Digitally-Integrated Smart Sensing of Diverse Airborne Grass Pollen Sources

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Grass pollen is the main outdoor allergen source globally, triggering hayfever and asthma in up to 500 million people. With over 10,000 species, the influence of grass type, location and climate on pollen in the air is not yet known. This is a key issue since subtropical and temperate grasses differ in response to environmental factors. The project aims to use artificial intelligence on digital camera images to learn to see local grass flowers and integrate this with air sensors trained to detect grass pollen types. The expected outcomes are new capacities to track airborne grass pollen types. These outcomes can transform how pollen can be monitored to reduce the burden of allergies, and provide evidence of changing airborne pollen loads.