The idea behind the upcoming BRAINCRAFT board (stand-alone, and Pi "hat") is that you'd be able to "craft brains" for Machine Learning on the EDGE, with Microcontrollers. On ASK AN ENGINEER, our founder & engineer chatted with Pete Warden, the technical lead of the mobile, embedded TensorFlow Group on Google’s Brain team about what would be ideal for a board like this. What did we come up with? Here is a start!
https://blog.adafruit.com/2019/07/28/designing-the-machine-learning-board-on-the-edge-braincraft-tensorflow-adafruit-machinelearning-tinyml/
Inputs: Loads of sensors! Can be connected via stemmaQT. Image sensors, like a camera, Panasonic Grid-EYE. Heat-Sensitive camera, person detector. Microphone, voice detection for powering off. Accelerometer, gestures, vibration sensing, predictive maintenance.
Outputs: Screen for debugging Speaker for audio feedback as to what is going on. Relay control to turn things on/off, etc. and/or actuator.
Connectivity: NB / Narrowband IoT. Wireless flexibility. Works with adafruit.io, of course!
Power: Battery powered / low-power. Solar add-ons, energy harvesting, OK with lots of power sources that are not reliable. On/off switch!
Adafruit 2019 2300
Are we missing anything? Post up in the comments on what you want in a low-cost machine learning board! brAIncraft!
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