Argonne is looking for curious, self-directed graduate and undergraduate students who can help us explore the intersection of sensors, scientific computing, cloud computing, image recognition, plant biology, terrestrial ecology, and 3D printers.
Large-scale computer simulations use experimental data as starting points. We are interested in setting up an experimental workflow that would gather data from a field site at Argonne and possibly a local organic community farm. Data would include soil moisture, temperature, images, and possibly CO2. Data collected would be made available to cloud-based HPC computation to process the image data, identify plant types and growth rates, and provide input to weather codes predicting moisture, etc. The project is to sketch out and create this testbed from scratch, including the purchase of image, soil, and weather sensors, setting up appropriate power delivery mechanisms (battery, solar power and energy harvesting methods), working with a 3D printer (Replicator 2X) to build cases, develop software tools chains for collecting and analyzing the data on HPC systems, and finally launching cloud instances and then exploring the performance of HPC simulations running on Argonne cloud platforms and Amazon.com. We may also explore the use of hyperspectral imaging of plants in a test environment. We will assemble a small, diverse team of summer students to participate in the design and then test components of such a testbed.
Key work areas that applicants would be matched to:
1) Assembling and analyzing cloud-computing workflows for image processing, data analysis, soil models, weather prediction, and plant model prediction
Key skills: Linux toolchains, C/C++, HPC and MPI. Will take existing programs and modify for cloud-computing workflow.
2) Finding, exploring specifications, purchasing, and building sensors to be deployed at a local field site.
Key skills: Understanding of imaging, sensors, field data collection. Experience with electronics, steppers, arduinos, etc, a plus.
3) Collecting, understanding, and analyzing environmental data, GIS would be helpful.
Key skills: experience with collecting and exploring environmental data sets
4) Developing a 3D printing configuration so sensors and cameras can be mounted and deployed
Key skills: basic engineering and understanding of 3D models, willingness to learn new tools develop new ideas for sensor / 3D printing.
5) Explore hyperspectral imaging concepts for testing and possible deployment in future projects
Key skills: Understanding of terrestrial ecology, plant biology, willingness to read technical material, test imaging system, and explore data sets
This project will help us develop ideas for a remote sensing with combined HPC simulation and modeling project that we are interested in developing.
Students who are interested in working with us this summer should *immediately* apply here: http://www.dep.anl.gov/catalog/application.html
We would like to have a handful of students beginning in late May/Early June.
While filling out the web form, select:
* Period: Research Aide
* Projects: 229-MCS-1: SENSORS and SENSOR NETWORKS
Argonne Scientists: Pete Beckman, Nicola Ferrier, Rao Kotamarthi, Kate Keahey, Yuki Hamada, Rajesh Sankaran, Kazutomo Yoshii