Utilize este identificador para referenciar este registo:
https://hdl.handle.net/1822/89302
Título: | Georeferenced analysis of urban nightlife and noise based on mobile phone data |
Autor(es): | Elvas, Luís B. Nunes, Miguel Ferreira, Joao C. Francisco, Bruno Afonso, José A. |
Palavras-chave: | Mobile phone sensing Machine learning Clustering algorithms Urban environments Noise patterns |
Data: | 2024 |
Editora: | Multidisciplinary Digital Publishing Institute (MDPI) |
Revista: | Applied Sciences |
Citação: | Elvas, L.B.; Nunes, M.; Ferreira, J.C.; Francisco, B.; Afonso, J.A. Georeferenced Analysis of Urban Nightlife and Noise Based on Mobile Phone Data. Appl. Sci. 2024, 14, 362. https://doi.org/10.3390/ app14010362 |
Resumo(s): | Urban environments are characterized by a complex soundscape that varies across different periods and geographical zones. This paper presents a novel approach for analyzing nocturnal urban noise patterns and identifying distinct zones using mobile phone data. Traditional noise-monitoring methods often require specialized equipment and are limited in scope. Our methodology involves gathering audio recordings from city sensors and localization data from mobile phones placed in urban areas over extended periods with a focus on nighttime, when noise profiles shift significantly. By leveraging machine learning techniques, the developed system processes the audio data to extract noise features indicative of different sound sources and intensities. These features are correlated with geographic location data to create comprehensive city noise maps during nighttime hours. Furthermore, this work employs clustering algorithms to identify distinct noise zones within the urban landscape, characterized by their unique noise signatures, reflecting the mix of anthropogenic and environmental noise sources. Our results demonstrate the effectiveness of using mobile phone data for nocturnal noise analysis and zone identification. The derived noise maps and zones identification provide insights into noise pollution patterns and offer valuable information for policymakers, urban planners, and public health officials to make informed decisions about noise mitigation efforts and urban development. |
Tipo: | Artigo |
URI: | https://hdl.handle.net/1822/89302 |
DOI: | 10.3390/app14010362 |
e-ISSN: | 2076-3417 |
Versão da editora: | https://www.mdpi.com/2076-3417/14/1/362 |
Arbitragem científica: | yes |
Acesso: | Acesso aberto |
Aparece nas coleções: | CMEMS - Artigos em revistas internacionais/Papers in international journals |
Ficheiros deste registo:
Ficheiro | Descrição | Tamanho | Formato | |
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Aplied Sciences - Georeferenced Analysis of Urban Nightlife and Noise Based on Mobile Phone Data.pdf | 7,87 MB | Adobe PDF | Ver/Abrir |
Este trabalho está licenciado sob uma Licença Creative Commons