SONYC - Sounds of New York City

SONYC (Sounds of New York City) is a project that leverages the latest in machine learning technology, big data analysis, and citizen science reporting to more effectively monitor, analyze, and mitigate urban noise pollution. ## Approach The project involves large-scale noise monitoring across New York City using: - Distributed sensor networks - Machine learning for sound classification - Citizen science reporting - Big data analysis ## Goals - Monitor urban noise pollution at city scale - Analyze noise patterns and sources - Develop strategies for noise mitigation - Engage citizens in noise monitoring ## Related Publications - Juan Pablo Bello, Cláudio T. Silva, Oded Nov, R. Luke DuBois, Anish Arora, Justin Salamon, Charles Mydlarz, Harish Doraiswamy. "SONYC: a system for monitoring, analyzing, and mitigating urban noise pollution"