There is a required project, which will come to the forefront after Spring break. The project will count for a considerable proportion of your grade.
The project will have a computing-for-sustainability component at its core.
The computing aspect of the project may involve
- that is adapted from another source,
- implemented from an algorithmic description in a paper, or
- original, as in a mobile application;
- hardware, probably adaptations to an existing robot, device, or component;
- theoretical analysis of some kind, to include statistical analysis of data;
- application and evaluation of existing packages and apps; or
- some combination of these (e.g., programming a robot).
The sustainability domains in which the project can focus are many, presumably situated somewhere in natural, built, and social applications.
The first half of the semester is intended to introduce you to a variety of computational paradigms and sustainability domains. In selecting your project, however, scan ahead to computing paradigms that are addressed later in the semester (e.g., robotics), because these too are viable areas for projects.
If your project will require the purchase of resources (e.g., a robot, a software package), then talk to me early — I have modest funds to support purchase of resources (from NSF Grant 1521672 “Collaborative Research: CompSustNet: Expanding
the Horizons of Computational Sustainability“).
The final deliverable for your project will be a presentation that we will show on the final days of class (December 5 and 7). If (and only if) you are taking the course for graduate credit, then you will also submit a 6 page conference style paper on December 8 (it is possible that we can negotiate a later graduate-paper submission date, but only if the student requests it).
Projects are individual by default, but I will consider proposals for two-person team projects.
- Modify or construct from scratch an NetLogo model for some sustainability application
- to evaluate the likely effects on traffic of variable placed parking hubs and public transit;
- to evaluate the likely effectiveness of a reserve and corridor design based on animal movement
- Apply a machine learning algorithm to novel data sets and evaluate the predictive rules that result,
- using some real sustainability related data set;
- using simulated data from a NetLogo model
- Theoretical analysis of growth rates in ecological footprint, CO2, trash, or energy