I’M not going to lie, to date I’ve often found the ability to put my faith in artificial intelligence (AI) a bit difficult, perhaps because I’m a writer and it naturally makes you feel threatened in some way. However, the more I look, the more I see that, in the context of horses, the ethical debates around creativity etc. can easily be swept to one side by the hugely impressive AI technologies for gait analysis to name but one. AI is transforming the equine industry, and particularly with foaling cameras used to monitor pregnant mares and detect signs of labour. In my mind up until now, there’s no beating an experienced owner or stud attendant who knows their mares inside out, but as anyone who has spent a few weeks foaling knows, there’s no denying exhaustion kicks in eventually.

Traditionally, foaling has always required round-the-clock human supervision, but AI-powered cameras can, according to the manufacturers, make the process more efficient and reliable.

AI-driven foaling cameras use machine learning and computer vision to analyse a mare’s behaviour in real time. These cameras can detect subtle signs of labour, such as restlessness, pawing, sweating, lying down frequently, or changes in breathing patterns. Once the system recognises these indicators, it can send alerts to horse owners or stable staff via mobile apps or text messages, ensuring they can respond promptly.

Traditional monitoring

We already have foaling cameras of course, and foaling alarms, but one of the main arguable advantages of AI in foaling cameras is its ability to reduce human error, often brought on by fatigue from the many late nights in the barn. Since mares often give birth at night, traditional monitoring requires constant observation, which can be exhausting and sometimes ineffective. AI-powered cameras work 24/7, ensuring that no critical signs are missed. Additionally, these systems can record and analyse data over time, improving their accuracy in predicting foaling events.

Enhance accuracy

Some advanced foaling cameras also integrate thermal imaging and biometric sensors to monitor a mare’s body temperature and heart rate. These additional data points enhance the accuracy of foaling predictions and provide valuable insights into the mare’s overall health.

As AI technology continues to evolve, foaling cameras will likely become even more sophisticated, integrating with wearable sensors, smart barns, and automated alert systems.This innovation not only improves foal survival rates, but may also provide peace of mind for horse breeders, reducing stress and labour costs associated with constant foaling surveillance. Ultimately, AI-driven foaling cameras are revolutionising equine care, making the foaling process even safer and more predictable.