What does the expression “near-sensor AI” mean?
It means using artificial intelligence methods directly on the sensor. Essentially, it is the exact opposite of just collecting data: we try to perform an objective evaluation of data quality and its information content as close to the sensor as possible and then process this result immediately.
And what does that achieve in practical terms?
It enables us to make adaptive adjustments to the sensor. Our primary goal is to generate sensor data of outstanding quality. The data collected in this way is of much higher quality than with conventional sensor systems with standard signal acquisition and processing, as non-linear effects in the signal data can be statistically acquired and correctly processed.
What will a system equipped with near-sensor AI look like? Does near-sensor AI fundamentally alter the design? How will future systems differ from current ones?
Purely on the surface, you’ll hardly notice a difference. The really striking changes will be under the “hood”: first of all, AI-supported systems will be much easier to operate. The system will relieve users of many work steps and help them with tasks such as choosing the right settings. It will also adapt autonomously to changed conditions with no need for user interaction. The main impact of this will be increased efficiency: in the future, I simply won’t have to concern myself with many work steps or changing conditions.