Aire Mexico City
AIRE Sao Paulo
Aire V.3 is a machine learning generated audiovisual album driven by patterns found in pollution data levels in different cities around the world: Mexico City, Bogotá, and São Paulo. All data is provided by the Resource Watch predictive system, designed by the World Resource Institute and NASA.
Interspecifics created a series of sounds and visual compositions showing the dynamics of air pollutants in each of these three cities. The first stage of the project consists of an A/V experience in ten-minute segments showing cityscapes made from 3D map elevations and satellite imagery, accompanied by generative sound compositions. Pollutants are analyzed on a saturation scale and assigned a sound identity on their own that responds to the data flow through modulation or control signal. The most relevant and particular patterns detected by our customized machine learning tool are used to trigger and mute the sound events as they occur, establishing the structure of the entire composition.
Aire v.3 was created with support from the air quality department of the World Resource Institute Mexico under the direction of Dr. Beatriz Cárdenas.