Since my last post on my Final Year Project, I have spent a lot of time investigating the feasibility of the different aspects of the piece.
Research & Context
To continue from my previous post, my plan is to build an object that contradicts technology’s ongoing ability to disengage people from the natural world while simultaneously causing its destruction, ergo to use technology to reconnect the individual with the natural world.
This idea has been bolstered recently by some research I have been doing into other living media projects. In the video about the Babbage Cabbage (a living media piece), the narrator cites KL Thomson’s claim that people are able to connect more strongly to living things. Thus, by using living plants in my piece, I plan to create a stronger will in the user/participant to interact with the piece and engage better with the issues the object raises.
I have also been in contact Diego Maranan, an artist, researcher, and educator, and the Biomodd projects that create symbiotic relationships between technology and living organisms which Diego has been involved with. The issues raised in these projects are quite profound, particularly on an ethical level. That is, is it ethical to leave the health of a living organism solely up to the health of a man-made machine, to the extent that if one dies, the other inevitably follows suit?
This is a question that I believe is taken to a higher level with the project I plan to build. Whereas the Biomodd projects are using technology to keep the organisms alive, my piece aims to use technology to perhaps cause harm to the organisms under its control depending on the data being fed into the system. I would argue however that it is therefore taking the responsibility away from the technology and placing it back into the hands of the individual, because it is only by the individual ignoring the detrimental affects that the technology is causing that the plants will die.
This captures nicely and echoes the issues that are happening on a global scale with climate change and environmental destruction. The technology is causing detrimental effects to the world, but my dissertation research suggests that by involving themselves in the process, individuals can counteract this affect through their own intelligent, sustainable, decentralised use of technology.
Before, I discussed my plan to build an Earth-map-shaped hydroponic system, where the different continents held their own organisms and would reflect the health of the region that they are in.
However, having investigated this plan further, I have found that the data simply doesn’t exist that fit my needs. There were two options that I was considering;
- To listen for news headlines related to climate change or other environmental issues, such that a headline such as “European Carbon Emissions Plummet” would have a positive affect on my Europe, while a headline such as “Amazon Rainforest Sees Record Deforestation” would cause an extreme negative affect on my South America.
- To use global & regional climate-/environment-related data (such as temperature, pollution, etc.) to paint a real-time picture of the health of different regions and thus control the health of the plants with this data.
In reality however these plans both proved to have their issues.
Firstly, the ability to gain useful insight from news headlines alone was much more than a challenge. To begin with, creating a steady and useful stream of news headlines was difficult. Only a handful of news publications have API or RSS accessible feeds of their published articles. This issue could be overcome however through the use of the Twitter Streaming API, which I experimented with. However, this still proved difficult, as even with 200 environment and news publication accounts followed, the challenge remained to sort through what was useful and what was junk.
From the 200 accounts I was following, I was receiving anywhere from 0-15 tweets a minute, but the vast majority of these were unrelated to the environment. I therefore set out to create a list of keywords to filter by, such as “Climate Change,” “Environment,” and “pollution”. This didn’t help much however, as the crucial problem still needed to be solved: analysing the tweet for content programatically.
Even filtered by keywords, and following only a select number of accounts, the majority of tweets that got through were still useless and unrelated. For example, while trying to listen for tweets about the Amazon rainforest, I instead received nothing but tweets about the company Amazon.
Without context analysis the tweets were near enough useless, and even if I was able to somehow gain context and sort tweets into “good” headlines and “bad” headlines for my system, there was still the issue of identifying locations, and when the majority of tweets read something along the line of “water pollution levels rise: t.co/somelink” with no mention of a place in the tweet, because most publications are American- or US State-centric, it seemed like too much effort to pursue this option.
Secondly, using global data was a little simpler, but not entirely broad or insightful. There are a number of APIs for historical weather and climate data, but only a handful related to realtime (live) data, and all but one of these I found were either costly or related only to weather (i.e. “Is it cloudy?” – not very useful).
One, however, has proved quite useful. BreezoMeter provide hourly updates for air quality and pollution data for the majority of the world. Although only one type of data, and not directly climate-change related, the US Global Change Research Program lists greenhouse gases and atmospheric carbon dioxide as two key indicators of climate change. Additionally, a report by the Air Quality Expert Group (AQEG) on behalf of Defra highlighted the negative impacts that all forms of air pollutants, from aerosols to carbon particulates have on the environment and climate.
BreezoMeter provides information about the most harmful pollutant currently in the air (as in, if the affects of carbon particulates are going to be more severe than current carbon dioxide levels, then measures of particulates are reported) Therefore from this data I believe it is possible to assess the current (hourly) state of the climate. And considering these emissions are for a good part created directly by technology or in pursuit of innovation, I am comfortable in arguing that it is a good metric to follow.
However, no single point changes much from an hour-to-hour basis. In the image above, each “pixel” is one longitude by one latitude area (blue are either ocean or have no data available), and over the course of a day I have not seen any significant changes to any one pixel. Therefore I have decided to abandon my idea for the Earth-map-shaped piece and instead focus globally. Therefore I can focus on the average health of the entire planet and not just specific regions to control the piece.
I believe this is arguably a better approach, highlighting the globalisation of the issue and its causes (technology, industry) and linking the health of the whole planet together rather than isolating different regions, which in the real world environment is definitely not the case.
I am therefore redesigning the piece in my mind as I write this. I am at this point inspired heavily by the Biomodd projects and their aesthetic (not just practical) emphasis on the interconnectivity between technology and nature. Another post should follow in the future about my design choices in much more detail!