test Edge AI - Artificial Intelligence at the Edge

 

Edge AI

Case study 1: AI solution for people counting sensor

Discover an AI-based people-flow counting sensor running on STM32H7 and developed by Schneider Electric in cooperation with ST.

Case study 2: Low-power predictive maintenance

Discover how Lacroix optimized the maintenance frequency of reflow ovens thanks to STM32 Machine Learning capabilities.

Case study 1: AI solution for people counting sensor

Extract of the video Making buildings smarter is one of the big challenges of today's companies to improve their efficiency. The people flow counting sensor developed by Schneider Electric in partnership with STMicroelectronics enables the counting of the number of people. It also detects whether they are crossing a virtual line in both directions, using a large field of view and a small resolution thermal sensor.

This prototype can count in real-time and with a high level of accuracy the restaurant's attendance, while running on the standard STM32 microcontroller. This is achieved thanks to the artificial intelligence algorithm embedded on the STM32 microcontroller and the use of a thermal infrared technology.

 

ST partners up with Schneider Electric: people flow counting sensor leveraging STM32CubeAI (3:24)

Watch the full video (3:24)

Related resources:

Case study 2: Low-power predictive maintenance + AI at the Edge

Extract of the video Lacroix Group and its ecosystem are building the future of industrial electronics, in the design and production of industrial embedded systems and connected objects.​ At the heart of its smart industry strategy, Lacroix Electronics is now experimenting with predictive maintenance on its own assembly lines with the help of STMicroelectronics and its AI ecosystem.

The first trial of the condition monitoring technology is being done on the reflow oven of an automated line that solders component on PCB boards.

 

LACROIX Group Technology Predictive Maintenance in factory with ST Partner (5:11)

Watch the full video (5:11)

Related resources:

PDF: Predictive maintenance at LACROIX Electronics

Download the PDF slide deck: Predictive maintenance at LACROIX Electronics (Oven fan monitoring using Machine Learning on STM32L4)

Artificial Intelligence @ ST

Get Started with Edge AI

Download the AI extension for STM32CubeMX to map pre-trained Neural Networks

X-LINUX-AI STM32 MPU OpenSTLinux Expansion Package Download X-LINUX-AI, STM32 MPU OpenSTLinux Expansion Package that targets Artificial Intelligence for STM32MP1 Series microprocessors.

FP-AI-SENSING1 STM32Cube function pack Download FP-AI-SENSING1, STM32Cube function pack for ultra-low power IoT node with artificial intelligence (AI) application based on audio and motion sensing.

FP-AI-VISION1 STM32Cube function pack Download FP-AI-VISION1, STM32Cube function pack for high performance STM32 with artificial intelligence (AI) application for Computer Vision.

FP-AI-NANOEDG1 STM32Cube function pack Download FP-AI-NANOEDG1, Artificial Intelligence (AI) condition monitoring function pack for STM32Cube.

AI-related featured articles

Neural Networks on STM32: Thanks to a new set of Artificial Intelligence (AI) solutions, you now have the possibility to map and run pre-trained Artificial Neural Networks (ANN) on STM32 microcontrollers…

Artificial Intelligence: Learn more about AI and how ST has been actively involved in AI research for many years…

SensiML, the End-to-End AI Toolkit for SensorTile.box: Is there a way to streamline the creation and validation of machine-learning algorithms at the edge? It's a question that ST Authorized Partner SensiML answered in a popular presentation during the Virtual…

Support & Community

ST Community machine learning and AI Ask questions and get answers about STM32 Machine Learning & AI.

artificial intelligence webinar On-demand webinar: ST artificial intelligence solution for 32-bit MCUs: Thanks to concrete application examples, you will know more about running Artificial Neural Networks, how to use the STM32Cube.AI tool to convert Neural Networks into optimized code for STM32 MCUs.

artificial intelligence video training (MOOC) Introduction to STM32Cube.AI: Learn how to use STM32CubeMX and X-Cube-AI tools to work with Neural Networks on STM32.