IN026
Towards a Digital Twin of Sustainable Earth and Infrastructure
Towards a Digital Twin of Sustainable Earth and Infrastructure
Session ID#: 161039
Session Description:
A comprehensive, trustworthy, and yet effective framework, such as a Digital Twin, is needed to enable the persistent ingest of multiple sources of observational and modeling earth system data in an accurate and efficient manner to allow near real-time visualization and decision-making as well as continuous monitoring to mitigate future impacts and improve infrastructure resilience.
This session seeks contributions in developing intelligent virtual representations of the Earth in the form of Digital Twin or similar to address critical social and environmental issues of our time. These Digital Twin systems will incorporate characteristics such as dynamically integratable Earth system models and simulations; other relevant models (e.g., related to the world’s infrastructure); continuous and timely (including near real time and direct readout) observations (e.g., space, air, ground, over/underwater, Internet of Things (IoT), socioeconomic); long-time records; as well as big data analytics and artificial intelligence tools.
Index Terms:
1910 Data assimilation, integration and fusion [INFORMATICS]
1932 High-performance computing [INFORMATICS]
1942 Machine learning [INFORMATICS]
1998 Workflow [INFORMATICS]
Primary Convener: Zhangshuan Hou, Pacific Northwest National Laboratory, Richland, WA, United States
Convener: Laura Rogers, NASA Langley Research Center, Hampton, VA, United States
Student/Early Career Convener: Laura Rogers, NASA Langley Research Center, Hampton, VA, United States
See more of: Earth and Space Science Informatics
