3D tech which detects emotional state of pigs could benefit farmers

The study sees pigs’ facial expressions analysed using state-of-the-art 3D technology (Photo: SRUC)
The study sees pigs’ facial expressions analysed using state-of-the-art 3D technology (Photo: SRUC)

New technology that can detect the emotional state of pigs could lead to a tool that can monitor animals’ faces and alert farmers to any health and welfare problem.

Pigs, which are highly expressive animals, will have their facial expressions analysed using state-of-the-art 3D technology.

Research has previously shown they can signal their intentions to other pigs using different facial expressions.

There is also evidence of different expressions when they are in pain or under stress.

Animal behaviourists from Scotland’s Rural College (SRUC) have teamed up with machine vision experts at the University of the West of England (UWE Bristol) for the study.

At SRUC’s Pig Research Centre, scientists are capturing 3D and 2D facial images of the breeding sow population under various, typical commercial situations that are likely to result in different emotional states.



For example, sows can experience lameness and could show different facial expressions relating to pain before and after being given pain relief.

Detecting positive emotional state is more novel but sows are highly food motivated and appear calm and content when satiated. Researchers hope this mood could be reflected in sows’ facial expressions.

On-farm use

Images are then processed at UWE Bristol’s Centre for Machine Vision, where various machine learning techniques are being developed to automatically identify different emotions conveyed by particular facial expressions.

After validating these techniques, the team will develop the technology for on-farm use with commercial partners where individual sows in large herds will be monitored continuously.

Professor Melvyn Smith from UWE Bristol’s Centre for Machine Vision said: “Machine vision technology offers the potential to realise a low-cost, non-intrusive and practical means to biometrically identify individual animals on the farm.

“Our work has already demonstrated a 97% accuracy at facial recognition in pigs. Our next step will be, for the first time, to explore the potential for using machine vision to automatically recognise facial expressions that are linked with core emotion states, such as happiness or distress, in the identified pigs.”



Early identification of pig health issues gives farmers the potential to improve animal wellbeing by tackling any problems quickly and implementing tailored treatment for individuals.

This will reduce production costs by preventing impact of health issues on performance.