





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 28 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.
Noise Sources Identification
Accurately identifies and categorizes noise sources in real-time.
Audio Events Classification
Classifies specific audio events using event triggers and real-time analysis.
Automatic Reporting
Generates detailed reports with prediction confidence and data visualization.
Accurately identifies and categorizes noise sources in real-time.
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Classifies specific audio events using event triggers and real-time analysis.
Read more
Generates detailed reports with prediction confidence and data visualization.
Read more
Environmental Noise
SvanNET AI can classify sound sources into 28 distinct categories
The main application of SvanNET AI is in environmental noise management, particularly for urban noise and traffic. It is used to monitor, identify, and categorize various noise sources in cities, helping authorities and planners implement targeted noise reduction measures. By providing accurate and real-time data on noise pollution, SvanNET AI supports the development of effective strategies to mitigate the adverse effects of urban noise on public health and improve overall urban living conditions.
Read moreWatch a new handy video about the SvanNET AI functionality that can be used for automatic noise source classification.
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SvanNET AI
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 28 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. |