A Penn State-led research team used data from low-cost sensors, artificial intelligence and mobility data to improve models that assess human exposure to fine particulate matter (PM 2.5), tiny particles in smoke and other forms of air pollution that can pose health dangers. Public health officials can use the models to develop strategies to reduce exposure to unhealthy air quality, according to the researchers.
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