Title: Precision Management of Animals: Definition, Challenges, and Opportunities
Dr. Isabella Condotta is an Assistant Professor at the University of Illinois at Urbana-Champaign and specializes in Precision Management of Animals (PMA). She has been developing research projects in this area for over 9 years, investigating non-invasive technologies for managing and monitoring production animals. Her current research areas on the PMA field are well-being, automation, and environmental health, with focus on image and sound processing and machine learning techniques. Dr. Condotta has developed machine learning models to acquire weight, lameness level, body condition score, and back fat of swine based on images. She has also developed models to acquire piglets’ body temperatures through thermal images and superficial sensors and studied the impact of environmental enrichment on animals’ behavior through sound and image processing. She has a passion for teaching, with experience in teaching elementary, high school, college-prep, undergrad, and grad students.
Growing populations, rising wealth, and urbanization are translating into increased demand for animal products, which causes a need for rapid intensification of production. With that, economic pressures mount on animal producers, who are forced to increase herds’ sizes in order to be commercially feasible, limiting time of interaction with their animals. In contrast, society is demanding closer attention to the needs of individual animals and their well-being, and reduction of the environmental impact of animal production. Paying closer attention to the animal not only can positively impact animal welfare and health but can also increase the capacity of the producer to increase sustainability while still reaching production needs. That’s when Precision Management of Animals (PMA) becomes necessary: the animals become central to the system and, by automatically interpreting their behavior and physical conditions through principles and technologies of process engineering, it is possible to generate data that feeds real-time monitoring and warning systems for producers, so they can take immediate management actions when needed. This leads to better management choices that are not only driven on profits, but, instead, on the needs of the animals and their care, which leads to a more effective use of resources, including antibiotics, grains, and water; improvement of animal welfare; and a data stream that can help guide new facility designs, and genetic evaluation and selection. This talk will focus on challenges and opportunities on the PMA field from both research and commercial standpoints.
