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Automotive MCU Family Integrates Machine Learning

Oct. 10, 2024
Imagimob enhanced its automotive machine-learning portfolio by integrating ML capabilities into Infineon's ASIL D-compliant MCUs.

Along with electrification, the greatest current drivers of the automotive industry—autonomous and automated driving—are being impacted by the capabilities and functionalities promised by AI. Artificial intelligence will play a critical role in enabling vehicles to detect pedestrians, analyze driver behavior, recognize traffic signs, and control trajectories, as well as addressing myriad other needs.

Due to the environment the systems operate in, autonomous and automated driving-solutions depend heavily on AI systems with machine-learning (ML) capabilities, with processors that can handle the large amounts of data safely, securely, and in real-time. Addressing this challenge, Imagimob  integrated ML capabilities into Infineon's automotive ASIL D-compliant MCUs, such as the AURIX TC3x and AURIX TC4x devices.

“The integration of secured and dependable AI capabilities into microcontroller families is crucial for advancing autonomous-driving applications in the automotive industry,” said Thomas Boehm, Senior Vice President Microcontroller at Infineon. “We are proud that our AURIX microcontrollers are now supported by Imagimob Studio, making them accessible to developers worldwide. This highlights our role as a leading innovator in the industry.”

“With the integration of AURIX into our Imagimob Studio, we are bringing full machine-learning compatibility and capabilities to the automotive sector,” said Alexander Samuelsson, CTO of Imagimob. “This means that all the use cases we support with our platform are now also available for Infineon’s AURIX microcontrollers.”

Streamlined ML Model Creation with Imagimob Studio

Developers can create robust ML models for edge AI and deploy them with Infineon's AURIX MCUs. They can start by creating ML models in Imagimob Studio, which are able to deploy on the MCUs directly within the platform. It helps deploy the code seamlessly, streamlining machine-learning implementations on MCUs and the creation of sophisticated ML models.

Imagimob Studio offers a sample project for siren detection to demonstrate model creation and deployment, creating acoustic models with AURIX MCUs and a microphone shield. The company also developed new regression models for calculating remaining battery power, health status, and usage time in products.

Providing a seamless upgrade path from the AURIX TC3x family of ASIL D-compliant automotive MCUs, AURIX TC4x scalable MCUs are powered by the next-generation TriCore 1.8. They feature a scalable accelerator suite with a parallel-processing unit and multiple intelligent accelerators for cost-effective AI integration.

These advances provide enhanced ML capabilities that allow for the deployment of more complex or multiple models simultaneously. In the example in the siren detection project, the AURIX TC4x enables both siren detection and voice interaction simultaneously.

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About the Author

Alix Paultre | Editor-at-Large, Microwaves & RF

Alix is Editor-at-Large for Microwaves & RF

An Army veteran, Alix Paultre was a signals intelligence soldier on the East/West German border in the early ‘80s, and eventually wound up helping launch and run a publication on consumer electronics for the U.S. military stationed in Europe. Alix first began in this industry in 1998 at Electronic Products magazine, and since then has worked for a variety of publications, most recently as Editor-in-Chief of Power Systems Design.

Alix currently lives in Wiesbaden, Germany.

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