# Measuring noise pollution
> "Noise pollution maps are generally produced using specific software, integrating noise emission and acoustic propagation models, coupled with geospatial data and traffic information. Although these maps are limited by the calculation assumptions and the quality of the input data, they make it possible to assess the broad outlines of a noise distribution in a city and to evaluate the effect of action plans to reduce noise. **However, they generally lack realism, particularly from the point of view of the temporal dynamics of noise. Conversely, noise observatories, consisting of a large number of acoustic sensors, offer a more realistic description of noise environments. However, the limitation of the number of sensors, for technical and cost reasons, does not allow carrying out noise mapping with a sufficient spatial step"** > > Judicaël Picaut, Ayoub Boumchich, Erwan Bocher, Nicolas Fortin, Gwendall Petit and Pierre Aumond - A Smartphone-Based Crowd-Sourced Database for Environmental Noise Assessment - 22 July 2021 International Journal of Environmental Research and Public Health ## How will Silencio change this? Transforming Noise Pollution Monitoring with Silencio Silencio aims to revolutionize noise pollution monitoring by utilizing the power of smartphones, negating the need for numerous fixed environmental sensors. With 90.72% of the world's population owning a smartphone (7.26 billion), pervasive computing holds immense potential for mass participation in environmental initiatives. This approach can raise awareness about environmental concerns, support education, activism, and democracy, and provide unprecedented levels of environmental data. Mobile computing empowers both experts and the general public to collect and analyze environmental data with accuracy and cost-effectiveness that outperforms current noise assessment methods. Smartphones enable a convenient and economical way to gather noise level data in various locations. It is essential to acknowledge that the accuracy of smartphone decibel meters may vary. However, as technology advances and with the collective power of large-scale data, the margin of error can be significantly reduced. Silencio's innovative approach to noise pollution monitoring harnesses the ubiquity of smartphones to enhance our understanding of environmental noise and its impacts, transforming the way we study and address this critical issue.
## Relevant research papers and articles Enda Murphy & Eoin A. King (Silencio's Scientific Advisors) - Testing the accuracy of smartphones and sound level meter applications for measuring environmental noise - Applied Acoustics 3 December 2015 {% file src="/files/8D8FkAMWdiYPCeBrxyZi" %} Judicaël Picaut, Ayoub Boumchich, Erwan Bocher, Nicolas Fortin, Gwendall Petit and Pierre Aumond - A Smartphone-Based Crowd-Sourced Database for Environmental Noise Assessment - 22 July 2021 International Journal of Environmental Research and Public Health {% file src="/files/bT8tiJIvVDcLHHl8Y7da" %} --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://decentra-2.gitbook.io/litepaper-silencio/the-project/measuring-noise-pollution.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.