Recent advances in machine learning and acoustic signal processing techniques, based on work at Georgia Tech Research Institute Agricultural Technology Research Program, have created an opportunity for automated, real-time monitoring for problematic respiratory sounds. Detection results that track the course of the disease have already been demonstrated in vaccine trials for laryngotracheitis and infectious bronchitis. These techniques are now being adapted and transferred into commercial production environments by AudioT, where they can provide valuable data to keep farmers and vets informed as they make decisions and prioritize their time and resources.

Live Q&A following the presentation moderated by Terrence O'Keefe, Content Director, WATT Global Media