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Sensors and sensibilities - a focus on improving animal welfare

Sensors and sensibilities - a focus on improving animal welfare

Published:10 August 2018

As a member of the Precision Livestock Management team at CQUni, Eloise Fogarty is undertaking research to monitor sheep welfare at lambing.

As an animal lover and a member of the Precision Livestock Management team at CQUni, Sydney-native Eloise Fogarty has taken on research that involves using autonomous sensor technology such as GPS tracking to monitor sheep welfare at lambing.

After attending high school in Singapore, Ms Fogarty returned to Australia to study Animal and Veterinary Bioscience at the University of Sydney.

She explains that consumers are becoming increasingly concerned about animal welfare and about purchasing ethically-produced food and fibre.

Her research will improve existing welfare monitoring systems. It will also provide consumers with the confidence that the ‘woolly jumper’ they are purchasing has been produced in the most ethical way possible.

“At the moment farmers have a limited amount of time to check that the animals in their care are all ok. This means that, sometimes, sick animals aren’t picked up on straight away and don’t get treated as soon as they could be, and this becomes not only a welfare issue but also impacts farm productivity.

“I’m looking at how on-animal sensors, like GPS trackers and accelerometer sensors (like the Fitbit sensor), can be used to monitor animals remotely to detect any problems. The great thing is that sensors can 'watch' an animal 24/7, meaning we have a much bigger chance of detecting issues earlier."

With Ms Fogarty’s research, she particularly focuses on assessing welfare at the time of the birth of a lamb as this is the most critical time period for both the mother and the baby.

“Lots of things can go wrong and being able to remotely detect the birth using a sensor on the ewe means that farmers can be made aware of any issues and get on top of them quickly,” she says.

“I hope to establish a predictive modelling system that can identify when pregnant ewes are due to give birth. This will ensure farmers can better monitor their animals and maximise the well-being of the mother and offspring."