On the Use of Linear Regression for the Assessment of Stability in Noise Monitoring Networks: A Practical Example

Invited paper

Kostas Sotirakopoulos

National Physical Laboratory

Wednesday 3 june, 2015, 11:20 - 11:40

0.8 Rome (118)

As modern cities grow and urban environments become increasingly complex the need for creation of robust systems which can be used for monitoring various environmental parameters including noise becomes more and more profound. Such systems enable the extraction of useful information about a city’s environment which can then be used to inform the public. Technological advances have made possible the creation of systems using cheap components like mems microphones. However the nature of their components as well as the network’s installation makes them vulnerable to a great number of destructive factors like extreme weather conditions and aging of their elements. Ensuring good operation is vital for the reliability of the recorded data. Hence the creation of monitoring systems aiming to evaluate data quality is crucial. Over the years various methods have been developed towards achieving this goal. In this paper we propose the use of statistical parameters, spatial and temporal correlations between closely located receptors as well as the possible utilization of available information on events that can trigger significant sound levels for the evaluation of a network’s stability in terms of sensitivity of the receptors and the identification of noise patterns which can indicate data degradation due to system failures or significant drifts from calibration. The proposed methods were developed based on datasets recorded at Katendrecht, Rotterdam between December 2013 and January 2014.

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