KCI Launches SoundScanNX

KCI makes available SoundScanNX, an advanced machine learning model that streamlines environmental noise classification, impacting how engineers and urban planners assess traffic sounds.

SoundScanNX, for use in traffic noise impact studies, is an AI-driven model that simplifies classification of audio recordings, automatically distinguishing between traffic and non-traffic noise, such as cars, motorcycles, trucks, airplanes, birds and voices. By eliminating a need for human listening, SoundScanNX streamlines traffic studies by automatically analyzing audio recordings, identifying the dominant sound in each file along with its peak and average amplitudes.

SoundScanNX is available on the BRYX Model-as-a-Service (MaaS) cloud platform, allowing users to upload their audio files, process them, and view and download their results.

“Accurate and consistent noise classification is essential for shaping healthier, more livable communities. SoundScanNX empowers AEC professionals with the insights they need to design and recommend smarter urban spaces while optimizing resources and ensuring regulatory compliance," says Jeanne Ruthloff, Technology & Innovation Sector president.

Designed for integration into existing urban planning workflows, SoundScanNX eliminates data sorting. This advancement helps streamline workflows, reduce inefficiencies, and support data-driven decisions for sustainable urban development. To get started with a free trial of the SoundScanNX model, visit gobryx.com.

Sources: Press materials received from the company and additional information gleaned from the company’s website.