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Avoid the Hustle

epidemiology

Category: Essay Writing

Sound level meter apps on cell phones are a good example of the miniaturization of sensors and the increasing power of cell phones. Many such sensors and applications are free or very cheap, so can quickly become a widespread source of environmental data. The major concern, however, is accuracy (how close to the true noise value?) and precision (how well do the same measurements match each other?). A sample comparison on the last page made by the CDC shows that phone noise apps can be off by 10 to 15 dB in some cases, which is quite a lot, while some apps appear to be quite accurate.
For this assignment, due next week, please download one of the recommended sound level phone apps shown below. If you do not have a cell phone, see if you can borrow one from someone. If not, please check with me.
Android: Sound Meter by Smart Tools:

http://www.appbrain.com/app/sound-meter/kr.sira.sound

iPhones: Decibel 10th:

https://itunes.apple.com/us/app/decibel-10th/id448155923?mt=8

SPL:

https://itunes.apple.com/us/app/spl-meter/id309206756?mt=8

With this app, perform the following:
1. Measure or estimate average noise levels (in decibels) in the locations you spend the most time, including the waking activity areas of your residence, bedroom area at night, travel, and work/school.
Take 10 readings. This can be by eye or saved by the phone. Calculate the standard deviation of these readings. If readings are highly variable, i.e., a standard deviation of more than 5 db, take an additional 10 readings.
2. Estimate the average time you spend in each of these areas.
You can do this by thinking about a typical day. Ignore weekends.
3. Calculate a time weighted 24-hour noise exposure.
(E.g., 2 hrs @ 70 dB plus 8 hours @ 60 db plus 14 hours at 50 dB = ((2*70)+(8*60)+(14*50))/24 hours = 55 dB).
4. Comment on the ease of use of the app.
For example, were the numbers easily readable? Did they change slowly enough to estimate an average by eye? Could you save data? Were there any features to help interpret the readings?
5. Comment on how well the app appears to perform.
For example, a) For steady sounding noise conditions, were the numbers also steady? b) Did the numbers increase and decrease with what you perceive to be louder or quieter noise levels? c) Were there certain locations or types of noise that seem too high or too low compared to your perception of loudness? For example, lecture slide #8 lists
For good sleep < 30dB
Whisper 35
Quiet classroom or office <45
Conversation 55
City traffic 65
Motorcycle or lawn mower 95
Did these appear to agree with what you measured?
6. Other Aspects of Measurements: Did you notice any noise sources that were annoyingly loud? How loud were they? Were there any sources that were annoying but not loud? What were they and how loud were they?

7. Was your bedroom quiet enough and consistently quiet enough for good sleeping? E.g., < 35 dB or else the quietist your meter read by at least 5 dB? If not, was there a specific source of noise? How loud was this source?

Please note that the above tasks and evaluations are somewhat subjective. There are no “right” ways to evaluate a sensor without a reference method to compare against.