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    Suggestions for Edge AI Board for Vision-Based Automation (Light/Audio Control)

    TinyML
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    • R
      rahuljeyaraj last edited by

      Hi everyone,

      I’m planning a vision-based AI project where the AI model should run directly on the embedded board (not in the cloud). Based on the inference results, I want to trigger actions like controlling a light or playing a pre-recorded audio file through a speaker.

      Could you please suggest which board or boards would be suitable for this kind of edge AI application? Also, does MakerGram stock such boards?

      Thanks in advance for your help!

      salmanfaris 1 Reply Last reply Reply Quote 0
      • salmanfaris
        salmanfaris @rahuljeyaraj last edited by

        Hi @rahuljeyaraj ,

        Welcome to the MakerGram community forum, There are several capable development boards available right now for the application. I'm sharing the one we have at our MakerGram inventory,

        For small models, I recommend using - XIAO ESP32-S3 Sense along with Edge Impulse platform to create the model, Here the processing is managed by the esp32 Core itself. It maybe feel slower if the mode it bit heavy.

        next option for small models is Seeed Grove Vision v2 camera where all the processing will done in the inbuilt "Arm Cortex-M55 & Ethos-U55" and you can get the inference results via the I2C or UART from the board, later you can process with Arduino or any XIAO board itself.

        If the model is moderate in size, better to go with Raspberry Pi and v2 or v3 camera and use the Edge Impulse models.

        Currently, we have these board available.

        1 Reply Last reply Reply Quote 0
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        • Hi @rahuljeyaraj ,

          Welcome to the MakerGram community forum, There are several capable development boards available right now for the application. I'm sharing the one we have at our MakerGram inventory,

          For small models, I recommend using - XIAO ESP32-S3 Sense along with Edge Impulse platform to create the model, Here the processing is managed by the esp32 Core itself. It maybe feel slower if the mode it bit heavy.

          next option for small models is Seeed Grove Vision v2 camera where all the processing will done in the inbuilt "Arm Cortex-M55 & Ethos-U55" and you can get the inference results via the I2C or UART from the board, later you can process with Arduino or any XIAO board itself.

          If the model is moderate in size, better to go with Raspberry Pi and v2 or v3 camera and use the Edge Impulse models.

          Currently, we have these board available.

          • read more
        • R

          Hi everyone,

          I’m planning a vision-based AI project where the AI model should run directly on the embedded board (not in the cloud). Based on the inference results, I want to trigger actions like controlling a light or playing a pre-recorded audio file through a speaker.

          Could you please suggest which board or boards would be suitable for this kind of edge AI application? Also, does MakerGram stock such boards?

          Thanks in advance for your help!

          • read more
        • @salmanfaris Thank you Salman, This solution worked for me.

          • read more
        • @Abhay Can you try one more method

          Downloaded both boards, “Seeed nRF52 Boards” and “Seeed nRF52 mbed-enabled Boards.”

          Copy the adafruit-nrfutil from

          /Users/<user>/Library/Arduino15/packages/Seeeduino/hardware/mbed/2.9.2/tools/adafruit-nrfutil/macos/adafruit-nrfutil

          to

          /Users/<user>/Library/Arduino15/packages/Seeeduino/hardware/nrf52/1.1.8/tools/adafruit-nrfutil/macos/adafruit-nrfutil

          Then chmod -x the copied file

          Please check and let me know. Src

          • read more
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