Precision Management of Animals (PMA) integrates sensors, data analytics, and automation within livestock environments. These tools are reshaping how producers monitor animals in systems that face increasing pressure from changing welfare expectations, limitations on antibiotic use, recurring and emerging diseases, environmental regulations, climate variability, and chronic labor shortages. Consolidation has expanded the number of animals under the care of a relatively small workforce. Under these conditions, it becomes difficult to recognize early signs of illness or performance decline. Subtle changes in behavior or physiology are often missed during routine observation, especially in species with minimal individual identifiers such as broilers, laying hens, or pigs.

The concept of PMA aligns closely with the broader field of precision livestock farming (PLF), which focuses on continuous, automated monitoring of animals and their environments. PLF and PMA share the goal of improving management by leveraging sensor-based information to inform timely, informed decisions. PMA emphasizes the integration of these tools into management practices across U.S. production systems, and PLF provides the technological foundation that enables these practices to function at a commercial scale.

Labor availability continues to be one of the most persistent constraints. Producers struggle to recruit and retain employees in sufficient numbers, and turnover rates remain high. Fewer caretakers are responsible for more animals, often across multiple barns or sites. This situation limits the ability to identify individual animals that are beginning to experience health or welfare issues and can introduce safety risks for both animals and workers. Production losses and welfare challenges increase when minor changes in activity, posture, or performance are overlooked.

Commercial livestock systems have traditionally relied on herd- or flock-level assessment. Although caretakers observe animals daily, time constraints make it nearly impossible to consistently identify individuals that need attention. Rapid and reliable individual-level monitoring is therefore essential. PMA technologies, such as wearable sensors, machine-vision systems, microphones, environmental monitors, and integrated data platforms, support continuous observation of groups and individuals. These tools detect subtle behavioral patterns that signal stress, disease, or injury and support targeted care that improves individual outcomes. Enhanced early-warning systems developed through PMA are increasingly critical for protecting U.S. livestock industries from emerging and invasive disease threats that jeopardize agricultural security and producer profitability.

To reach their full value, PMA systems must integrate production, environmental, health, and behavioral data into outputs that are clear, reliable, and useful for producers. Individual-level information accelerates detection and treatment of clinical and subclinical disease. Earlier intervention reduces animal suffering, prevents disease spread, lowers antimicrobial use, and decreases medication and treatment costs. Benefits extend to workers through improved safety and more predictable workflows, and to facilities through improved efficiency and reduced environmental variability.

PMA also creates opportunities to define novel phenotypes that cannot be measured through traditional observation. Continuous digital monitoring provides information related to maternal behavior, disease resilience, thermotolerance, activity patterns, social interactions, feeding behavior, gait characteristics, and responses to environmental stressors. These novel phenotypes have immediate relevance for management and long-term value for genetic improvement. Breeding programs increasingly incorporate sensor-derived phenotypes to identify animals that are adaptable, productive, and robust. Engineers use these digital data streams to evaluate how design, ventilation, lighting, stocking density, and environmental conditions shape behavior and performance, which supports innovation in barn design and climate adaptation.

The rapid growth of PMA has accelerated the shift from primarily manual animal care to an integrated, data-driven management model. This work requires collaboration across engineering, data science, animal science, veterinary medicine, and genetics. Electrical engineers contribute to sensor development, computer scientists design machine-learning models, animal scientists interpret behavior and welfare, veterinarians guide health-related applications, and agricultural and biological engineers integrate these components into functional systems.

Livestock production practices vary across regions, which reinforces the need for coordinated multistate efforts. The North Central Region represents more than one-third of U.S. livestock and poultry production and supports a large agricultural economy. Its Experiment Stations and Cooperative Extension networks are positioned to advance PMA research and guide deployment. Since the initial formation of this multistate project, interest and capacity in PMA and PLF have expanded significantly. The U.S. Precision Livestock Farming Conferences held in 2023 (Knoxville, TN) and 2025 (Lincoln, NE) demonstrate national and international engagement in this area. Universities across the region continue to add faculty positions that support PMA research, reflecting recognition of the need for long-term investment in this discipline.

The PMA multistate committee remains essential for maintaining coordinated progress. It brings together expertise from engineering, animal behavior, genetics, veterinary medicine, and data science to address problems that exceed the capacity of individual institutions. Shared knowledge, aligned research priorities, cross-station collaboration, and industry engagement strengthen the development and evaluation of PMA tools. This coordinated structure ensures that research outcomes are practical, scalable, and applicable across livestock species and production systems, and it underscores the continued relevance of renewing this project.  NC1211 directly advances USDA’s 2025 Farmers First priorities by developing precision technologies that increase producer profitability through automation and labor efficiency, strengthen protection of American agriculture through earlier detection of disease and health threats, and expand market opportunities by generating new precision phenotypes that improve livestock productivity, resilience, and product quality. Additional benefits include improved resource-use efficiency that supports long-term agricultural sustainability.