Artificial Intelligence (AI) is now being used by South African scientists to detect and classify pollen spores in real-time, which may improve the forecasting of bioaerosols that trigger respiratory illnesses like allergic rhinitis (hay fever) and asthma.
Monitoring of airborne pollen provides an important source of information for the globally increasing number of hay fever and asthma sufferers.
Up to now, scientists have manually counted airborne pollen and spore types using volumetric air samplers, but with the latest developments in image recognition methods and machine learning, automating this process has become feasible. By combining cutting-edge technologies, like AI and imaging flow cytometry, which measures the size, count, shape and structure of a cell, researchers are able to build a system for South Africa that is capable of identifying and categorising pollen more accurately and at much faster rates.
In addition to AI providing a more comprehensive picture of pollen in the present, it can also help to model historic environmental change that can help scientists get a better grasp on which plants were thriving at any given point in history, potentially dating back thousands to millions of years. Its numerous applications are transforming the way scientists conduct research and is enabling new discoveries across fields – accelerating scientific productivity.
For more on this topic, please refer to the media release below.
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- Prof Jonny Peter, head of the Division of Allergology and Clinical Immunology at Groote Schuur and the UCT Lung Institute, who also leads the South African Pollen Network (SAPNET) – Cape-based.
- Dr Tshego Mabelane, first HPCSA certified Family Physician Allergist in South Africa – Jhb-based.
- Dr Dilys Berman, aerobiologist – Cape-based.
