in a demonstrator for AI-based fan monitoring using the machine learning approach TinyML: Motor bearings or fan blades can be directly monitored with the compact retrofittable solution. Defective parts are indicated directly via a red LED.
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Dipl.-Hdl. Dipl.-Des. Beate Hövelmans
Head of Corporate Communications
beate.hoevelmans(at)imms.de+49 (0) 3677 874 93 13
Beate Hövelmans is responsible for the text and image editorial work on this website, for the social media presence of IMMS on LinkedIn and YouTube, the annual reports, for press and media relations with regional and specialist media and other communication formats. She provides texts, photographs and video material for your reporting on IMMS, arranges contacts for interviews and is the contact person for events.