Detection and localization of impulsive sound events for environmental noise assessment

2017 ◽  
Vol 141 (5) ◽  
pp. 3886-3886 ◽  
Author(s):  
Peter W. Wessels ◽  
Jeroen v. Sande ◽  
Frits Van der Eerden
2009 ◽  
pp. 217-217-11
Author(s):  
JW McGaughey ◽  
EE Dennison ◽  
SP Ying

2016 ◽  
Vol 139 (4) ◽  
pp. 2070-2070
Author(s):  
Frank Van den Berg ◽  
Frits Van der Eerden

Nucleus ◽  
2017 ◽  
Vol 14 (1) ◽  
pp. 5-16
Author(s):  
Cleomacio Miguel da Silva ◽  
Cleiton Miguel da Silva ◽  
Geraldo Jorge Barbosa de Moura

Author(s):  
Eoin A. King ◽  
Akin Tatoglu ◽  
Robert D. Celmer

This paper presents results of an ongoing project which aims to develop a purpose-built platform for using smart phones as alternative to sound level meters for citizen-science based environment noise assessment. In order to manage and control environmental noise effectively, the extent of the problem must first be quantified. Across the world, strategic noise maps are used to assess the impact of environmental noise in cities. Traditionally, these maps are developed using predictive techniques, but some authors have advocated the use of noise measurements to develop more reliable and robust noise maps. If adopted correctly, smartphones have the capability to revolutionize the manner in which environmental noise assessments are performed. The development of smartphone technology, and its impact on environmental noise studies, has recently begun to receive attention in the academic literature. Recent research has assessed the capability of existing smartphone applications (apps) to be utilized as an alternative low-cost solution to traditional noise monitoring. Results show that the accuracy of current noise measurement apps varies widely relative to pre-specified reference levels. The high degree of measurement variability associated with such apps renders their robustness questionable in their current state. Further work is required to assess how smartphones with mobile apps may be used in the field and what limitations may be associated with their use. To over come the above issues, this project is developing a platform specifically for citizen science noise assessment. The platform consists of a smartphone app that acquires a sound signal and transfers the data to a server via a web based API for post processing purposes. This then returns key information to the user, as well as logging the data for use in a massive noise mapping study. The structure of the proposed platform maintains a clear separation between client (phone) and server. This approach will allow implementation of future open source client side apps for both Android and iOS operating systems.


2014 ◽  
Vol 482-483 ◽  
pp. 400-410 ◽  
Author(s):  
Stylianos Kephalopoulos ◽  
Marco Paviotti ◽  
Fabienne Anfosso-Lédée ◽  
Dirk Van Maercke ◽  
Simon Shilton ◽  
...  

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