Teen Uses AI and Sensors to Expose School Air Pollution and Prompt County Action

While studying South Bay air data, Kelly Liu realized regional monitors did not capture the conditions inside many classrooms. She created AI models that layered traffic, weather and location data to predict pollution levels around individual schools. To verify the predictions, she organized the installation of affordable particulate sensors at several underserved campuses, giving students real-time readings.

The resulting maps and sensor data made clear that exposure varied dramatically between nearby schools, prompting parents and educators to demand better filtration, ventilation and response plans. County officials have begun discussing uniform air-quality standards and funding to address the gaps. Liu’s project illustrates how youth-led research can turn hidden environmental inequities into actionable policy.