SONYC (Sounds of New York City) is an NSF-funded research project housed at New York University's Center for Urban Science and Progress (CUSP) with collaborators across NYU as well as at the Ohio State University. Formed in 2013, the SONYC team studies the acquisition, analysis, classification, and visualization of urban noise. The project uses a combination of fixed sensors, computer analysis (using a technique called machine learning), and citizen scientists to help  better understand noise pollution. The objective of SONYC is to provide New York City, and by extension cities across the country and around the world, with a raft of tools and techniques to identify, classify, and map different kinds of noise.

This curriculum, developed by NYU students in collaboration with the SONYC team and the Center for K-12 STEM Education at NYU's Tandon School of Engineering, is an indispensable part of the SONYC toolkit - by getting school-age children engaged on noise, we can help empower a new generation of advocates for a quieter, less stressful city. Along the way, students learn important (and NGSS-aligned) skills around the physics of sound, the electronics involved in measuring it, the engineering of recording it, and the computer science of manipulating it inside the computer.

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