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February 9, 2026AgriEngineering2 citationsOpen Access

Precision Livestock Farming for Dairy Sheep: A Literature Review of IoT and Decision-Support Systems for Enhanced Management and Welfare

MMMarco MuraOTOthmane TrimasseVCV. Carcangiu

Key Points

  • This review aims to synthesize advancements in precision livestock farming (PLF) technologies for dairy sheep monitoring and management.
  • Conducted a literature review focusing on PLF technologies from 2018 to 2025.
  • Analyzed applications including weight monitoring, biometric identification, and virtual fencing.
  • Evaluated the impact of IoT, AI, and sensor technologies on dairy sheep farming.
  • Identified key PLF technologies relevant to dairy sheep such as wearable sensors and decision-support tools.
  • Highlighted barriers to practical adoption including economic and ethical challenges.
  • Outlined potential for scalable applications like drone-assisted herding and digital twins.

Abstract

The dairy sheep, vital to the Mediterranean economy, struggles to balance productivity, sustainability, and animal welfare, especially in extensive, small-scale systems. Precision livestock farming (PLF) technologies offer new opportunities by enabling continuous, non-invasive, and data-driven monitoring across diverse farming conditions. Despite rapid progress in sensors, computer vision, wearable devices, and artificial intelligence (AI), a comprehensive synthesis focused on dairy sheep remains limited. This review provides an updated overview of PLF applications in dairy sheep farming, based on a literature review. The 2018–2025 timeframe was chosen to capture recent advances in Internet of Things (IoT), AI, and sensor technologies that have achieved practical relevance only in recent years. The review identifies core technological domains such as automated weight and body condition monitoring, biometric identification, wearable and IoT-based sensors, localization systems, behavioral and thermal monitoring, virtual fencing, drone-assisted herding, and advanced decision-support tools. Innovations including lightweight deep-learning models, multimodal sensing frameworks, and digital twins highlight the growing potential for scalable, real-time applications. While technological progress is substantial, practical adoption is hindered by economic, technical, interoperability, and ethical barriers. This review consolidates current evidence and identifies future priorities to guide the development of integrated, welfare-focused PLF solutions for dairy sheep farming.

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Cite This Study

Mura et al. (2026) studied this question.

synapsesocial.com/papers/698979a6f0ec2af6756e76d5https://doi.org/10.3390/agriengineering8020058
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