NSF Convergence Accelerator Real-World Chemical Sensing Applications: Sensory Nature-Inspired Technology Platform for Monitoring Indoor Air

About This Grant

Healthy indoor air quality is paramount to human health, especially considering that on average, Americans spend approximately 90% of their time indoors. Current commercial indoor air quality sensor systems are unable to identify or distinguish specific chemicals in the air, including toxic compounds from natural substances. As a consequence, these systems fail to determine the level of harm and alert about negative effects on health, which can contribute to cancers, cardiovascular and neurodegenerative diseases and other medical conditions. Current air quality sensors also tend to report inaccurate concentrations of chemicals in the air, require frequent recalibration, and are expensive. To address this technology gap and to keep Americans safe, this project seeks to develop and commercialize a sensory nature-inspired technology platform for monitoring indoor air. The product is a low-cost, highly accurate indoor air quality monitoring system that provides precise, real-time information about hazardous chemicals in indoor air. Offering seamless building integration, the technology first alerts customers, such as building managers. Knowing the status of the air inside each room and space gives the customers the ability to quickly identify problems and take immediate action, such as building ventilation adjustment, air cleaning, or, in extreme cases, tenant evacuation. In addition to the immediate public health benefits, the outcomes of this project provide impacts across multiple U.S. sectors that require real-time gas sensing, including disease diagnosis, search-and-rescue, food spoilage monitoring, and hazardous waste identification. The project’s technology platform for monitoring indoor air incorporates bio-inspired technological concepts to overcome the limitations of current indoor air quality sensor systems, providing exceptional sensitivity, specificity, and robustness to variations in factors like temperature and humidity. Specifically, the technology’s key elements include (1) an array of inexpensive off-the-shelf chemiresistive sensors, (2) the modulation of the intake and expulsion of air (akin to biological sniffing), (3) state-of-the-art temporal data processing, and (4) machine learning models to distinguish specific chemicals in the air. As a low-cost, highly accurate, real-time indoor air quality monitoring system, this technology is poised to improve the ability to measure indoor air and prevent negative health effects stemming from hazardous air quality, and usher in a new era of indoor air quality sensing. This investment will de-risk this technology platform, positioning it for potential future commercialization by the private sector. 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.