SvanNET AI is a Svantek proprietary functionality for SvanNET AMS, an online solution that supports multi-point connection with Svantek’s noise and vibration monitoring stations. The AI module enables automatic noise source recognition and classification by using artificial intelligence and machine learning. This AI system employs machine learning algorithms to analyze recorded audio data, accurately categorizing sound sources into 27 distinct classes, such as industrial noise, traffic, and natural sounds. By automating the noise source identification process, SvanNET AI provides precise and real-time noise monitoring, enabling cities to manage urban noise pollution more effectively.
In acoustics, noise sources identification is crucial for effective noise control. By recognizing the source of noise, acoustic engineers can identify where design changes will most effectively improve the overall noise radiation. The main applications are in product design and environmental noise management. In product design, classic analog methods such as beamforming, microphone arrays, or frequency analysis are used. However, in environmental noise, the large amount of data makes it impossible to scale manually. Particularly with traffic noise, acousticians must identify types of vehicles (car, truck), types of trains (cargo, passenger), or aircraft passages, and count them per day or week to evaluate long-term patterns. AI solves this problem by efficiently processing large datasets and providing scalable and accurate noise source identification.
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