OD34D:
New Information Systems Tools for Implementing Autonomous Multisource, Multipoint Observing Systems II Posters

Session ID#: 84492

Session Description:
An exciting array of new and emerging space-borne and in-situ observing technologies are coming to the ocean science community, including, inter alia, autonomous surface and underwater vehicles, ocean observing CubeSats, and next-generation large satellite missions. The true power behind the proliferation of these new platforms and tools for remote and in-situ ocean measurements lies in integrating them into observing systems that can predict and then act to observe transient or temporary phenomena, and that are flexible and autonomous in their control and data acquisition and processing. This session aims to: 1. Identify new methods and techniques for autonomously processing communicating, and acting on information from observing systems with different instruments at different vantage points, e.g., combinations of traditional and small-satellite observations, UAVs/AUVs, moored instrumentation, etc. 2. Facilitate cross-disciplinary discussion and collaboration between practitioners and technologists in the ocean science community, and 3. Identify the gaps and needs in the ocean science community for advanced information systems technologies to advance flexible, autonomous observing systems. The session chairs welcome any submission related to technology development or needs in areas such as machine learning and other advanced processing techniques, real- or near real-time processing and telemetry, goal- or prediction-directed autonomy, dynamic inter-calibration, evaluation/comparison of alternative observing strategies, network communications etc. Data science abstracts (e.g., machine learning, artificial intelligence, computational techniques) are welcome, but should contribute to implementing autonomous multi-source, multi-point observing systems rather than post-collection data analysis or fusion.
Co-Sponsor(s):
  • ME - Marine Ecology and Biodiversity
  • OB - Ocean Biology and Biogeochemistry
  • PS - Physical Oceanography: Mesoscale and Smaller
Index Terms:

1940 Machine-to-machine communication [INFORMATICS]
1942 Machine learning [INFORMATICS]
1968 Scientific reasoning/inference [INFORMATICS]
1972 Sensor web [INFORMATICS]
Primary Chair:  Ian G Brosnan, NASA Ames Research Center, Earth Science Division, Moffett Field, CA, United States
Co-chairs:  Wu-Jung Lee, Applied Physics Laboratory University of Washington, Acoustics Department, Seattle, WA, United States, Laura Rogers, NASA Langley Research Center, Hampton, VA, United States and Robert Heitsenrether, NOAA Chesapeake, Chesapeake, VA, United States
Primary Liaison:  Ian G Brosnan, NASA Ames Research Center, Earth Science Division, Moffett Field, CA, United States
Moderators:  Robert Heitsenrether, NOAA Chesapeake, Chesapeake, VA, United States and Sarah Webster, University of Washington, Applied Physics Laboratory, WA, United States
Student Paper Review Liaison:  Wu-Jung Lee, Applied Physics Laboratory University of Washington, Acoustics Department, Seattle, WA, United States

Abstracts Submitted to this Session:

 
OD34D-3466
Cross-Domain command and communications synergies towards more effective cooperative missions (652956)
Paulo Dias1, Michael Incze2, Keila Lima1, Maria Costa1, Manuel Ribeiro1, Joao Tasso Borges de Sousa1, Joshua Baghdady3, Ben Jones3, Noah Hafner3, A. Zachary Trimble4, Margo Edwards3 and Raymond Andrade4, (1)University of Porto, LSTS, Department of Electrical and Computer Engineering, School of Engineering (FEUP), Porto, Portugal, (2)Naval Undersea Warfare Center, Division Newport, Newport, RI, United States, (3)University of Hawai'i, Applied Research Laboratory, Honolulu, HI, United States, (4)University of Hawai'i at Mānoa, RIP Laboratory, Department of Mechanical Engineering, Honolulu, HI, United States
 
OD34D-3467
A submesoscale cyclonic eddy observed with autonomous vehicles in synergy with ship and satellite measurements (645457)
Adriana M Santos Ferreira1, José C B da Silva2, Renato Mendes3,4 and Joao Tasso Borges de Sousa1, (1)University of Porto, LSTS, Department of Electrical and Computer Engineering, School of Engineering (FEUP), Porto, Portugal, (2)University of Porto, Department of Geosciences, Environment and Spatial Planning (DGAOT), Porto, Portugal, (3)Universidade do Porto, CIIMAR (Interdisciplinary Centre of Marine and Environmental Research), Porto, Portugal, (4)University of Aveiro, CESAM (Centre for Environmental and Marine Studies), Aveiro, Portugal
 
OD34D-3468
Autonomous Path Planning to Optimally Harvest Dynamic Fields (657800)
Manan Doshi, Massachusetts Institute of Technology, Cambridge, United States, Manmeet Bhabra, Massachusetts Institute of Technology, Mechanical Engineering, Cambridge, MA, United States and Pierre F J Lermusiaux, Massachusetts Institute of Technology, Department of Mechanical Engineering, Cambridge, MA, United States
 
OD34D-3469
Complementary Ocean Data Collection using Heterogeneous Sensor Platforms (654846)
Tore Mo-Bjørkelund1, Petter Norgren1, Trygve Olav Fossum2 and Martin Ludvisen2,3, (1)Norwegian University of Science and Technology, Department of Marine Technology, Trondheim, Norway, (2)Norwegian University of Science and Technology (NTNU), Department of Marine Technology, Centre of Autonomous Marine Operations and Systemt (AMOS), Trondheim, Norway, (3)University Centre in Svalbard, Department of Arctic Technology, Longyearbyen, Norway
 
OD34D-3470
A Flexible, Automated, Processing and Decision System to Support Ocean Color Satellite Vicarious Calibration Using Hyperspectral Radiometric Instrumentation on Autonomous Profiling Floats. (648539)
Andrew Barnard, SEA-BIRD SCIENTIFIC, Bellevue, WA, United States, Emmanuel Boss, University of Maine, Orono, United States, Robert J Frouin, University of California San Diego, Scripps Institution of Oceanography, La Jolla, CA, United States and Matthew R Mazloff, Scripps Institution of Oceanography, UCSD, La Jolla, United States
 
OD34D-3471
QARTOD - Prospects for Real-Time Quality Control Manuals, How to Create Them, and a Vision for Advanced Implementation (648398)
Mark Bushnell, CoastalObsTechServices, Virginia Beach, VA, United States, Kathleen Bailey, NOAA NOS U.S. Integrated Ocean Observing System, Silver Spring, United States, Julie A Bosch, NOAA / NCEI, Stennis Space Center, United States, Eugene F Burger, NOAA, Boulder, United States, Jennifer Dorton, SouthEast Coastal Ocean Observing Regional Association, Wilmington, NC, United States, Robert Heitsenrether, NOAA Chesapeake, Chesapeake, VA, United States, Jeff King, USACE, Washington, United States, Shannon McArthur, National Data Buoy Center, Stennis Space Center, MS, United States, Mario Tamburri, University of Maryland (UMCES CBL), Solomons, MD, United States, Julie Thomas, UCSD/SIO/IOD, La Jolla, CA, United States and Hans Christoph Waldmann, MARUM - University of Bremen, Bremen, Germany
 
OD34D-3472
NASA's AIST Program funds technology for the next decade (655106)
Michael M Little, NASA Headquarters, Earth Science Technology Office, Washington, DC, United States
See more of: Physical Oceanography: Mesoscale and Smaller