Mobile device can accurately and inexpensively monitor air quality using machine learning
Thursday, May 11, 2017 - 06:01
in Physics & Chemistry
UCLA researchers have developed a cost-effective mobile device to measure air quality. It works by detecting pollutants and determining their concentration and size using a mobile microscope connected to a smartphone and a machine-learning algorithm that automatically analyzes the images of the pollutants.