Physical AI for Smarter, Sustainable Farming, and Beyond

At the intersection of artificial intelligence and agricultural engineering, Physical AI for Precision Agriculture brings intelligence directly into the farm environment. Our research focuses on developing smart, sensing systems—from energy-harvesting wearable ear tags and implantable biosensors to edge-computing devices and vision-based AI—that continuously monitor animal health, welfare, and behavior in real time. By integrating data such as body temperature, movement, and environmental conditions, these systems can detect early signs of heat stress, disease, or discomfort in individual cows.

Projects like MmCows combine multimodal sensing, computer vision, and machine learning to turn complex barn data into actionable insights for farmers. Beyond improving livestock welfare, these technologies create adaptive systems that automatically optimize ventilation, cooling, and feeding, advancing sustainable and energy-efficient farming.

Importantly, the same physical AI principles that make farms “intelligent” have strong potential in human healthcare. The minimally invasive biosensing, continuous vital monitoring, and low-power edge AI architectures developed for cattle can be adapted for wearable and implantable medical devices, remote patient monitoring, and preventive health systems. In this way, innovations born in agriculture may also help build the next generation of personalized, energy-efficient healthcare solutions.