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kartikvd24 / Flight_contoller_stm32_mpu6050

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This project performs motion classification using accelerometer data (accX, accY, accZ) on an STM32 board. The AI model is built using NanoEdge AI Studio, and sensor data is collected via a USB serial emulator for training and testing. It demonstrates how embedded AI can detect different movements (like tilt, shake, or rest) directly on the device

i2c stm32 hal classification led stm32f401re mlp uart mpu6050 embedded-c stm32cubeide nanoedge
  • Updated Oct 30, 2025
  • C

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