Twitter

We (Lizzie) managed a huge feat in accomplishing pushing the data of the Arduino and sound sensor to Twitter. This created an additional layer of interactivity and in encouraging the individual to engage in monitoring the sound environment that they experience.

You can view the feed for the data we collected during setup, test and presentation here.

Post Presentation

Despite losing an LED during the presentation set up overall it went really well. (I said environment way too much)

The questions that we were asked were both informative of our product and presenting, concerning both the technical elements that we had dismissed in our development as well as queries pushing the importance of sound and how people would react in an environment that increases focus on the awareness of the sound environment.

One question that was slightly out of field was a query of volumes by motorways. Naturally this is in an area of unknown or unspecified factors, sound insulation, building materials, sheltering, which changes the reception of sound itself. Being aware of the environment in relation to sound also means being aware of it in terms of location and what that area comprises of. Different materials provide different levels of insulation against the elements, sound inclusive.
The first step to bettering the environment you’re in may start with being aware of sound, but continues with the investigation and maturing of the environment through your influence.

That said the decibel values for living by a motorway, unabsorbed by plantlife, barriers or otherwise, would be very high, and well beyond recommendable exposure levels for a few hours.

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/

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.

A mess of wires

This is the current state of our set up – a mixture of sensor, wifly, wires (more organised than they look) and LEDs.

Our project has developed through the limitations and freedoms of our discoveries, between finding ways and incompatibilities with different parts of kit and thinking new ways to do things to improve upon the original concept. We’d like to give the final result a more immediate response to the data it is discovering, and we’ve removed the idea of using GPS due to the want to completely avoid any privacy concerns. Thus, we’ve rearranged our ideas for output and as such expect that the hat-scarf-bear will have three “claws” on one paw comprised of three LEDs, two green – for good and manageable levels of sound – and one red, for determining and warning of dangerous levels of sound or noise in the immediate area.
We’re also intrigued by the idea of linking the bear up to a twitter feed, so that we can not only share/broadcast this information but encourage other people to find ways of using the data, as well as ourselves. The purpose of the decibear is to raise awareness after all, and while the awareness in concept may be unique to the individual wearer, online it can become the awareness of many more, even if in a secondary state.

Suddenly Sound

I figured out what was causing us so much trouble with the sound sensor – we’d been pinning it up wrongly the whole time! Where in the diagram that we had been following it showed us to connect it in a certain way, I found that exchanging the ground and sensor made it work, whereas previously we were connecting to the sensor but it wasn’t responding to loud sounds.

Similarly, we later discovered what the problem with the Wifly shield was as well – that it wasn’t compatible with my Mega 2560 Arduino board. Solving the issue turned out to be rather simple, a case of wiring four pins of the shield to a different part of the board.

20130219_125734

Proposal

In exploring the space that is around us it is important to be not only aware of the potential that the space holds, but also to gain awareness of what is already within the space. In this case our attention is drawn to the environment created by sound, to later be developed in the terms of how sound can affect us as human beings.

The project concept works on three key points, the first being the technical elements – sensors to monitor sound levels and send/store the data. The second is mapping out the data in relation to the areas traversed, to establish locations of higher noise pollution and to identify more preferable areas of quieter sound levels. The final key point is what we hope to finish on with the project, which is the element of gamification/personal mental health. To explore our final key element we want to create a dialogue between the technology and the wearer – as one would be allowed only so much exposure to certain radiations, the wearer should limit their exposure to certain levels of environmental noise pollution. The gamification elements constructed within this concept are still in development and conceptual stages.

To achieve this concept we intend to utilise the Lilypad Arduino, which is something that neither of us has touched on or dabbled with before, which is quite exciting. The Lilypad will enable us to attach the technology to clothing and materials, allowing it to go out into the field and achieve the project we are setting out to do.

What is interesting to consider is how we are intending to make both a piece of clothing and the immaterial “travelling” – the path which is walked and has been traversed in both present and past tenses – blogjects. Where the clothing becomes a blogject of data moving through the space, the route taken becomes a blogject in its own right through the clothing. In such a way the clothing is given a sense of deterministic agency, discovering in its own right statuses of sound and noise pollution around it and the wearer.