Deploy models on MEMS machine-learning core for sensor node-to-cloud solutions

Geneva, Switzerland, November 5, 2024 -- ST AIoT Craft, a new web-based tool from STMicroelectronics, simplifies developing and provisioning node-to-cloud AIoT (Artificial Intelligence of Things) projects that use the machine-learning core (MLC) of ST’s smart MEMS sensors.

The MLC is unique to the ST MEMS portfolio and enables decision-tree learning models to run directly in the sensor. Capable of operating autonomously, without host-system involvement, the MLC ensures low latency with low power consumption and efficiently handles tasks that require AI skills such as classification and pattern detection.

ST AIoT Craft also integrates all the steps needed for developing and provisioning IoT projects that leverage the MLC for in-sensor AI and offers a secure and user-friendly approach. There is robust cyber protection for data in the cloud and the web-based tool is conveniently accessed online without downloading to desktop. This saves time for users as it requires no installation, and eases collaboration between different team members such as as AI specialists and embedded software engineers.

The tool provided for creating decision-tree models includes the AutoML function, which automatically selects optimal attributes, filters, and window size for sensor datasets. This framework also trains the decision tree to run on the MLC and generates the configuration file to deploy the trained model. For beginners it is a quick and easy introduction to ST smart sensors that simplifies developing AI applications. In addition, to provision the IoT project, the gateway can be programmed with the Data Sufficiency Module (DSM) tool that intelligently filters data points for transmitting to the cloud, to optimize communication and minimize power consumption, and facilitates future retraining.

Users can find examples that show how to work with decision trees to build IoT sensor-to-cloud solutions, including fan-coil monitoring, asset tracking, human activity recognition, and head gestures. The examples are ready to flash and run for evaluation in ST reference IoT boards such as SensorTile.box Pro, STWIN and STWIN.box. Users can customize these examples to accelerate their own projects, bringing their own data or enhancing available datasets.

ST AIoT Craft is included in the ST Edge AI Suite repository. This contains all software tools, examples, and models for developing machine-learning algorithms to deploy on ST edge-AI devices such as STM32 microcontrollers (MCUs), Stellar MCUs, and MEMS sensors that contain the MLC or the intelligent sensor processing unit (ISPU). 

AIoT Craft is available free of charge online now. Please visit https://staiotcraft.st.com/index.html to register.

STM32 is a registered and/or unregistered trademark of STMicroelectronics International NV or its affiliates in the EU and/or elsewhere. In particular, STM32 is registered in the US Patent and Trademark Office.

About STMicroelectronics 

At ST, we are over 50,000 creators and makers of semiconductor technologies mastering the semiconductor supply chain with state-of-the-art manufacturing facilities. An integrated device manufacturer, we work with more than 200,000 customers and thousands of partners to design and build products, solutions, and ecosystems that address their challenges and opportunities, and the need to support a more sustainable world. Our technologies enable smarter mobility, more efficient power and energy management, and the wide-scale deployment of cloud-connected autonomous things. We are committed to achieving our goal to become carbon neutral on scope 1 and 2 and partially scope 3 by 2027. Further information can be found at www.st.com.