Cows with Beacon


Improving animal health with modern tracking technology

The aim of DigiStable is to use intelligent, secure interfaces in the digital barn of the future to link new, sensor-detected characteristics for the automatic recognition of personality structures of dairy cows and social interactions with conventional performance, fertility, and health characteristics. The aim is to ensure animal welfare, animal health, and thus also the performance of dairy cows, and at the same time to improve management procedures and occupational safety. The evaluations will be bundled digitally for the farm and mirrored in a familiar channel that is already well-established in practice. In addition, behavioral traits relevant to breeding are to be identified, the recording of which can be implemented at the practice level and thus allows a more comprehensive breeding value profile in order to benefit from digitalization in the long term in the area of breeding as well and to be able to positively advance the safeguarding of animal welfare and animal health on farms.

Records of individual animal behavior patterns are usually too costly on practical farms to be recorded per se. Currently, there is no system available on the market that automatically records personality patterns and social interactions comprehensively and with the necessary accuracy. A promising approach to be able to capture such traits automatically in the barn with sufficient accuracy nevertheless is offered by real-time indoor location technology based on ultrawideband (UWB) technology. Through 3-dimensional position detection in real-time with high accuracies, a wide variety of interactions of dairy cows with humans and other cows as well as reactions to processes in the barn can be tracked and evaluated. The aim is to make this technology, which is already sufficiently established in the industry, usable for agricultural purposes. For this purpose, the technique has to be adapted to the conditions and demands of commercial agriculture in order to extract resilient phenotypes for practical use and to be able to generate an automatic pipeline for management evaluations.

The project is funded by the German Federal Agency for Agriculture and Food.