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Noise Pollution Maps Crowdsourced From Smartphone Data
A new method of creating noise pollution maps uses crowdsourced smartphone data.
Credit: Technology Review
Researchers at the Commonwealth Scientific and Industrial Research Organization (CSIRO) say they have developed an improved method of creating noise pollution maps that uses crowdsourced smartphone data.
Measuring noise pollution in large metropolitan areas on a systematic basis is difficult because noise levels change over relatively short distances and over the course of a day, making the maps time-consuming and costly to create. CSIRO researchers say using smartphone data can simplify this task and make it less expensive.
To ensure that readings are only taken outside, the smartphone uses a global positioning system measurement. The phone then determines whether ambient conversations are taking place, and if so, waits until they are done to avoid a skewed reading. In addition, the phone can use built-in sensors such as the proximity sensor and accelerometer to determine whether it is being held in a person's hand, because readings taken from a bag or pocket are inaccurate. If the smartphone meets all of the researchers' criteria, it records an ambient sound level reading, location, and time, which is transmitted to a central server when the phone is in a Wi-Fi zone.
The central server uses all of the crowdsourced readings to generate a map, which the researchers say is accurate enough to reconstruct data recorded using conventional sound level meters, even when up to 40 percent of the original data points are missing.
From Technology Review
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Abstracts Copyright © 2013 Information Inc., Bethesda, Maryland, USA
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