The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project will result from the development of a quick, easy, and accurate way to count cattle and detect bovine illnesses on feedlots and ranches via Unmanned Aerial Vehicles (UAVs). Current methods for counting cattle are extremely time-consuming or inaccurate, and sometimes both. Additionally, bovine illnesses are often diagnosed too late, leading to 50% of cattle mortalities on feedlots and yielding a $1.9 billion economic loss to the cattle industry. The proposed technology will leverage aerial images to (a) count cattle accurately and efficiently and (b) identify ill cows up to one week before clinical symptoms appear without the need to install expensive health-monitoring equipment on each cow. Ultimately, the proposed technology promises to more broadly impact the way wildlife and endangered species are tracked by automating wildlife counting on aerial images.
This Small Business Innovation Research (SBIR) Phase I project proposes to develop an imaging-based solution for feedlot accountants, nutritionists, and auditors to monitor cattle. The project will leverage aerial photos of feedlot pens to automatically count all cattle breeds - regardless of season and ground conditions - using a combination of deep learning and traditional image processing tools. Additionally, this project will leverage aerial thermography to measure bovine temperatures; machine learning tools will be developed to differentiate between elevated body temperatures associated with illness and those associated with normal confounding factors. The goals of this Phase I project are to develop and fully validate the technology for cattle counting on feedlots and to establish the technical feasibility of leveraging aerial thermographic imaging for prediction of cattle health.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
