IN018
Computing at the Edge for Earth Science

Session ID#: 80820

Session Description:
Geophysical instrumentation is becoming increasingly complex and configurable. Instrumentation that either samples a region of space or performs on-board data reduction (ie signal processing) can fail to collect the data required to answer science questions if left in a “catch-all” mode. Edge computing pushes analysis and control from centralized systems to or next to the instrument itself (where full bandwidth is available, and dedicated hardware reduces control latency). This allows scene characterization (through machine learning and other techniques) and adaptive sampling and processing. Our community could benefit from exploring how to integrate new lightweight computing hardware and new data analysis algorithms into distributed instrumentation. This cross-disciplinary session solicits submissions that demonstrate applications of edge computing to geophysical sensors or network of sensors both fixed and mobile.
Index Terms:

0520 Data analysis: algorithms and implementation [COMPUTATIONAL GEOPHYSICS]
0535 Hardware solutions [COMPUTATIONAL GEOPHYSICS]
0555 Neural networks, fuzzy logic, machine learning [COMPUTATIONAL GEOPHYSICS]
0594 Instruments and techniques [COMPUTATIONAL GEOPHYSICS]

Primary Convener:  Scott M Collis, Argonne National Laboratory, Argonne, IL, United States
Conveners:  Aaron Ian Packman, Northwestern Univeristy, Evanston, IL, United States, Peter H Beckman, Argonne National Laboratory, Argonne, IL, United States and Vivien Anne Rivera, Northwestern University, Evanston, IL, United States
Primary Liaison:  Scott M Collis, Argonne National Laboratory, Argonne, IL, United States
 
Software-Defined Sensors: using Edge Computing to Revolutionize Sensing (Invited) (504287)
Charles E Catlett1, Peter H Beckman1, Rajesh Sankaran1, Nicola J. Ferrier1, Seongha Park2 and Yongho Kim2, (1)Argonne National Laboratory, Argonne, IL, United States, (2)Argonne National Laboratory, Argonne, United States
 
Dynamic load balancing using hypergraph partitioning for parallel geospatial cellular automata models (532255)
Wei Xia, China University of Geosciences, Wuhan, Hubei, China
 
SpaceCube 3.0: A Space Edge Computing Node for Future Science Missions (546950)
Gary Crum1, James P MacKinnon1, Alessandro Geist1, Christopher M Wilson1, Elizabeth Middleton2 and Patrice G Cappelaere3, (1)NASA Goddard Space Flight Center, Greenbelt, MD, United States, (2)NASA Goddard Space Flight Cen., Greenbelt, MD, United States, (3)ASRC Federal Technical Services, Ellicott City, MD, United States
 
Autonomous Magnetic Maps Generation for Monitoring using Small and Autonomous Aerial Robots (550353)
Jaco DIAS Domingues1, Hector Azpurua1, Rosa Elvira Correa Pabón2, Gustavo Medeiros Freitas3 and Gustavo Pessin1, (1)ITV Instituto Tecnológico Vale, Robotics Lab, Ouro Preto, Brazil, (2)ITV Instituto Tecnológico Vale, Robotics Lab, Ouro Petro, Brazil, (3)Universidade Federal de Minas Gerais UFMG, Belo Horizonte, Brazil
See more of: Earth and Space Science Informatics
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