Resources

Access our free resources to learn about machine learning.
Find links to useful content for each of our solutions: NanoEdge AI Studio, STM32Cube.AI and X-LINUX-AI.
Find all the function packs that integrate concrete examples to easily start a project.

Introduction to STM32 AI solutions


Overview of Artificial Intelligence solutions for STM32 (NanoEdge AI Studio, STM32Cube.AI)


Give your product an Edge using AI on STM32


Intelligence at the Edge [e-book]
A great source of technology, market, and product information for casual learner as well as data scientist

STMicroelectronics - Edge AI - eBook - mouser

Get started with NanoEdge AI Studio

Discover how to create your data collection and create your first machine learning algorithm in a few clicks

Presentations


[Marketing presentation] NanoEdgeAI solution overview


[Databrief] Automated Machine Learning (ML) tool for STM32 microcontrollers


[Flyer] NanoEdge AI Studio Machine-Learning Software Development for Connected devices and Industrial Equipment Advertisement


Online training


Anyone can build self-learning edge AI devices for STM32


How to easily integrate anomaly detection or predictive maintenance capabilities into your system with NanoEdge AI Studio


NanoEdge AI from datalogging to integration


Blog articles


STEVAL-STWINKT1B: New Components and Application Examples Help Developers Working on Condition Monitoring Applications with AI at the Edge


The Next Automation Age, How New Cyber-Physical Systems Are Making a Positive Difference


NanoEdge AI Studio: 2 New Algorithm Families in 1 Comprehensive AI Solution


License agreement


NanoEdge AI Studio software license agreement


AI on STM32: fan anomaly detection and classification on current sensing with NanoEdge AI Studio

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AI on STM32: edge AI motor anomaly detection with NanoEdge AI Studio

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NanoEdge AI Studio V3 – Anomaly Detection demo

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Fun with NanoEdge AI: this smart Bialetti Moka Express takes your coffee experience to new heights

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AI on STM32: tinyML predictive maintenance in an STM32 microcontroller with NanoEdge AI Studio

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NanoEdge AI Studio V3 Product Overview

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AI on STM32: Filter clogging detection on an X-NUCLEO-IHM07M1board with NanoEdge AI Studio

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AI on STM32: multiple fan condition monitoring with NanoEdge AI Studio and SensorTile

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ST @ EW: NanoEdge™ AI Studio in practice

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Discover IRMA from Oxytronic, made with NanoEdge AI Studio

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Get started with STM32Cube.AI

Discover how to optimize your AI Neural Network and create processing libraries for your STM32 project

STM32Cube.AI Developer Cloud

Discover how to take advantage of this online platform to optimize, benchmark and create AI processing libraries for your STM32 project.

Presentations


[Marketing presentation] Optimize Neural Networks on STM32 with STM32Cube.AI


[Databrief] Artificial intelligence (AI) software expansion for STM32Cube


Wiki


How to measure machine learning model power consumption with STM32Cube.AI generated application


Blog articles


STM32Cube.AI and NVIDIA TAO Toolkit, Download and watch a 10x jump in performance on an STM32H7 running vision AI


ST joins MLCommons, why 1 benchmark can help teams adopt machine learning at the edge


STM32Cube.AI v7.3 empowers users to find the perfect balance between inference times and RAM


STM32Cube.AI v7.2, Now With Support for Deeply Quantized Neural Network and Why It Matters


License agreement


STM32Cube.AI software license agreement – SLA0048


Getting Started with STM32Cube.AI

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ST partners up with Schneider Electric: people flow counting sensor leveraging STM32CubeAI

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How students at University College London developed an edge AI digital stethoscope PoC in 8 weeks

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Get started with X-LINUX-AI for OpenSTLinux

Learn how to easily integrate Kera and TensorFlow trained AI models into your OpenSTLinux environment

Presentations


[Databrief] X-LINUX-AI: AI Expansion Package for STM32 MPU OpenSTLinux


AI on STM32: Multiple Object Detection with X-LINUX-AI

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STM32 MP1 AI for people counting from EW2022

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Accelerate your development with STM32 function packs

To simplify application development, we offer code examples around important use cases, such as computer vision, sensing, and condition monitoring. Our function packs are a complete integration of an artificial neural network coupled with pre/post-processing functions and connected to microcontroller peripherals.
These software packages help you save precious time, allowing you to focus on your artificial neural network models and what makes your application unique.

FP-AI-MONITOR1


STM32Cube function pack for ultra-low power STM32 with artificial intelligence (AI) monitoring application based on a wide range of sensors

#STM32Cube.AI #NanoEdge AI Studio

FP-AI-SENSING1


STM32Cube function pack for ultra-low power IoT node with artificial intelligence (AI) application based on audio and motion sensing

#STM32Cube.AI

FP-AI-VISION1


STM32Cube function pack for ultra-low power IoT node with artificial intelligence (AI) application based on audio and motion sensing

#STM32Cube.AI

FP-AI-FACEREC


Artificial Intelligence (AI) face recognition function pack for STM32Cube

#STM32Cube.AI

FP-AI-CTXAWARE1


STM32Cube function pack for ultra-low power context awareness with distributed artificial intelligence (AI): acoustic analysis with NN on MCU and motion analysis with ML on IMU

#STM32Cube.AI

Wiki – Computer vision applications


Wiki – Sensing applications


AI on STM32: Computer Vision made simple with FP-AI-VISION1 and STM32Cube.AI

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AI on STM32: People Counting Demonstration – Advanced model detection in computer vision

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AI on STM32: Person Presence Detection with FP-AI-VISION1

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AI on STM32: Face recognition with FP-AI-FACEREC

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AI on STM32: Condition monitoring and motor control with FP-AI-NANOEDG1

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Getting started with the FP-AI-SENSING1 (STM32Cube function pack, AI/sensing)

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