Abstract
Large-scale noise pollution sensor networks consist of hundreds of spatially distributed microphones that measure environmental noise. These networks provide historical and real-time environmental data to citizens and decision makers and are therefore a key technology to steer environmental policy. However, the high cost of certified environmental microphone sensors render large-scale environmental networks prohibitively expensive. Several environmental network projects have started using off-the-shelf low-cost microphone sensors to reduce their costs, but these sensors have higher failure rates and produce lower quality data. To offset this disadvantage, we developed a low-cost noise sensor that actively checks its condition and indirectly the integrity of the data it produces. The main design concept is to embed a 13 mm speaker in the noise sensor casing and, by regularly scheduling a frequency sweep, estimate the evolution of the microphone's frequency response over time. This paper presents our noise sensor's hardware and software design together with the results of a test deployment in a large-scale environmental network in Belgium. Our middle-range-value sensor (around €50) effectively detected all experienced malfunctions, in laboratory tests and outdoor deployments, with a few false positives. Future improvements could further lower the cost of our sensor below €10.
Highlights
Urban noise pollution sensor networks consist of spatially distributed microphones that measure environmental noise
While these results show that Q is sensitive to failure conditions, the sensitivity is remarkably different between MC and MK sensors
All sensors equipped with the middle-range value Knowles microphone capsule (MK type) were able to successfully detect and report all of their failures while deployed outdoors for several months
Summary
Urban noise pollution sensor networks consist of spatially distributed microphones that measure environmental noise. Typical noise measurements sensors (microphones + outdoor casings) cost from hundreds to thousands of euros, rendering large-scale network deployments financially prohibitive To counteract this limitation, high-cost noise sensors have been replaced in some network deployments with low-cost, off-the-shelf microphones. Self-tests can be used as a network maintenance tool that helps in the identification of defective sensors needing replacement This in turn will increase the overall quality and accuracy of the noise measurement network by removing malfunctioning nodes and the contaminated data they generate. Passive techniques rely on the analysis of the data collected by the sensor and in some cases its neighbor sensors They can be performed offline as a post-processing task or online in near real time. Another patented technique for mechanical deflection sensors uses a movable part to slightly deflect the sensor and measure its response [5]
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