Q-Track Milk Operations Optimization System

Automated milking systems make dairy operations more efficient and less stressful for animals and farmers alike. However when a problem occurs, a suspect animal must be found and diagnosed quickly. This effort aims to evaluate the feasibility of a Q-Track Milk Operations Optimization (Q-MOO) system. The proposed Q-MOO system will employ a novel, low-frequency real-time location system (RTLS) that exploits Near-Field Electromagnetic Ranging (NFER) technology. NFER RTLS has the potential to provide high accuracy location data of animals at a reasonable cost even in complicated RF propagation environments such as when animals are clustered in close proximity or when line-of-sight to a receiver is obscured by metal fences, shelters, or structures. This effort also aims to take a more comprehensive look at the value of location data in optimizing dairy operations. Teaming with dairy experts at Auburn University, Q-Track will explore whether location awareness can further enhance the safety and productivity of dairy operations by correlating animal locations, associations, activity levels, and other innovative ways location data can add value. Our commercialization partners anticipate the proposed system will be economically viable by reducing the labor required to find a suspect cow and speeding intervention in the context of automated milking systems. We will further explore additional value and benefits in a trial at Auburn University's E.V. Smith Dairy Research Center.