Happy or unhappy cow? Data Science takes us closer to animal welfare
Can we use artificial intelligence to help improve communication between humans and cows? Cengiz Cetinkaya thinks so and thus developed a machine learning model for real-time emotion prediction in his Data Science MSc programme at Lucerne University of Applied Sciences and Arts.
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Cengiz Cetinkaya
Former HSLU Applied Information and Data Science student
Professor Mr. Peter Gloor, MIT Massachusetts (Boston) Institute of Technology:
Innovative Researcher, Scientist, Lecturer & Entrepreneur
Bridging hearts with Data Science: the happy animal revolution
Cengiz’s model aims to gauge bovine bliss levels by identifying anxiety and stress in real-time – using machine learning in images and videos to recognize whether a cow is happy or unhappy.
Artificial Intelligence helps him to rethink animal welfare. Will soon only happy cows graze on our pastures? Cengiz’s Master’s thesis takes us to a trough full of ideas for animal welfare.
A project is underway about launching a “Happy Cow” label that cattle breeders can use to groom the public’s perception of their operations.
And anyone wanting to learn more about their four-legged best friend’s mental state can use the “waggydog” app from the start-up FaunaAI. The first version of the app is for dogs, but prototypes for cows, horses and cats are already in the pipeline.
The app is already available for iOS and Android: Click here to download the app.
We would like to thank Cengiz Cetinkaya and Peter Gloor for sharing these fascinating insights into this groundbreaking project!
Author & Masterstudent: Cengiz Cetinkaya
Former HSLU Applied Information and Data Science student
Supervising lecturer: Professor Mr. Peter Gloor, MIT Massachusetts (Boston) Institute of Technology
Innovative Researcher, Scientist, Lecturer & Entrepreneur
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