By Gina Roos, editor-in-chief
STMicroelectronics expands the STM32CubeMX ecosystem for the STM32 microcontrollers with the addition of advanced artificial intelligence (AI) features. With the new STM32Cube.AI extension pack, product developers can now convert pre-trained neural networks into C-code that calls functions in optimized libraries that can run on STM32 MCUs, said ST. The toolbox includes the STM32Cube.AI mapping tool along with software examples running on ST’s SensorTile reference board.
The new STM32 neural-network developer toolbox brings AI to microcontroller-powered edge, nodes, and embedded devices for a variety of applications including IoT, smart building, industrial, and medical. The STM32Cube.AI delivers a new FP-AI-SENSING1 software function pack that provides examples of code for human activity recognition and audio scene classification based on neural networks.
These code examples can be used with the ST SensorTile reference board to capture and label the sensor data before the training process, enabling the board to run inferences of the optimized neural network, and the ST BLE Sensor mobile app, which acts as the remote control and display.
The STM32Cube.AI extension pack (part number: X-Cube-AI) can be downloaded via ST’s STM32CubeMX MCU configuration and software code-generation ecosystem. The tool currently supports Caffe, Keras (with TensorFlow backend), Lasagne, ConvnetJS frameworks, and several IDEs, including from Keil, IAR, and System Workbench.
Engineering services are available for developers through qualified partners as part of the ST Partner Program and the dedicated AI & Machine Learning (ML) STM32 online community. ST will demonstrate applications developed using the STM32Cube.AI extension pack running on STM32 microcontrollers in a private suite at CES 2019.
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