Move over, artificial insemination. There’s a new “A.I.” in town, and it’s more intelligent than you.
A graduate student at the University of California-Davis has developed a customizable artificial intelligence (A.I.) platform that analyzes cow behavior data to help farmers anticipate changes and problems in their herds, and choose the right management interventions to address them.
Animal biology PhD candidate Catie McVey said she developed the platform, called DairyFit, utilizing data that already is being captured from sources like activity monitors, ear tags, and other precision dairy technologies that document behaviors like eating, chewing cud, walking, and resting time.
“DairyFit helps to pull out patterns hiding in big, messy data streams,” said McVey. “Then it lets the farmer decide…I want to empower farmers with data, not replace them.”
An interesting example of the power of DairyFit emerged in the analysis of sick-cow behavior. McVey and her team anticipated that sick cows would enter pens last, with their healthier herd mates leading in the front. Instead, they found that healthy cows led from the front and chased from the back, sandwiching the sick cows in the middle of the pen to keep the herd together.
Earlier this year, McVey’s research earned the “Animal Health + Industry” award as part of the Big Bang! Business Competition at UC-Davis. She currently is testing DairyFit with a group of farmers, with the goal of converting it to a smartphone app.
The platform can be applied to herds of all sizes and is designed to by highly affordable, opening up the world of big data analysis to small farmers. “We should be giving them tools to engage with their data,” McVey declared. “I’m never going to make an algorithm that knows better than the farmer. And I don’t want to live in a world anymore where the algorithms that monitor my online shopping are more sophisticated than the ones that keep my cows alive.”
