Dr. Austin Polebitski, an Associate Professor in Civil and Environmental Engineering, will focus on data collection, platform usability in decision support, and create and implement the surveys. He will be responsible for development of the analytics code and coordinating project meetings with the producers as well as coordinate undergraduate efforts in data analysis. Dr. Polebitski has a long history of provided decision support to utilities regarding short term and long-term operations as well as in planning for climate change. His PhD research focused on prediction of fine-resolution municipal water demands based on demographics.
Dr. Argyha Das, an Assistant Professor in Computer Science, an Assistant Professor in Computer Science and Software Engineering, will help in requirement analysis, design, implement the analytic pipeline on leveraging the recent advances in cloud and related technologies. He will also help mentoring the undergraduate student for data analysis. Das got his Ph.D. in big data analytic and has multiple years of experiences in data-engineering and data-analysis in both industrial and academic project.
Dr. Andy Bohnhoff has been in the dairy industry his entire life. He grew up on a family farm in Plymouth WI where his family milked 100 cows in a stall barn. He attended the University of Wisconsin Madison where he graduated with honors with a degree in Animal Science. He then attended University of Wisconsin School of Veterinary Medicine where he focused on production medicine and surgery. After graduation, he furthered his schooling by attended the Colorado State University School of Veterinary Medicine where he completed an internship in Integrated Livestock Management/Food Animal Medicine and Surgery. He practiced veterinary medicine in Colorado for 3 years before returning to the Land of Beer and Cheese(Wisconsin) where he started focusing his efforts on Dairy Nutrition and Health Management. He currently works for Prairie Estates Genetics providing technical support for dairy farms and also provides primary nutrition consulting for dairies in Wisconsin and Colorado.
This research project consists of four phases: producer engagement to understand current use of on-farm data and the collection of historical data, creation of the DAIRI platform and populating of the databases for each producer, use of DAIRI in daily operations and decision making, and comparative analysis of important metrics related to herd health and revenue.
Phase 1
The research team will tour facilities and understand farm operations related to dairy production, the types of data streams that are generated, and discuss the metrics that are most important to that producer’s goals.
Phase 2
The team will use the recent advances in cloud-based technologies, deploying the custom databases and analytics software. The analytics reports will be available as a web-based, live dashboard to the dairies/partner-industries.
Phase 3
With the partners using the platform to upload data daily as well as pull reports. Usage will be monitored as well as periodic surveys administered to understand how the producers are using the platform in daily operational.
Final Phase
The final phase of the research uses what was both gathered and learned in the first three phases to create a comparative analysis of operations before and after use of the DAIRI decision support tool.
The expected outcome of this project is to have producers more engaged with their data and to provide undergraduate researchers with a real-life project with tangible outcomes. Day-today operations of farms are complicated, time consuming, and hands-on, with many decisions having to made daily that could impact revenue or herd health over the next week or longer. DAIRI will provide near real time assistance with decision making as feed adjustments, grouping strategies, lactation rotations, and health of each animal can be tracked and visualized, providing a single-point shared resource that the farmer can discuss with nutritionists, feed consultants, and farm technicians, keeping all eyes focused on the same data and situation. The research team expects that daily or weekly use of DAIRI will result in increased herd health, more streamlined operations, and hopefully increased revenue for the partner producers, as well as better data management. The team will provide an undergraduate research student the opportunity to meet with partners and learn how to take their needs and translate that into an end-product. This will provide the student with training that mirrors real professional life. The team hopes to work with a student(s) within data science and/or agribusiness/agronomics that is passionate about connecting end-user needs to easy to understand and implement web interfaces.
