Noise Mapping

Noise mapping aims to create visual representations of sound levels across space and time, primarily to mitigate noise pollution and improve urban planning. Current research focuses on developing dynamic noise maps that capture transient noise sources using IoT sensors and machine learning algorithms like generative adversarial networks (GANs) and diffusion models to overcome limitations of traditional methods. These advancements enable faster, more accurate noise assessments, particularly for traffic noise, and facilitate integration into urban design tools, ultimately improving the efficiency and effectiveness of noise control strategies.