Learn why room occupancy detection using environmental sensors and tabular data wins over computer vision.
What if we say that there’s a more budget-friendly way to detect occupancy than real-time video analysis?
Worrying about whether your parcels are transported safely? Check out the new project to learn how you can apply TinyML to easily track the status of your packages and monitor if they are moving, staying in the same place, impacted, thrown, picked up, placed in the wrong position, etc.
Do you often find your "smart" vacuum cleaner stuck or blocked by a carpet, a doorstep, or even your brand new shoes? It’s quite an annoying situation, isn’t it? Learn how to make your robot smarter in a few steps by running a TinyML model on an Arduino Pro board, Nicla Sense ME.
We are happy to introduce the new case of our ambassador, Sumit Kumar «Unlock Passwords with TinyML-based Digit Recognition».
Perform the MNIST digit recognition on passwords using the TinyML approach on a tiny MCU.
Sumit Kumar has prepared a new project where he shows how to quickly develop a TinyML model to recognize drawn digits on touch interfaces with low-power MCUs.
It’s a detailed set of guidelines on how to make your own dataset, train the model on a no-code platform, and run the model on the device!
Interested in how to quickly develop TinyML models to recognize custom, user-defined drawn gestures on touch interfaces, embedded in low-power MCUs?
Check out the new project «Handmade Drawing Recognition Interface from my Smartphone» from Sumit Kumar.