Teaching
AN SCI/BSE 344 – Digital Technologies for Animal Monitoring (3 credits, Spring Semester)
Course Description: Sensing Technologies have revolutionized agricultural systems in the past decades. The use of Artificial Intelligence (AI) systems for livestock animals and veterinary medicine has allowed great advances in animal monitoring, computer-aided diagnosis, and optimal farm management decisions. The objective of this course is to provide key concepts of sensor technology used for livestock and companion animal monitoring and veterinary medicine. The course is based on lectures and in-class discussions of journal articles.
AN SCI 875 – Advanced Digital Agriculture (3 credits, Fall Semester)
Course Description: This three-credit course will focus on key concepts and applications of sensor technology and data analyses applied to livestock, environment, and crop production. In this course the students will (1) understand what precision agriculture is and why it is needed;(2) become familiar with data science principles; (3) learn the current remote sensing technologies in livestock and agricultural systems; (4) understand the principles and applications of sensor technology applied to animals, crop and environment; (5) become familiar with GIS (Geographic Information Systems) software; (6) gain a basic understanding of principles and applications of data analyses; (7) become familiar with cloud computing and data visualization; and (8) apply precision agriculture to a real situation.
Requirements: Prior coursework in MATH 112 and MATH 113 (or equivalent) and one Stats course (for example: STAT 301, STAT 371, or STAT 571)


