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The Environmental Noise Directive (END) requires that a five-year updating of noise maps is carried out to check and report on the changes that have occurred during the reference period. The updating process is usually achieved using a standardized approach consisting of collecting and processing information through acoustic models to produce the updated noise maps. This procedure is time consuming and costly, and has a significant impact on the financial statement of the authorities responsible for providing the maps. Furthermore, the END requires that easy-to-read noise maps are made available to the public to provide information on noise levels and the subsequent actions to be undertaken by local and central authorities to reduce noise impacts. In order to update the noise maps more easily and in a more effective way, it is convenient to design an integrated system incorporating real-time noise measurement and signal processing to identify and analyze the noise sources present in the mapping area (e.g., road traffic noise, leisure noise, etc.) as well as to automatically generate and present the corresponding noise maps. This wireless acoustic sensor network design requires transversal knowledge, from accurate hardware design for acoustic sensors to network structure design and management of the information with signal processing to identify the origin of the measured noise and graphical user interface application design to present the results to end users. This book is collection in which several views of methodology and technologies required for the development of an efficient wireless acoustic sensor network from the first stages of its design to the tests conducted during deployment, its final performance, and possible subsequent implications for authorities in terms of the definition of policies. Contributions include several LIFE and H2020 projects aimed at the design and implementation of intelligent acoustic sensor networks with a focus on the publication of good practices for the design and deployment of intelligent networks in other locations.

History of engineering & technology --- motor --- mechanical fault --- detection --- RMS --- sound --- drill --- safety --- pattern --- bearing --- fan --- shaft --- road traffic noise --- noise events --- intermittency ratio --- urban sites classification --- noise monitoring --- real-time noise mapping --- wireless sensor networks --- noise mapping --- noise mitigation --- DYNAMAP project --- outdoors noise --- sound level meter --- digital signal processing --- multirate filters --- dynamic noise maps --- anomalous noise events --- individual impact --- aggregate impact --- WASN --- sensor nodes --- urban and suburban environments --- noise control --- sensor concept --- road traffic noise model --- dynamic model --- acoustics --- smart cities --- deep learning --- long short-term memory --- temporal forecast --- p-u sensor --- p-p sensor --- noise --- Adrienne --- stabilization --- damping --- acoustic impedance --- road surfaces --- low-cost sensors --- networks --- noise sources --- regression analysis --- contribution analysis --- vehicle interior noise --- acoustic sensor design --- acoustic event detection --- map generation --- public information --- END --- CNOSSOS-EU --- motor --- mechanical fault --- detection --- RMS --- sound --- drill --- safety --- pattern --- bearing --- fan --- shaft --- road traffic noise --- noise events --- intermittency ratio --- urban sites classification --- noise monitoring --- real-time noise mapping --- wireless sensor networks --- noise mapping --- noise mitigation --- DYNAMAP project --- outdoors noise --- sound level meter --- digital signal processing --- multirate filters --- dynamic noise maps --- anomalous noise events --- individual impact --- aggregate impact --- WASN --- sensor nodes --- urban and suburban environments --- noise control --- sensor concept --- road traffic noise model --- dynamic model --- acoustics --- smart cities --- deep learning --- long short-term memory --- temporal forecast --- p-u sensor --- p-p sensor --- noise --- Adrienne --- stabilization --- damping --- acoustic impedance --- road surfaces --- low-cost sensors --- networks --- noise sources --- regression analysis --- contribution analysis --- vehicle interior noise --- acoustic sensor design --- acoustic event detection --- map generation --- public information --- END --- CNOSSOS-EU

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

The Environmental Noise Directive (END) requires that a five-year updating of noise maps is carried out to check and report on the changes that have occurred during the reference period. The updating process is usually achieved using a standardized approach consisting of collecting and processing information through acoustic models to produce the updated noise maps. This procedure is time consuming and costly, and has a significant impact on the financial statement of the authorities responsible for providing the maps. Furthermore, the END requires that easy-to-read noise maps are made available to the public to provide information on noise levels and the subsequent actions to be undertaken by local and central authorities to reduce noise impacts. In order to update the noise maps more easily and in a more effective way, it is convenient to design an integrated system incorporating real-time noise measurement and signal processing to identify and analyze the noise sources present in the mapping area (e.g., road traffic noise, leisure noise, etc.) as well as to automatically generate and present the corresponding noise maps. This wireless acoustic sensor network design requires transversal knowledge, from accurate hardware design for acoustic sensors to network structure design and management of the information with signal processing to identify the origin of the measured noise and graphical user interface application design to present the results to end users. This book is collection in which several views of methodology and technologies required for the development of an efficient wireless acoustic sensor network from the first stages of its design to the tests conducted during deployment, its final performance, and possible subsequent implications for authorities in terms of the definition of policies. Contributions include several LIFE and H2020 projects aimed at the design and implementation of intelligent acoustic sensor networks with a focus on the publication of good practices for the design and deployment of intelligent networks in other locations.

motor --- mechanical fault --- detection --- RMS --- sound --- drill --- safety --- pattern --- bearing --- fan --- shaft --- road traffic noise --- noise events --- intermittency ratio --- urban sites classification --- noise monitoring --- real-time noise mapping --- wireless sensor networks --- noise mapping --- noise mitigation --- DYNAMAP project --- outdoors noise --- sound level meter --- digital signal processing --- multirate filters --- dynamic noise maps --- anomalous noise events --- individual impact --- aggregate impact --- WASN --- sensor nodes --- urban and suburban environments --- noise control --- sensor concept --- road traffic noise model --- dynamic model --- acoustics --- smart cities --- deep learning --- long short-term memory --- temporal forecast --- p-u sensor --- p-p sensor --- noise --- Adrienne --- stabilization --- damping --- acoustic impedance --- road surfaces --- low-cost sensors --- networks --- noise sources --- regression analysis --- contribution analysis --- vehicle interior noise --- acoustic sensor design --- acoustic event detection --- map generation --- public information --- END --- CNOSSOS-EU