Preprint Review Version 1 Preserved in Portico This version is not peer-reviewed

Automated Tracking Systems for the Assessment of Farmed Poultry

Version 1 : Received: 14 May 2021 / Approved: 16 May 2021 / Online: 16 May 2021 (22:43:58 CEST)

How to cite: Neethirajan, S. Automated Tracking Systems for the Assessment of Farmed Poultry. Preprints 2021, 2021050364 (doi: 10.20944/preprints202105.0364.v1). Neethirajan, S. Automated Tracking Systems for the Assessment of Farmed Poultry. Preprints 2021, 2021050364 (doi: 10.20944/preprints202105.0364.v1).

Abstract

The world's growing population is highly dependent on animal agriculture. Animal products provide nutrient-packed meals that help to sustain individuals of all ages in communities across the globe. As the human demand for animal proteins grows, the agricultural industry must continue to advance its efficiency and quality of production. One of the most commonly farmed livestock is poultry and their significance is felt on a global scale. Current poultry farming practices result in the premature death and rejection of billions of chickens on an annual basis before they are processed for meat. This loss of life is concerning regarding animal welfare, agricultural efficiency, and economic impacts. The best way to prevent these losses is through the individualistic and/or group level assessment of animal on a continuous basis. On large-scale farms, such attention to detail was generally considered to be inaccurate and inefficient, but with the integration of Artificial Intelligence (AI) assisted technology individualized and per-herd assessments of livestock are possible and accurate. Various studies have shown cameras linked with specialized systems of AI can properly analyze flocks for health concerns, thus improving the survival rate and product quality of farmed poultry. Building on the recent advancements, this review explores the aspects of AI in the detection, counting and tracking of the poultry in commercial and research-based applications.

Subject Areas

Poultry behaviour; target tracking; deep learning; precision livestock farming; poultry production systems.

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