Automating Animal Monitoring & Staff Behavior Detection
for a Leading Network of Dairy Farms
#Data Science & AI
for a Leading Network of Dairy Farms
for a Leading Network of Dairy Farms
The client needed a solution to continuously monitor calf activity levels to assess animal health and to detect any incidents of animal mistreatment by identifying signs of aggressive behaviour from farm staff. This required an advanced system capable of tracking the animals’ behaviour in real time, identifying early signs of health issues, and flagging any aggressive actions by staff members to improve both operational efficiency and animal welfare standards. The solution needed to integrate seamlessly into existing operations while providing accurate insights for both animal health monitoring and human behaviour analysis.
First, accurately tracking calf activity levels to monitor their health was complex, requiring a system capable of detecting subtle changes in behavior, such as standing, lying, or inactivity, which could indicate early signs of illness. Second, detecting and preventing aggressive behavior from farm staff toward the animals was crucial. This required a reliable method to identify aggressive interactions, including enhancements for recognizing individuals despite challenges such as uniform clothing or distance from the camera.
Stellans implemented a comprehensive solution comprising two main components:
Compiled a dataset and trained an object detection model using active learning to detect cows in standing and lying positions and track their activity levels.
First, farm staff were detected and skeletal keypoints were extracted to enable tracking, though uniform clothing initially caused difficulties. To solve this, object and keypoint detection models were retrained using client-specific annotated data. In the second stage, keypoints from each staff track were used to train a transformer-based neural network that identified aggressive behaviour.
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We can’t wait to deliver the best results to you!
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