Remote sensing applied to facial recognition in cows and more

Lakeland College continues to By Dr. Yuri Montanholi build on partnerships to advance Instructor & Researcher on the development and validation of novel technologies to support the demand of the livestock sector for optimizing animal remote monitoring, for enhancing production efficiency, while promoting animal welfare and sustainable production. Through a collaboration with an Alberta based company, OneCup AI (onecup.ai), research on computer vision artificial intelligence is being further

investigated and optimized as a tool to quickly and precisely identify individual beef and dairy cattle. The technology is also being used to detect the onset of calving in commercial herds using the cattle herds at Lakeland College. With this project, livestock producers will benefit from improved animal identification and earlier prediction of calving. As well, students will have hands-on experience with innovative precision livestock farming tools.

Advances in animal identification are aligned with Canadian livestock industry strategies to enhance livestock traceability to ensure animal health, food safety, and to enable the use of other precision livestock technologies. Research at Lakeland College is validating and optimizing the application of an automated camera suit developed by OneCup AI, called BETSY (Bovine Expert Training and Surveillance), to perform facial recognition in mature and growing cattle. In fact, the cattle individual recognition is a more encompassing subject under BETSY, by incorporating several body landmarks. Bounding boxes and key points are used to train and enable BETSY’s predictions (Picture 1). BETSY runs in two primary vision algorithms, organized into layers: network for bounding boxes (cow, head, hide, tail, udder, knee, and, hoof) and network for the key points, of which there are approximately 40. Bounding boxes form a natural hierarchy, where each bounding box must reside in a cow. The key points form a graph with natural symmetry. The symmetry is key to accuracy; if BETSY knows where an eye, ear and nostril is, it knows where to look for the opposing eye, ear, and nostril. The assessments in mature animals are being conducted in dairy and beef cows, as these animal types have unique features that can be sensed by the imaging system. While Holstein dairy cows have distinct black/brown and white patterns, the beef cows have more uniform color patterns with varying hair length over the seasons. The remote monitoring of growing animals is designed to address the facial changes occurring on the animals during their rapid growth phase. Is BETSY able to recognize a newborn animal and then still recognize the same animal later in their life? We are addressing this question by monitoring newborn heifer calves from birth until their breeding age. During the nursing period, BETSY is able to capture images at the automated feeding system (Picture 2), which is visited by the calves several times daily. Then, during the rearing phase, BETSY will continue monitoring the juvenile heifers at the rearing pen. Collectively, these studies on facial recognition will assist to build algorithms and contribute to ensure the robustness of this touch-less and tag-less identification method of cows.

Among several husbandry practices, calving constitutes a great example of where remote monitoring could be of paramount benefit both for the welfare of animals and the economic success of cow-calf enterprises. At Lakeland College research is underway using BETSY to automatically detect and monitor behaviors at the onset of calving. Calving signs are to be continuously monitored at the College’s dairy (Picture 3) and beef (Picture 4) herds. With the 24/7 monitoring, the imaging system will be able to sense the individual changes in each cow related to the proximity of parturition. These changes include expansion of the udder, vulva relaxation, Beef cows close to calving disappearance of pelvic ligaments, mucous discharge, restlessness and “weird” behaviors, among others. Upon proper development and validation, this combination of artificial intelligence and imaging analysis will assist producers in earlier and more convenient detection of calving, potentially reducing labor on farms especially during the cold months of the year. Moving forward, other aspects of livestock husbandry will be targeted via imaging automation, including research on early disease detection, support for reproduction (i.e. estrus detection) and, remote monitoring of welfare. This collaboration between Lakeland College and OneCup AI will contribute to shape practical and cutting-edge imagingbased solutions for the cattle and dairy industries in Alberta and beyond, while supporting ever important advanced training of our students.