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TRUVACE RECORD VERSION
record: TRV-2026-0951
version: 1
kind: certified
reason: Certified into the record
timestamp: 2026-09-01T06:05:34.617244Z
status: published
lens: g_space
sector: other
headline: Precision Livestock Farming Technologies for Sheep Welfare in Extensive Systems: A Comprehensive Review
dek: Background Ensuring animal welfare in extensive sheep production systems remains challenging due to large grazing areas, limited human supervision and the difficulty of detecting early signs of health or behavioural problems. Precision Livestock Farming (PLF) technologies have emerged as promising tools to enhance monitoring and welfare assessment in such environments. Objective This review examines recent advances in PLF technologies and their potential contribution to improving sheep welfare in extensive farmi…
gain_title: Wearable PLF sensors achieved up to 85% accuracy for lameness detection and over 97% accuracy for stress-related physiological changes in extensive sheep systems.
problem_title: (none)
trace_subject: (none)
gain_reading: Wearable PLF sensors achieved up to 85% accuracy for lameness detection and over 97% accuracy for stress-related physiological changes in extensive sheep systems.
gain_evidence: wearable devices, including accelerometers and Global Positioning System (GPS) collars, can achieve up to 85% accuracy in detecting lameness and over 97% accuracy in identifying stress-related physiological changes
problem_reading: (none)
problem_evidence: (none)
quick_read: This peer-reviewed review from September 2026 synthesized more than 35 studies on precision livestock farming for extensive sheep production, where large grazing areas and limited supervision make early health detection difficult. It assessed wearable sensors, GPS collars, computer vision, AI and environmental monitoring including drones and ground-based sensors.

The synthesis matters because it quantifies monitoring gains that could improve welfare, productivity and sustainability, while also showing why those gains have not yet scaled. Uncertainty remains about cost-effective deployment, standardized welfare indicators and participatory design needed for wider farmer adoption.
limitation: Adoption remains limited due to economic costs, technical constraints and limited farmer awareness, and findings are from a synthesis of prior studies rather than a new field trial.
tag: Evidence-backed gain
key_points: Review synthesized more than 35 peer-reviewed studies on wearable sensors, computer vision, artificial intelligence and environmental monitoring for sheep. | Integration of remote sensing tools, drones and ground-based sensors improves monitoring of grazing patterns, social behaviour and environmental conditions. | Background challenge is large grazing areas, limited human supervision and difficulty detecting early signs of health or behavioural problems.
rundown: The review examined wearable devices including accelerometers and GPS collars, plus computer vision and environmental monitoring, for behavioural and physiological assessment in sheep.

By the September 2026 publication date, the literature reported up to 85% accuracy for lameness detection and over 97% accuracy for stress-related changes, while noting that cost, technical constraints and farmer awareness still limit adoption.
sources:
- peer_reviewed | Veterinary Medicine and Science | https://doi.org/10.1002/vms3.71207 | 2026-09-01
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