STMicroelectronics STM32Cube.AI neural-network developer toolbox

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Leveraging its STM32 family of microcontrollers, STMicroelectronics has extended the associated STM32CubeMX ecosystem for product developers, adding advanced artificial intelligence (AI) features.

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. Now ST’s neural-network developer toolbox is bringing AI to microcontroller-powered intelligent devices, and to deeply embedded devices across IoT, smart building, industrial and medical applications.

With STM32Cube.AI, developers can convert pre-trained neural networks into C-code that calls functions in optimised libraries that can run on STM32 MCUs. It 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.

The extension pack can be downloaded inside ST’s STM32CubeMX MCU configuration and software code-generation ecosystem. The tool supports Caffe, Keras (with TensorFlow backend), Lasagne, ConvnetJS frameworks and IDEs including those from Keil, IAR and System Workbench.

The comprehensive toolbox, consisting of the STM32Cube.AI mapping tool and application software examples running on small-form-factor, battery-powered SensorTile hardware, together with the additional support through the ST Partner Program and dedicated STM32 online community, offers a fast and easy path to neural-network implementation on STM32 devices.

For more information: www.st.com/STM32CubeAI.