A Virtual Dairy Farm Brain

Title A Virtual Dairy Farm Brain
Team V.E. Cabrera, M. Ferris, K.A. Weigel, M. Livny, H. White, J. Patel
Term 24 months, 2017-2019
Amount $500,000
Sponsor UW 2020
hhtps://research.wisc.edu/funding/uw2020

Overview

This project will develop a "virtual dairy farm brain," a state-of-the-art suite of real-time integrated dairy farm management decision support tools. The "virtual dairy farm brain" will mimic actual farm management and will learn as it goes by applying complex machine learning pipelines and exploiting the interdependencies of the complex integrated biological, physical, and informational dimensions of dairy farm systems. The project will determine if a dairy farm can substantially improve its economic and environmental performance by interacting, adopting and applying integrated, databased analytics, expert systems, and artificial intelligence contained in whole farm decision support tools through the "virtual dairy farm brain." This innovative project is anticipated to transform how dairy farms will operate in the future and likely become the next big leap in dairy farm management. Dairy farms have embraced technological innovations and procured vast amounts of permanent data streams, but the problem is that they have not been able to integrate all this information to improve whole farm based management and decision-making. It is imperative to develop a system that can collect, integrate, manage, and analyze on-farm and off-farm data in real-time for practical and relevant actions. This project's main assets include using existing data - cow, herd, farm, market, weather, crops, and soils - and integrating these data streams to produce new knowledge and optimized decision-support tools. The project is especially important and relevant to Wisconsin, the largest dairy farm state (10,000 farms), in which dairying contributes half of the agricultural economy, has an impact of $43 billion a year, and supports 80,000 jobs

Objectives and Hypothesis

The specific aims are:

  1. Integrate real-time big data streams
  2. Perform high-level big data integration, analyses, simulation, optimization and machine learning modeling
  3. Develop whole farm decision support tools

The three aims will be executed concurrently and will imply constant and continuous interaction among scientists (data structure - data analysis/modeling - decision aids) and between scientists and the dairy farm in a truly applied research extension project.

Our hypothesis is that a dairy farm can substantially improve its economic and environmental performance by interacting, adopting and applying integrated, data-based analytics, expert systems, and artificial intelligence contained in whole farm decision support tools through the "virtual dairy farm brain."

Some additional info:
UW2020
UW News
The CAP Times
Morning AqClips
Hoard's


Investigators