Team Leader
Skylar La
Texas A&M University
Visualization
lathuytrang16@tamu.edu
Project Type
Research
Who Can Join
Undergraduate Students
Project Description
Bovine Twin is an interdisciplinary research project aimed at reducing methane emissions in beef cattle through the development of a real-time, sensor-driven Animal Digital Twin. Methane represents not only a significant environmental concern but also a major energy loss up to 12% of a cow’s daily dietary intake is lost as methane. Our goal is to recover that lost energy and redirect it into productive growth using intelligent decision support tools.
Using sensor data from GreenFeed (methane), GrowSafe (feed intake), Smart Water (hydration), and Tru-Test RFID enabled scales (weight), we create a minute-by-minute metabolic simulation for each cow at Texas A&M’s McGregor Research Center. This data is integrated into a Python-based agent-based model (ABM) to simulate energy flow and forecast methane emissions. The simulation results are visualized in Unreal Engine 5, where each cow is represented as a dynamic 3D avatar with floating dashboards that show real-time performance metrics.
The digital twin allows users to test diet, feeding strategy, or selective management scenarios and visualize the outcomes on animal growth and methane reduction. This system transforms methane into a quantifiable energy loss that can be mitigated.
Team Needs
We are looking for motivated undergraduate students who are excited about applying their skills to real-world sustainability challenges.
Ideal team members may have experience or interest in one or more of the following:
• Computer Science / Data Visualization: Understanding of Python programming, MQTT or JSON data pipelines, Unreal Blueprints Visual Scripting, and Digital twin.
• Agricultural / Animal Science: Understanding of livestock production, methane mitigation, feed efficiency, or cattle behavior.
Additional qualities we value:
• Curiosity and willingness to learn new tools or domain knowledge.
• Ability to work independently and as part of a collaborative research team.
• Strong communication and documentation habits.
Special Opportunities
As a team member on the Bovine Twin project, you will:
• Work with real-world sensor data collected from Texas A&M’s McGregor Research Center.
• Gain experience with agent-based modeling, digital twin development, and 3D simulation in Unreal Engine.
• Develop technical skills in Python programming, Unreal Blueprints Visual Scripting, data integration (MQTT/JSON), and data visualization.
• Collaborate across disciplines, engaging with researchers from animal science, data science, and engineering.
• Have the opportunity to co-author scientific posters or papers for research conferences.
• Build a strong portfolio of impactful, interdisciplinary work to support future grad school or industry applications.
Most importantly, you’ll join a team working to solve a real-world problem—improving cattle productivity while reducing greenhouse gas emissions.