Precision livestock farming (PLF) — the use of sensors, data analytics, and automated systems to monitor and manage individual animals in real time — offers significant potential for improving animal welfare by detecting problems earlier, enabling more targeted interventions, and providing objective welfare data at scale.
Key PLF Technologies
Accelerometers and activity monitors: Ear or leg-mounted devices track movement, rumination, and lying time in cattle. Deviations from individual baselines indicate oestrus, lameness, or disease. Commercially available systems (SenseHub, Nedap, SCR) are widely adopted in dairy farming.
Automatic milk recording: Continuous monitoring of milk yield, composition, and conductivity per quarter enables early mastitis detection and health monitoring in dairy cows.
Computer vision and AI: Camera-based systems analyse gait (lameness scoring), body condition score, and behaviour patterns. Systems like Cainthus (facial recognition for dairy cows) and SORT/AIMIT (broiler welfare assessment) are in commercial use.
Automated weighing: Weigh stations in passageways or feeders enable continuous growth rate monitoring, flagging individuals that are failing to thrive.
Environmental monitoring: Temperature, humidity, ammonia, and CO2 sensors provide real-time housing quality data.
Welfare Benefits
PLF has demonstrated welfare benefits in practice:
Earlier lameness detection: studies show PLF systems detect lameness 3-5 days before visual observation, enabling earlier treatment
PLF systems generate large quantities of data, but alert fatigue — too many false positives — can reduce compliance and effectiveness. Integration with farm management systems improves usability. Cost remains a barrier for smaller farms. Data interpretation requires training and veterinary support. Most current systems are dairy-cattle focused; PLF for pigs, sheep, and poultry is less mature but developing rapidly.