Case Study: MOVALSYS
The customer wanted to automatically detect the footfall of people walking or running using the signal from an accelerometer.
The varied rhythm and stride among the users made it difficult to identify footfall patterns in the signal. The AI had to tackle situations that ranged from old people walking slowly to users in a race.
Advanced models of recurring neuronal networks were used that managed to obtain performance similar to a human being.
“Working with ENAIA was an amazing experience, they understood our problem perfectly and they solved it quickly with a quality level that was way above our expectations.”