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Open YPEC 2021

ON06-Pathogen Prediction Modeling

Arup has collaborated with the City University of Hong Kong to develop a pathogen prediction platform. The platform adopted the AI, IoT and cloud technologies, which ease the deployment of the IAQ monitoring platform into new and existing buildings. The team had successfully overcome the technical barriers in the industry and made pathogens ‘measurable’ and ‘predictable’ at building level with a financially and technically feasible approach. The team actualizes the knowledge regarding pathogens and transmission within built environment and transforms it into tool for prediction and quantification of infection risk with an affordable and technically viable solution. The AI algorithm were supported with pathogen correlation research with onsite sampling, and it has successfully identified the correlations between potential pathogens and commonly measurable parameters in air. Apart from the correlation, the algorithm could also predict the air pollution and thermal comfort trend up to 30 mins with an accuracy of 90%. The HVAC and the purification system can then have sufficient respond time to adopt appropriate adjustment to ensure the stable and excellent air quality. From project experience, the platform helps to reduce more than 1/3 high risk hours during operation period.