AI uses trained artificial neural networks to classify data signals from motion and vibration sensors, environmental sensors, microphones and image sensors, more quickly and efficiently than conventional handcrafted signal processing.
“This new neural-network developer toolbox is bringing AI to microcontroller-powered intelligent devices at the edge, on the nodes, and to deeply embedded devices across IoT, smart building, industrial, and medical applications,” said Claude Dardanne, President, Microcontrollers and Digital ICs Group, STMicroelectronics.
With STM32Cube.AI, developers can now convert pre-trained neural networks into C-code that calls functions in optimised libraries that can run on STM32 MCUs.
STM32Cube.AI comes together with ready-to-use software function packs that include example code for human activity recognition and audio scene classification. These code examples are immediately usable with the ST SensorTile reference board and the ST BLE Sensor mobile app.
Additional support such as engineering services is available for developers through qualified partners inside the ST Partner Program and the dedicated AI & Machine Learning (ML) STM32 online community.
ST will be looking to demonstrate applications developed using STM32Cube.AI running on STM32 microcontrollers in a private suite at CES, the Consumer Electronics Show, in Las Vegas, January 8-12, 2019.
