Scoping review of precision technologies for cattle monitoring

Abstract

Background: Livestock farming has increased in complexity considerably due to the growing demand for animal products combined with a decreasing number of farmers and ranchers. To meet this challenge, Precision Livestock Farming (PLF) aims to develop fully automated tools to continuously monitor animals, such as cattle, to detect issues earlier and improve productivity. The objective of this scoping review is to provide an overview of precision livestock farming technologies used for cattle monitoring. Methods: The Preferred Reporting Items for Systematic Reviews and Meta-Analyses for Scoping Reviews (PRISMA-ScR) guidelines were followed in this review. Peer-reviewed journal and conference papers from 2005 to 2023 were included, with a focus on technological systems used for cattle monitoring or disease detection. Extracted data included publication year, geographical region, type of technology used, type of monitoring, goal of the intervention, and the level of validation. The relationships between the technology, type of monitoring, and goal of intervention were also explored. Results: 413 papers were found to meet the eligibility criteria. The countries with the most papers were China (n = 55), Japan (n = 52), the United States (n = 38), Australia (n = 25), and India (n = 20). The most common types of technology were found to be inertial sensors (37 %) and images or videos (35 %). Simple classification methods were used in 48 % of papers and machine learning in 29 %. The two most common goals stated in PLF papers were determining animal behavior (30 %) and animal health (12 %). Conclusion: Overall, the results provide a snapshot of the types and uses of technologies in PLF for cattle management and suggest emerging technologies and applications of these tools to improve cattle health and welfare.

Keywords

• Precision livestock farming
• Beef cattle
• Dairy cattle
• Scoping review