Internet of Animals: Unsupervised Foaling Detection Based on Accelerometer Data

Pages: 315 - 320
Published: Jun 14, 2021
Abstract
The coming of a foal is often one of the most stressful moments in a horse owners life. Lots of effort is being put in the monitoring of periparturient mares since 10% of foalings require human intervention to assure the well-being of both mare and foal. To remedy this, an unsupervised, machine learning based, anomaly detection algorithm is proposed to detect any abnormalities in a mares behavior that could indicate the onset of parturition. An...
Paper Details
Title
Internet of Animals: Unsupervised Foaling Detection Based on Accelerometer Data
Published Date
Jun 14, 2021
Journal
Pages
315 - 320
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