Computational Sustainability

I’ve been hearing (and thinking) more and more about the role of machine learning and other data-intensive methods in sustainability.  This is certainly not a new idea — the highly successful expeditions project out of Cornell coined the term (and the website), I believe. Arguably, it’s one of the places in which the case for computer science is easiest to make: These are real problems where systems thinking and computational power, data gathering, and so on is making a difference. Some examples:

  1. Machine learning can find optimal solutions to complex problems that are difficulty for humans alone to model. For example: Golovin et al.  [2011] used machine learning to select patches of land for species conservation that optimize species survival (pdf). There is a nice synergy here as the problem being solved led to advances in machine learning. There must be dozens of similar problems waiting to be tackled.
  2. Big data meets big visualization in a number of projects. Urbmet.org provides data about energy use, population, and so on on a map supporting exploration, comparison, and so on. Data is also made available via an API. In a similar vein, Paulos et al. [2008] visualize air quality using data sense from the tops of taxi cabs and buses (pdf). SourceMap visualizes where things come from on a map, using crowdsourced data. While maps are very powerful, especially when it comes to community action, it would be nice to see this data used in other ways as well. For example, one could imagine that air quality sensors and data of this fidelity could have huge political and medical impacts for those asthma.
  3. Modeling and prediction aren’t just for climate change prediction. One of my favorite alternate examples is UrbanSim, an interdisciplinary project led by Waddell, Borning, and others. As an example of the importance of computation in this project, they have a TOG publication on the use of geometric and behavioral modeling in the “interactive design of urban spaces” [2009].

If you’re looking have ideas along these lines, post a comment or better yet submit to one of the up and coming sustainability conferences (e.g. http://www.ict4s.org). If you’re looking for ideas, there’s a number of past or about to be held conferences you can read up on or attend (e.g. http://www.computational-sustainability.org/compsust12http://www.aaai.org/Conferences/AAAI/2012/aaai12sustainabilitycall.php, or the list at http://www.computational-sustainability.org/).

References:

Daniel Golovin, Andreas Krause, Beth GardnerSarah J. ConverseSteve Morey: Dynamic Resource Allocation in Conservation Planning. AAAI 2011

Eric Paulos, R.J. Honicky, and Ben Hooker, Citizen Science: Enabling Participatory Urbanismin Handbook of Research on Urban Informatics: The Practice and Promise of the Real-Time City. Edited by Marcus Foth, Hershey, PA: Information Science Reference, IGI Global, 2008

Vanegas, Carlos, Daniel Aliaga, Bedrich Beneš, Paul Waddell (2009) Interactive Design of Urban Spaces using Geometrical and Behavioral Modeling. ACM Transactions on Graphics (TOG), also ACM SIGGRAPH Asia, 28(5): 10 pages, 2009. This is accompanied by a video.

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