Abstract: In an approach for controlling a multiphase flow configured to create a plurality of particles, a processor obtains images of a plurality of particles in a multiphase flow. A processor provides the images to a neural network adapted to determine a distribution of a spatial property of the plurality of particles from the provided images. A processor determines the distribution of the spatial property of the plurality of particles in the multiphase flow, based on the provided images, using the neural network. A processor controls the multiphase flow based on the determined distribution.

Abstract: Evaluating certain risks that are involved with respect to the transmission of pathogens in a given physical space. Some aspects of the present invention include applying privacy-preserving artificial intelligence (AI) algorithms and physics-based simulations on image data to characterize the potential source of pathogens. A multi-outcome artificial intelligence (AI) model that identifies object interactions and human actions, combined with physics-based simulations is used to accurately evaluate pathogen load distributions and infection risks.