EGU2020-12320, updated on 12 Jun 2020
EGU General Assembly 2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Introducing Sage: Cyberinfrastructure for Sensing at the Edge.

Scott Collis1,2, Pete Beckman1,2, Eugene Kelly3, Charles Catlett2,4, Rajesh Sankaran1,2, Ikay Altintas5, Jim Olds6, Nicola Ferrier2, Seongha Park2, Yongho Kim2, and Michael Papka2
Scott Collis et al.
  • 1Northwestern University, Chicago, USA
  • 2Argonne National Laboratory, Chicago USA
  • 3Colorado State University
  • 4The University of Chicago
  • 5San Diego Supercomputer Center
  • 6George Mason University

There are many networks of sensors for earth system science. Most networks are local or regional in scale (eg mesonets). National weather services maintain networks for meeting stakeholder needs and responsibilities to the WMO Global Observing System. These systems are comprised of single task rigid sensors generally attached to logger systems. Sage [1] is a project which will deliver a cyberinfrastructure network allowing multi-tenant, multi-tasked sensor packages. In addition to traditional meteorological instrumentation and advanced static and pan-tilt-zoom cameras Sage nodes have powerful compute infrastructure allowing machine learning based phenomenology detection at the edge. This allows science question-based reconfiguration of sensor operation. A well described Application Programming Interface (API) will allow new algorithms to be pushed to the edge and new sensor packages to be added including those that have complex configuration spaces like LIDAR and Radar. This presentation will introduce Sage and present early example results such as using cameras for cloud classification, inundation caused by heavy rainfall and early wildfire ignition detection. 



How to cite: Collis, S., Beckman, P., Kelly, E., Catlett, C., Sankaran, R., Altintas, I., Olds, J., Ferrier, N., Park, S., Kim, Y., and Papka, M.: Introducing Sage: Cyberinfrastructure for Sensing at the Edge., EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-12320,, 2020