NanoEdge AI Studio ML Design Software Supports Learning and Inferencing in AI-native MEMS Sensors

STMicroelectronics has expanded its NanoEdge AI Studio machine-learning design software which provides a complete end-to-end automated workflow that significantly eases the development of high-performing AI algorithms such as anomaly detection, classification, and regression. Designers can use NanoEdge AI Studio to distribute inference workloads across multiple devices including microcontrollers (MCUs) and sensors with ISPUs in their systems, significantly reducing application power consumption.

Increasing convenience and efficiency, on-device learning also permits development without requiring an exhaustive dataset to manage pre-deployment training. The libraries generated by NanoEdge AI Studio can run on any STM32 MCU, from entry-level devices containing the Arm Cortex-M0 core to the high-performance MCUs containing the Cortex-M7 core. 

Features

• Desktop tool for design and generation of STM32-optimized libraries: anomaly and outlier detection, feature classification, and extrapolation of temporal and multivariable signals

• Supports any type of sensor: vibration, magnetometer, current, voltage, multi-axis accelerometer, temperature, acoustic and more

• Explore millions of possible algorithms to find the optimal library in terms of accuracy, confidence, inference time, and memory footprint

• Generate very small footprint libraries running down to the smallest Arm® Cortex®-M0 microcontrollers

• Embedded emulator to test library performance live with an attached STM32 board or from test data files

• Native support for STM32 development boards, no configuration required

• Easy portability across the various STM32 microcontroller series