20.500.12556/RUL-143938 Automated identification and assessment of environmental noise sources Noise pollution is one of the major health risks in urban life. The approach to measurement and identification of noise sources needs to be improved and enhanced to reduce high costs. Long measurement times and the need for expensive equipment and trained personnel must be automated. Simplifying the identification of main noise sources and excluding residual and background noise allows more effective measures. By spatially filtering the acoustic scene and combining unsupervised learning with psychoacoustic features, this paper presents a prototype system capable of automated calculation of the contribution of individual noise sources to the total noise level. Pilot measurements were performed at three different locations in the city of Ljubljana, Slovenia. Equivalent sound pressure levels obtained with the device were compared to the results obtained by manually marking individual parts of each of the three measurements. The proposed approach correctly identified the main noise sources in the vicinity of the measurement points. immission directivity spatial filtering noise source classification environmental noise microphone arrays automatization of measurements usmerjenost imisije prostorsko filtriranje klasifikacija virov hrupa hrup v okolju mikrofonske antene avtomatizacija meritev true false true Angleški jezik Slovenski jezik Članek v reviji 2023-01-20 14:55:38 2023-01-20 14:55:43 2023-09-02 03:46:32 0000-00-00 00:00:00 2023 0 0 Objavljen je popravek tega članka (gl. datoteko Priloga – Erratum): Heliyon, 2023, Vol. 9, iss. 3, art. e13981, DOI: https://doi.org/10.1016/j.heliyon.2023.e13981. 17 str. iss. 1, art. e12846 Vol. 9 Jan. 2023 0000-00-00 Zaloznikova Objavljeno NiDoloceno 0000-00-00 0000-00-00 0000-00-00 534 2405-8440 10.1016/j.heliyon.2023.e12846 137356803 Murovec_...-Automated_identification_and_assessment_of_environmental_noise_sources.pdf Murovec_...-Automated_identification_and_assessment_of_environmental_noise_sources.pdf 1 5947C8E8E3DAFCA06508EA0056824E51 bd46b9decde3e71446ce81d3a74e9497f36414457d2b579617753548fb4a901a 38fb1343-98ca-11ed-9c94-00155dcfd717 https://repozitorij.uni-lj.si/Dokument.php?lang=slv&id=165999 1-s2.0-S240584402301188X-main.pdf 1-s2.0-S240584402301188X-main.pdf Erratum Erratum 1 0506A7E69BEA1D5D0BBA5316D1136890 018a820a902dd1a4110b0c1aa0b416ae2a43186b93116c987c7e0c9c6b0dc6c0 522dd51a-48a1-11ee-af86-0050569b8976 https://repozitorij.uni-lj.si/Dokument.php?lang=slv&id=173314 https://www.sciencedirect.com/science/article/pii/S2405844023000531 1 e1cc0ce4-98c9-11ed-9c94-00155dcfd717 https://repozitorij.uni-lj.si/Dokument.php?lang=slv&id=165998 Fakulteta za strojništvo 0 0 0