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sensor-design

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SarwanShah / Wind-Speed-Estimation-Using-Machine-Learning-And-Microphones-2023

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Engineered a 5,000 sample wind noise dataset and employed a CNN to estimate wind speed from their spectrograms. Gathered data using MEMS microphones and a cup anemometer as ground truth using ESP32. Recorded a mean-absolute error (MAE) of 1.12 m/s for wind speed

deep-learning embedded-systems meteorology convolutional-neural-networks embedded-machine-learning sensor-design
  • Updated Mar 4, 2025
  • Jupyter Notebook

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