Application of a novel visual representation method for urban noise source monitoring

Increasing urban mobility has led to a rise in the number of vehicles, resulting in urban noise pollution, which can cause health problems. Conventional methods for noise control can be adopted to reduce noise near the sources. However, this is not cost-effective to reduce overall noise level in the urban area. Therefore, it is preferable to encourage drivers to voluntarily reduce noise by applying methods such as cracking down on road noise sources. To this end, a real-time urban noise source monitoring system is needed, but processing large amounts of data can be difficult. In this study, a novel visual representation method, DoAgram, is applied for urban noise source monitoring. DoAgram can represent the time, frequency, and spatial information of the sound source within a 2D color graph. Therefore, the long-term spatial information of the sound source acquired from the sensor array node can be transmitted as a single image. Also, one can restore spatial information of the source from an image through a decoding process corresponding to the encoding method. One can find that the proposed method can be utilized as a database that can efficiently conduct urban noise source monitoring.