LAUSR

Abstract State of the art environmental noise monitoring systems are based on digital signal processing. In general, they measure and store environmental noise levels, but also perform computation, spectral filtering, narrowband spectral analysis, evaluation of statistical indices, wave recordings, detection of noise events based on thresholds, and other similar tasks. Advances in processing power enabled application of smartphones for environmental noise measurements as well as the development of more sophisticated equipment capable of complex multichannel digital signal processing in real time. This paper describes the development of three new measurement methods and their application in environmental noise monitoring system: 1) an automatic exclusion of uncorrelated noise events from measurements, 2) an automatic identification of the dominant noise source direction and 3) an automatic classification of the observed noise event. The implementation of these three options can reduce the need for human resources, ensuring lower costs and more reliable measurement results. Immision directivity is defined to determine the dominance of the noise source compared to the background noise. The suggested technical solution and new procedure was practically applied as a part of autonomous measurement and noise source classification system in the ambient noise investigation in a residential area.