KCI Technologies Inc., an engineering, consulting, and construction firm with offices across the United States, has announced the availability of SoundScanNX, a machine learning model designed to support environmental noise classification and help engineers and urban planners assess traffic-related sound impacts.
SoundScanNX is designed to improve the efficiency and consistency of traffic noise impact studies by automating the classification of audio recordings. The AI-based model distinguishes between traffic and non-traffic sounds—such as vehicles, airplanes, voices, and birds—removing the need for manual listening. It identifies the dominant sound in each file, along with peak and average amplitudes. Available on the BRYX Model-as-a-Service (MaaS) cloud platform, SoundScanNX enables users to upload, process, and access results quickly and easily.
Designed for integration into urban planning workflows, SoundScanNX simplifies data management, helping professionals reduce inefficiencies and make informed decisions for sustainable urban development.
For more information, visit kci.com.
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