Mamunur Rahman is an assistant professor of industrial and systems engineering at the University of Wisconsin–Platteville. Rahman’s research interests include supply chain resilience, green logistics, and process improvement using computer simulation, optimization, and machine learning.
This study proposes Precision Livestock Farming (PLF) to enhance dairy calf health and welfare. The traditional methods of periodic observations for monitoring animal health are deemed insufficient, leading to potential delays in identifying health issues. Precision Livestock Farming, utilizing continuous data collection from sensors, aims to provide real-time insights into the well-being of dairy calves.
The methodology involves a pilot project at Pioneer Farm, encompassing data harnessing from the Cow Manager (ear tag) system, and developing predictive machine learning models to forecast potential health issues. The expected outcomes include real-time information for dairy farmers to institute preventive measures and enhance operational efficiency in dairy farming through optimized calf health management practices. Students majoring in animal science and industrial and systems engineering will actively participate in various project phases, gaining hands-on experience by applying their knowledge to real-world problems, thereby contributing to both the project’s success and their academic growth.
The proposed work aligns with two priority areas of the UW Dairy Innovation Hub: (1) monitor animal health with PLF technologies within “Ensure Animal Health and Welfare” and (2) use big data to optimize dairy farm operations within “Grow Farm Businesses & Communities.”