Abstract
Residential noise is a leading cause of neighborhood dissatisfaction but is difficult to quantify for it varies in intensity and spectra over time. We have developed a noise model and data representation techniques that prospective homeowners and renters can use to provide quantitative and qualitative answers to the question, “is this a quiet neighborhood?” Residential noise is modeled as an ambient background punctuated by transient events. The quantitative noise model extracts noise features that are sent as SMS text messages. A device that implements the noise model has been build, calibrated and verified. The qualitative impact of sound is subjectively assessed by providing one-minute audio summaries composed of twenty 3-second sound segments that represent the loudest noise events occurring in a 24 hour sampling period. The usefulness and desirability of the noise pollution monitoring service is confirmed with pre- and post-use surveys.
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Zimmerman, T., Robson, C. (2011). Monitoring Residential Noise for Prospective Home Owners and Renters. In: Lyons, K., Hightower, J., Huang, E.M. (eds) Pervasive Computing. Pervasive 2011. Lecture Notes in Computer Science, vol 6696. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21726-5_3
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DOI: https://doi.org/10.1007/978-3-642-21726-5_3
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