Neural Networks

3D face recognition, voice control and image recognition of faulty or fake parts were all the rage at Embedded World 2019. The trend towards performing these applications offline – without access to powerful compute servers in the cloud – was obvious. However, these applications require powerful CPUs with equally powerful GPUs to run predictions on deep neural networks.

I was interested in solutions that run (deep) neural networks (NNs) on microcontrollers (MCUs). And, Embedded World didn’t disappoint! Renesas showed how to predict motor failure by monitoring current and vibration. STMicroelectronics had a demo counting the cars driving by using the characteristic sound of the Doppler effect. That’s what I would call the “edge”!