A Guide to STMicroelectronics' Edge AI Suite Tools

STMicroelectronics has plenty of Edge AI Tools that are useful in a variety of applications.  They collectively form the ST Edge AI Suite - STMicroelectronics. All of these tools can be used free of charge with a myST user account. To create an account, click on the avatar in the top right corner of the STMicroelectronics Website. You are now ready to access the ST Edge AI Suite!

1. NanoEdge AI Studio

The first tool is NanoEdge AI Studio, it is a good place to get started with Machine Learning. 

It is also compatible with Arduino Devices.

For getting started, the following video is a good example - Anomaly Detection Demo Using Edge AI.  It uses the Accelerometer on the STEVAL-STWINKT1B board.  In a future blog post I will try this demo using some other ST Micro boards that have an accelerometer.  Additionally, the Nano Edge AI libraries can be used with any type of sensor.

To use the Datalogger Feature in NanoEdge AI Studio, a Nucleo-F411RE, ST-EVAL or similar type of board is necessary.  Here are all the Board options shown:

2. ST Edge AI Developer Cloud

ST Edge AI Developer Cloud is a tool that allows users to do on remotely stored devices. You can import your own ML model or choose from ST Edge AI Model Zoo for optimization and testing. 

The following video is a getting started guide for STM32Cube.AI Developer Cloud, the predecessor of ST Edge AI Developer Cloud. While there are some differences between the two, this getting started video does have some helpful steps.  I'm also working on a blog post about getting started with the updated ST Edge AI Developer Cloud.

3. MEMS-Studio

MEMS-Studio is a software solution for using AI in embedded systems development. It can be downloaded from the linked webpage (MEMS-Studio).  Once installed an opened, you will have access to Getting Started with MEMS-Studio - User manual and Introduction-to-MEMS-studio Video.

4. STEdgeAI-Core

STEdgeAI-Core is used for compiling edge AI models on various ST MCUs MPUs, and Smart Sensors - all in one tool.  The following video gives an overview.

5. ST Edge AI Model Zoo

The ST Edge Ai Model Zoo is a collection of AI models that can be used for running on the other tools in the ST Edge AI Suite. It is comprised of three GitHub repositories: AI Model Zoo for STM32 devices, GitHub - STMicroelectronics/STMems_Machine_Learning_Core, and GitHub - STMicroelectronics/st-mems-ispu: Examples, tutorials, and other development resources for the ISPU.

6. X-CUBE-AI - AI expansion pack for STM32CubeMX 

The AI expansion pack for STM32CubeMX  is a tool used for optimizing and profiling Neural Networks and Machine Learning models for STM32.  To install this tool, open the STM32CubeIDE, and go to Help > Manage Embedded Software Packages > STMicroelectronics, then scroll down to X-CUBE-AI and click on the newest available version (9.1.0 in this case), then click "Install."  You may need to log-in on the pop up that appears for the expansion to install successfully.  Here is a screenshot of the installation screen.

7. ST High Speed Datalog

    One of the newer tools in the suite, ST High Speed Datalog is a data acquisition and visualization toolkit. It is specifically designed for applications in embedded systems and data science. The following Datalog Quick Start Guide is designed to get started with the Datalog along with the STEVAL-STWINBX1 .

8. StellarStudioAI 

    The next tool, StellarStudioAI is an AI tool for StellarStudio - development environment for Stellar automotive MCUs.  StellarStudioAI generates neural networks and converts them into C libraries for use by MCUS.

9. X-Linux-AI

    X-Linux-AI is an expansion for the STM32 MPU OpenSTLinux Distribution.  X-LINUX-AI  provides LINUX AI frameworks and application examples for use with STM32 MPUs.

10. ST ToF Hand Posture

    The final tool, ST ToF Hand Posture, is used for detecting hand gestures on STM32 MCUs using a Time-of-Flight sensor. It requires a free login to MyST to access.

This completes the summary of the ST Edge AI Tools. The first four tools listed are the best place to get started when doing AI projects for ST MCUs and MPUs.  Helpful example videos are also available for NanoEdgeAI Studio, and MEMS Studio.  For example, NanoEdge AI Studio V3 - Anomaly Detection demo and Introduction To MEMS Studio.