SBIR Phase I: Early Disease Prediction with Cattle Muzzles Using Artificial Intelligence, Facial Recognition, and Camera Capturing Technology

This Small Business Innovation Research (SBIR) Phase I project addresses the need for technologies that can benefit the production, protection, and health of agricultural animals, like cattle. The profit margins for cattle owners are very thin. Treating a disease costs cattle owners on average about $80 per head. By the time an owner can tell their cattle are infected, it is typically too late to prevent infection and the spread of the disease in the pen and feedlot. With the successful implementation of the proposed technology, cattle owners will save on average about $80 per head. For an average 500-head owner, pinkeye can impact 90% of the individual cattle herd if one individual animal is infected, costing over $15k to treat in the case of an outbreak. The proposed technology aims to reduce the cost to only the cost of one vaccine since the proposed system should alert the owner about this risk early, allowing early isolation before the disease is able to spread. The proposed solution would enable early disease detection, help to secure the US food supply chain, reduce the emission of greenhouse gasses, and benefit the US economy by preventing cattle loss. This Small Business Innovation Research (SBIR) Phase I project proposes to demonstrate the feasibility of a novel artificial intelligence (AI) technology to detect Bovine Respiratory Disease early on in a small pilot study. The company will develop an app (beta-version) that can automatically take pictures of cattle, use AI to analyze the muzzle, and then immediately send a notification of infected cattle to the cattle owner. When new calves that are sick enter a feedlot setting, they typically are not as active as healthy calves. There are also visible symptoms such as droopy ears, nasal discharge, and watery eyes. However, since the calves might be stressed due to travel, these symptoms do not necessarily mean the calf is sick, making it challenging to identify sick cattle. If successful, the proposed solution would reliably identify sick cattle and thereby enable early, targeted treatment. 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.