Lungs

Team Name: 
Saint-Simon

Lungs is a Posthuman, Web of Things IPhone App and Digital Art Installation. The work expresses climate change stress by transposing human mood onto Adelaide Street Trees. Music and visual indicators are used to demonstrate mood state. The project aims to challenge anthropocentrism, encourage climate change action and provide musicians with opportunities to syndicate context aware, nonlinear compositions.

Mood Model

According to Thayer, human mood is “a background feeling that persists over time” and can be analysed on two spectrums, energy to tiredness and tension to calmness. These spectrums are affected by circadian rhythms, health and other stressors. Lungs applies Thayer mood spectrums to comparable factors in trees.

Energy is calculated from transpiration and vigour. Transpiration in trees typically increases in the morning and reduces in the afternoon. This process cycles approximately each 24 hour period and is a circadian rhythm. Transpiration is driven by dryness of the atmosphere and the current level can be determined from the current vapour pressure deficit. VPD is offset by the vigour or health of the tree to form the energy value.

Tension is calculated from monthly deviations of the tas variable from the CSIRO Mk 3.6 GCM. Baseline deviations are calculated from the temperatures of Adelaide and a native locale of each tree species for the historical period of 1986 to 2005. Adelaide’s current temperature and four projected temperatures from the rcp85 scenario are weight averaged against the baseline of the target species and any change of more than 1 degree increases the tension value.

To simplify use, calculated energy and tension values are combined to select the closest Mirex Cluster. These clusters are mood classifications for music.

Cluster 1: Excited
Cluster 2: Joyful
Cluster 3: Sad
Cluster 4: Funny
Cluster 5: Aggressive

Mood Expression

Music is autonomously selected by the mood of nearby trees and the user can only change the selection by physically moving to an alternative location. Not unlike a conventional radio station, however the condition shifts the power relationship from the user towards the environment. Music is selected from a centrally hosted album.

The visualisation is based on stylised orphic cubism and is generated in realtime from the mood and decibel levels of the currently playing song.

Tree Data

Tree locations, vigour and species are obtained from the ACC Street Trees Dataset.

Weather Actuator

Both spectrums need near real time weather observations. Temperature and Relative Humidity are provided by a MQTT beacon service. The service accesses observations provided on the BOM FTP site and pushes current tas and rh values to each client App. The beacon makes use of data generated at the Kent Town Station.

Tree Species Data

A native locale of each tree species is needed to calculate the tas deviations in the tension spectrum. However, I was unable to locate machine readable lists of all species represented in the trees dataset. To resolve this issue, I built a Wikipedia Scraper. The Scraper retrieves tree species pages and searches for countries of origin using textual proximity to key phrase synonyms. ie: “first recorded”, “native to”, “natural distribution in”, etc

Commercialisation

For 2016 Adelaide Fringe Festival or Berlin Carnival, I’m interested in working with musicians local to those cities in developing an artist “sampler” album for this project. The App would present a unique way to experience the city for the many people travelling to those events.

References

[1] "Posthuman" in the Philosophical Posthumanism understanding as defined by people like Carey Wolfe
[2] Web of Things: http://www.w3.org/2015/05/wot-framework.pdf
[3] Robert E Thayer, the late psychology professor and Author of The Origin of Everyday Moods: Managing Energy, Tension, and Stress
[4] Mirex Clusters: http://www.jaist.ac.jp/~kshirai/papers/dang09a.pdf

Datasets Used: 
CSIRO-Mk3-6-0 Climate Model: https://data.csiro.au/dap/SupportingAttachment?collectionId=13783&fileId=832 Adelaide Street Trees: https://data.sa.gov.au/data/dataset/street-trees BOM Realtime Weather Observations (IDS60920.xml): http://data.gov.au/dataset/precis-forecast-south-australia Scraped various Tree Species Pages: https://www.wikipedia.org

Local Event Location: