NanoEdge AI Studio transforms edge development
Cartesiam has announced the availability of NanoEdge AI Studio V2, an 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.”
Key Features of NanoEdge AI Studio V2
- Superior approach to anomaly detection and classification — because the model is trained in the microcontroller, anomaly detection wakes up the classifier for characterisation, telling the system exactly what’s wrong, not just that there’s a generic problem — giving users the intelligence needed to make more informed decisions.
- Data science expertise, signal processing and machine learning skills not needed — unlike competitive AI software solutions running in the cloud — which require the expertise of data scientists and signal processing engineers — the IDE is an intuitive desktop tool that lets embedded developers focus on solving business problems rather than on selecting algorithms.
- Optimised for Arm Cortex-M MCUs, the industry’s most widely used embedded microcontrollers.
- Low RAM footprint — consumes as little as 4Kb RAM in a typical configuration, making it well suited for resource-constrained devices.
- Rapid learning at the edge — performs iterative learning in 30msecs in an Arm Cortex-M4 80Mhz to deliver intelligence quickly.
A growing collaboration with Bosch Connected Devices and Solutions validated Cartesiam’s approach to edge AI embedded development.
“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-Ing. Ando Feyh, Head of Technical Responsibility, Bosch Connected Devices and Solutions.
“With its range of eight sensors, the XDK platform lets designers monitor, control and analyse 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.”
Cartesiam also announced Use Case Explorer at data.cartesiam.ai, a new web-based platform. Users can download real datasets and try the NanoEdge AI Studio IDE on representative use cases, such as ventilator obstruction detection, breast cancer detection, vacuum-bag volume detection, and others. Cartesiam will continuously enhance the portal with additional datasets.