Hi GHI Team,
In the era of AIoT (AI and IoT), I think you need to consider to add machine learning feature on TinyCLR 2.0. With the power of SITCore, relatively huge flash size and enough ram we will be able to execute lite version of ML (machine learning) model.
AI on the edge is really useful when we need to off-load some AI processing from cloud to device to improve processing speed, safe bandwidth, reduce costs, and we can still operate without internet connection.
I got some references:
- STM32 X-Cube-AI https://www.st.com/en/embedded-software/x-cube-ai.html - we can convert model from keras, caffe, tensorflowlite, convnetjs and run it on mcu
- Execute simple neural network on arduino - https://www.anscenter.com/Blogs/Blog/GetPost/636879318392972431
- Tensorflow Lite - https://www.tensorflow.org/lite/microcontrollers
Some scenarios that we can achieve with this feature:
- Anomaly detection from time series data from sensors
- Preventive and Predictive maintenance
- Smart camera with object detection
- Smart Kiosk with product recommendation
- Hand written / gesture recognition on touch screen
What do you think ?