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Machine learning applied directly to sensor data for embedded systems

By PulseAugur Editorial · [1 sources] ·

This episode of Embedded.fm, titled "I've Seen A Giraffe," features David discussing the limitations of raw sensor data, such as Inertial Measurement Units (IMUs). He explains that this raw data is insufficient on its own and highlights the growing trend of applying machine learning directly to sensor inputs for improved embedded systems design. AI

IMPACT Discusses the application of machine learning to sensor data, potentially improving the efficiency and capabilities of embedded systems.

RANK_REASON Podcast episode discussing a technical topic.

Read on Mastodon — mastodon.social →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Machine learning applied directly to sensor data for embedded systems

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COVERAGE [1]

  1. Mastodon — mastodon.social TIER_1 English(EN) · [email protected] ·

    In episode 536: I've Seen A Giraffe, David breaks down why raw sensor data (like IMU readings) isn't enough on its own and how running machine learning directly

    In episode 536: I've Seen A Giraffe, David breaks down why raw sensor data (like IMU readings) isn't enough on its own and how running machine learning directly on sensors is changing embedded systems design. Listen here: https:// embedded.fm/episodes/536 And read the transcript …

    LINKS embedded.fm/…/536

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