Project bibliography and reference

Dave Cornman. (2003). Effects of Noise of Wildlife. Nature Sounds Society. http://www.naturesounds.org/conservENW.html

Lane H, Tranel B (1971). “The Lombard sign and the role of hearing in speech”. J Speech Hear Res 14 (4): 677–709. http://jslhr.asha.org/cgi/content/abstract/14/4/677

Louis Hagler, MD. (2005). Summary of Adverse Health Effects of Noise Pollution. World Health Organization Guideline for Community Noise. http://www.noiseoff.org/document/who.summary.pdf

The Journal of Speech and Hearing Disorders, Monograph Supplement 1, 1950 http://www.asha.org/uploadedFiles/publications/archive/Monographs1.pdf

HSE NIHL Statistics. http://www.hse.gov.uk/statistics/causdis/deafness/index.htm

The Journal of Speech and Hearing Disorders, Monograph Supplement 1, 1950 http://www.asha.org/uploadedFiles/publications/archive/Monographs1.pdf

Noise-Induced Hearing Loss, D.E. Wheeler, P.h.D, 1950 http://archotol.jamanetwork.com/article.aspx?articleid=587677

Applied Industrial Hygiene, Noise-Induced Hearing Loss, Volume 4, Issue 7, 1989 http://www.tandfonline.com/doi/abs/10.1080/08828032.1989.10390405

Noise-Induced Hearing Loss, Peter M. Rabinowitz, 2000 http://hannaziegler.tripod.com/ent/varia/rabinowi.pdf

WHO Prevention of Noise Induced Hearing Loss Report, 1997 http://www.who.int/pbd/deafness/en/noise.pdf

HSE NIHL in the workspace http://www.hse.gov.uk/food/noise.htm

It’s a Noisy Planet: Protect their hearing http://www.noisyplanet.nidcd.nih.gov/Pages/Default.aspx

National Institute of Deafness and Other Communication Disorders, NIHL http://www.nidcd.nih.gov/health/hearing/pages/noise.aspx

Deafness Research.co.uk http://www.deafnessresearch.org.uk/content/your-hearing/main-types-of-hearing-loss/noise-induced-hearing-loss/

Twitter Mood Light, Instructables http://www.instructables.com/id/Twitter-Mood-Light-The-Worlds-Mood-in-a-Box/step7/Programming-step-1-SPI-UART/

CC logic, Physical Computing http://www.cc-logic.com/blog/posts/physical-computing-part-1-of-3-getting-wifi-working/

GPS Tracking, Jeremy Blum, 2012 http://www.jeremyblum.com/2012/07/16/tutorial-15-for-arduino-gps-tracking/

Lightweight Low Power Arduino Library http://www.rocketscream.com/blog/2011/07/04/lightweight-low-power-arduino-library/

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Limits and averages

To find the levels of sound in the immediate environment, we have a sound sensor attached to LEDs to pinpoint when you have reached a level of sound in your environment that will become hazardous with extended exposure.

But what determines those levels is a (relative) understanding of how the sound meter relates to decibels.

This is a bit of a problem, because I am incredibly sucky at maths, but should be fairly simple to get a basic understanding of.

143
133
29
61
53
66
2
109
165
22
79
38
33

Omitting the 0 readouts, this is what the sensor gives us over a couple of seconds. The numbers are highly varied and show no clear graduation between low to high sound, perfectly indicative of how sound works, the sudden, incidental and unexpected is much documented in these readings, emphasised to a degree by having the sensor on its highest setting.

Translating these numbers is (at least for silly me) no small task, given that the power for each sound is increased for every three decibels. However, for the sake of time, I’ve left algebra for the most part to the side and worked out what the numbers mean against an android sound sensor with a decibel readout.

270 – 90dB

230 – 85dB

200 – 80 dB

140 – 70dB

80 – 60dB

These numbers are roughly accurate, and allow us to make better sense of what the sensor is giving us.

Considering decibels, we know that  85 decibels is safe for eight hour exposure per day times, and that with 91 decibels we are looking at a safe exposure time of only two hours. Referencing what we know of the three decibel incremental value, for every three added decibels the safe listening time is cut in half. That means 82 decibels has a safe exposure time of 16 hours, and 79 has a safe time of 32hrs. As such, we can work out that a round figure of 80 dB has a safe daily exposure limit without risking premature NIHL.

In addition, if we wanted to find out what the accumulative exposure to a level of sound would be for a twenty four hour period, we can also roughly work it out.

For 80dB, an accumulative reading per minute from the sensor would total 288,000 at the end of a 24 hour period. For 85dB, it would be 331,200, for 90dB, 388,800.

With this information we can read the sensor data, interpret it and tell the LEDs how to respond in a manner that represents the immediate environment.

Mormor Ingrid

I was researching to see what other cool projects people have done using arduino sound sensors, and I couldn’t find that many to be honest, it seems sound isn’t an area that’s too well explored.

I found one project though, called Mormor Ingrid, that was just too creepy not to share!

The website says it combines ‘the classic arts of sculpted busts and sketchbook drawings’ with projection mapping, and adds it’s interactivity through slapping a surface monitored by an arduino sound sensor. The sound input then controls which sketchbook style drawings are projection-mapped onto the bust, and the effect is really freaky. Watch the video for yourself really, see what I mean:

here

I’m not sure if there’s really anything we can draw from this project for inspiration, we’re taking ambient background sound, and this project uses sound as an interaction method, but I was really drawn into the project, so I thought I would share it, and see if maybe we can take any aspects from it to make people equally drawn into ours?