Technology

How it works

A monitoring algorithm with no direct world analogues — from sensor signal to final diagnostic conclusion

The KOROVSKI algorithm works on the same principle as facial recognition — except instead of facial features it analyses each animal's biological signals and compares them against a reference database.

Four diagnostic steps

From the physical signal at the animal's skin — to a report on the veterinarian's screen

Data capture

A capacitive collar sensor records the cow's low-frequency wave signal from the skin surface daily, converts it, and sends a digital data container to the server over WLAN.

Analysis and comparison

The KOROVSKI algorithm extracts «nosological process fingerprints» from the digital container and compares them against a reference marker database, computing the similarity percentage for each indicator.

Results display

Results are shown in the interface in a «traffic light» format: bound to the sensor ID and a specific animal. Reports for any period are supported.

Timely prevention

By detecting cattle disease risks before clinical symptoms appear, the system lets the veterinarian act ahead of time. Intervention before illness onset avoids economic losses.

How data flows through the system

End-to-end analytics: from collar sensor to veterinarian decision

Data collection

The collar sensor reads a low-frequency electromagnetic signal in the acoustic frequency range from the animal's skin.

Transmission

The recorded signal is converted into a digital fingerprint and sent over WLAN to the server for post-processing.

Analysis

The KOROVSKI algorithm processes the data and compares it against the reference marker database.

Result

Through whole-herd monitoring, the cattle that actually need prevention are identified.

Prevention

The veterinarian sees the real picture for each cow and intervenes precisely and on time before illness sets in.