Azemi is professor and chair of electrical & computer engineering at UW–Platteville. His research interests include the application of dynamical systems and signal modeling, stochastic estimation, and computational analysis in several areas, such as control systems, power systems, communications, bio-computing, and social computing.
Farms have relied on human vision to observe and interpret animal behavior. As farm sizes increase and labor changes, it is more challenging to rely on human observations. The goal of this project is to design a modular, low-cost monitoring system using sensors, computer vision and artificial intelligence to assist Wisconsin dairy farmers with the health and welfare of their herd and grow their farm business. In the full version of the system, the smart cameras and sensors will observe and detect nutritional, behavioral, health and environmental activities that can impact animal welfare and wellbeing. Next, we will translate this visual information and sensor collected data into actionable insights that enable the farmer to make data-driven decisions to improve farm operations and animal health. The idea of using an artificial intelligence system for dairy farm management is not new, but existing systems are too expensive for many farmers. The outcome of this project will provide an opportunity for farmers to employ an affordable system and grow their business.