Cartesiam has announced the NanoEdge™ AI Studio V2, the first integrated development environment (IDE) that simplifies creation of machine learning, inference, and now classification libraries for direct implementation on Arm Cortex-M microcontrollers (MCUs).
Thousands of commercially available industrial IoT (IIoT) embedded devices are already in production with NanoEdge AI Studio V1 for anomaly detection. With the addition of classification libraries to NanoEdge AI Studio V2, developers can now more easily go beyond anomaly detection to qualify problems directly in endpoints.
“Cartesiam makes tools for embedded developers, offering an intuitive push-button approach that requires no background in data science, opening AI to the billions of resource-constrained embedded devices built with Arm Cortex-M MCUs,” said Joël Rubino, CEO and co-founder, Cartesiam. “We initially designed NanoEdge AI Studio to meet demand from our customers in predictive maintenance, who, having accumulated data on the use of their equipment, asked us to help them easily qualify their events as well as to anticipate them. The new version of our IDE allows those customers — and any other embedded designer — to effortlessly develop a classification library without the usual challenges associated with signal processing and machine learning skills. This dramatically reduces costs and speeds time to market.”
NanoEdge AI Studio V2 offers a superior approach to anomaly detection and classification because the model is trained in the microcontroller and anomaly detection wakes up the classifier for characterization, telling the system exactly what’s wrong, not just that there’s a generic problem. This gives users the intelligence needed to make more informed decisions.