Development of Cost-Effective Biosensors for Detection of Respiratory Disease in Feedlot Cattle

Bovine Respiratory Disease Complex (BRDC) poses a significant challenge to the cattle industry, leading to substantial economic losses exceeding $4 billion annually in the U.S. and is the leading causeof deaths and illnesses in feedlot cattle. Beyond the direct impact on animal welfare and farmers' livelihoods, the disease contributes to a broader public health issue: the overuse of antibiotics and the rise of antimicrobial resistance (AMR), a global crisis projected to cause millions of deaths and trillions in economic damage if left unchecked. Additionally, recent outbreaks of zoonotic diseases like H5N1 avian influenza in livestock highlight the urgent need for better, earlier disease detection systems to protect both animal and human health, and ensure food security. Current detection methods, mainly relying on visual inspection, are frequently too late for effective treatment. Existing wearable technologies aretoo expensive andlack the capability to monitor crucial vital signs like heart and respiratory rates.Our project addresses this critical need by developing the Seismi health monitoring device, a small, energy-efficient biosensor designed to be seamlessly integrated into existing cattle ear tags. Unlike existing solutions, the Seismi device is planned to be battery-free in its final version, powered wirelessly as cattle approach feeding or watering areas, ensuring continuous, real-time vital sign monitoring without disrupting daily farm operations. In the STTR Phase I, we will focus on optimizing the device's design for durability and continuous operation in challenging feedlot environments, and crucially, training the softwareto accurately interpret cattle heart and respiratory rates with an accuracy similar to standard veterinary medical monitoring equipment. We will then use this data to develop intelligent algorithms capable of distinguishing between healthy animals and those showing early signs of respiratory disease, aiming for high accuracy in detection. The ultimate goal of this project is to provide a cost-effective and reliable tool for early disease detection, significantly improving animal welfare, reducing economic losses for producers, and decreasing the reliance on antibiotics, therebystrengthening overall agricultural biosecurity. This technology also lays the groundwork for future applications in detecting other widespread diseases, tracking livestock from birth to slaughter, offering a comprehensive solution for livestock health management and populationg tracking.