The broader impact/commercial potential of this STTR project is in the reduction of healthcare-associated infections (HAIs) by proactively responding to data from novel sensors. In addition, the technology being developed in this project can also help measure airborne particle concentrations in other environments. The successful completion of this proposal will result in improved public health from reduced hospital stay and commercially benefit both hospitals and patients by reducing hospitalization costs. The development and deployment of sensors in a hospital, enabled by this project, will help our startup build a critical dataset to train analytical models for near real-time identification of hospital spaces with a pathogen problem.
This STTR Phase 2 project proposes to develop a novel sensor for integrated measurement of air quality (AQ) and pathogen loads in the air and combine these measurements to create a an early warning system to identify contaminated areas in critical facilities like hospitals. Healthcare-associated infections (HAIs) are $20 billion problem and are responsible for over 100,000 deaths in the US. Our low-cost, robust, networkable, and easy-to-operate sensors will provide a data driven solution to the critical public health problem. Combining novel techniques for real-time detection of airborne particles with state-of-the-art pathogen analysis, our sensor system will provide data to develop analytical models that will predict hospital spaces with pathogen problems before they cause expensive infections.
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.
