IRNAS partners with Edge Impulse to create the next generation of applied IoT devices

Why on-device machine learning?

Take an oversimplified example of a temperature sensor, which measures the temperature every 1s and averages it to one value per hour. Effectively, only a single property has been extracted from the 3600 data points that are then thrown away. Given the power has already been used to acquire the measurements, it is worth exploring what more useful information can be extracted from this data and thus increasing the added value of the solution.

Izoelektro RAM-1 surge arrestor monitoring

ElephantEdge animal conservation and industrial IoT tracker

Keko-Varicon varistor semiconductor yield optimization

IRNAS machine learning vision

At IRNAS, we have been combining the experience with IoT devices and analytical methods in various solutions that have been used by a wide range of customers. The majority of these solutions have plenty of technical capacity left that could be occupied by machine learning. As shown, such upgrades offer great improvements in the value our solutions provide to the user.

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Institute IRNAS

Institute IRNAS

We are applying today’s knowledge to create systems for an open future.