The video explores how STMicroelectronics brings edge AI into a smart rear-view mirror demo built on the new STM32N6 microcontroller, using on-chip neural processing to run YOLOv8n object detection and semantic segmentation directly on the MCU while streaming compressed video to a phone. It shows how cars, trucks, buses, cyclists and pedestrians are classified in real time at around 24 frames per second, all from a microcontroller footprint instead of an application processor. https://www.st.com/en/microcontrollers-microprocessors/stm32n6-series.html
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At the heart of the board is an Arm Cortex-M55 core paired with ST’s Neural-ART accelerator NPU delivering up to 600 GOPS and roughly 3 TOPS per watt, backed by 4.2 MB of embedded RAM for buffering feature maps and camera data efficiently. An integrated image signal processor prepares the sensor stream for the AI accelerator while a hardware H.264 encoder and connectivity blocks handle video compression and Wi-Fi streaming, so the same chip can both understand the scene and deliver it to an external display without extra external hardware.
The smart rear-view mirror concept illustrates how this computing budget can be used for pixel-level semantic segmentation of the full frame instead of simple bounding boxes, enabling more robust perception for driver assistance, fleet monitoring or lightweight ADAS. Running YOLOv8n-class models at around 24 FPS within a power envelope of only a few hundred milliwatts makes it viable for always-on automotive and two-wheeler systems where thermal headroom is tight and cost per node must remain low.
Beyond automotive, the interview touches on other STM32N6-based demos including speech enhancement, where the same NPU pipeline is used to clean up noisy audio on-device, and precision seed dispensing, where AI helps regulate real-time seed flow to avoid clogging in agricultural machinery. Together they show how computer vision, audio processing and control loops can coexist on one MCU platform for industry, smart agriculture and embedded sensing.
To help developers get from idea to deployment, ST points viewers to its ST Edge AI and STM32 AI ecosystem, including the ST Edge AI Developer Cloud, STM32Cube.AI code generation, model zoo examples such as semantic segmentation, and production-ready discovery kits and dev boards now in volume. Filmed at Embedded World North America 2025 in Anaheim, this conversation gives a concise snapshot of how STMicroelectronics positions the STM32N6 as a high-performance edge AI microcontroller for real-world embedded engineering.
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