Abstract

Abstract The modern livestock industry is increasingly adopting data, technologies, and automation into daily husbandry and management routines and decisions. These advances in precision livestock farming (PLF) enable improved financial margins, sustainability, efficiency, and animal productivity and welfare. However, there is currently a gap between the engineers and data scientists designing the technologies and the animal scientists and caretakers using them. At North Carolina State University a novel course on PLF Systems for undergraduate and graduate students was developed in the Department of Animal Science. Through lecture delivery, livestock production scenarios, scientific literature, and data-based homework assignments students explored data collection, management, analysis, and data-based decision making. Students gained hands-on experience with a variety of sensor types and signal processing through lab-based activities. Basic hardware and software development concepts were explored during an Arduino-based microcontroller activity. The course was developed and refined using student feedback to include additional sensor and lab-based days and additional in-class supported activities utilizing Excel for data manipulation, processing, and presentation. Self-reported student learning results were collected across two semesters (19 students; 18 Animal Science, 1 Biological Engineering) with84% of students indicated the course was effective in increasing their ability to evaluate and implement technology in livestock production systems and 74% of students reported increased knowledge of coding and software, as well as their ability to clean, analyze, and make sense of raw data. The topics and delivery methods implemented in this course could inform the basis for development of similar interdisciplinary PLF courses at other academic institutions.

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