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Tool adds machine learning classification to small MCUs

Technology News |
By Ally Winning

French embedded AI startup Cartesiam has developed a tool to add machine learning classification to small microcontrollers which is being used in a sensor board by Bosch.

“Edge AI is huge, it’s like a tsunami,” said Joël Rubino, CEO and co-founder at Cartesiam talking to eeNews Europe. “We started in 2016 with this idea that there are billions of machines that are generating data and we need to listen to that data with a different approach, not to stream it to the cloud but to focus on the edge.”

The first version of the NanoEdge AI Studio tool, launched in February 2020, allows anomaly detection on ARM Cortex-M 32bit microcontrollers such as those from STMicroelectronics, Microchip and Renesas. The tool provides algorithm selection, optimisation and quantisation to create the library in around 4Kbytes that flags an anomaly in a signal. This is aimed at preventative maintenance.

“The technology giants in the cloud busines are all interested in the edge, not to run at the edge but to capture data from the edge,” said Rubino. “We started with the idea that our playground is the microcontroller, so we hired PhDs in machine learning and signal processing to rewrite the ML and signal processing algorithms to run in a microcontroller. It was a lot of hard work to test that in real environments, but V1 was mathematically correct and industrially proven,” he said.

Version two now allows a classification library to be built to identify the source of the anomaly from training data. This is built on a PC without using the cloud, and incorporated as a library in firmware in an edge AI design. This allows the classification library only to be called when an anomaly is detected for lower power operation. It can also be updated separately from the anomaly engine.

The company is to add the AI tool to an eight IoT sensor board from Bosch.

“For Bosch Connected Devices and Solutions, Cartesiam’s NanoEdge AI Studio is a natural fit as it perfectly extends our major existing IoT product line — the Cross Domain Development Kit, the XDK,” said Dr Ando Feyh, head of technical responsibility at Bosch Connected Devices and Solutions. “With its range of eight sensors, the XDK platform lets designers monitor, control and analyze processes remotely via Bluetooth or Wi-Fi, enabling our customers to quickly create more intelligent connected machines. NanoEdge AI Studio V2 increases the XDK’s unique functionality, providing the ability to process data for anomaly detection and classification for one or more sensors. Given this, we plan to use Cartesiam’s platform in a wide range of internal and external projects, and are closely working together with Cartesiam on a NanoEdge AI Studio integration with our XDK.”

“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,” said Rubino. “The new version of our IDE allows them to 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.”

Cartesiam has also launched a web-based platform with real edge AI datasets that can be used in the tool. These include air conditioning ventilator obstruction detection, breast cancer detection and vacuum-bag volume detection and Rubino says it will continuously enhance the portal with additional datasets.

www.cartesiam.ai

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