EGU24-5308, updated on 08 Mar 2024
https://doi.org/10.5194/egusphere-egu24-5308
EGU General Assembly 2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.

Information Physical Quantum Technological Intelligence (IPQuTI) for Global High-Resolution Anticipatory Multi-Hazard Sensing, Modelling and Decision Support

Rui A. P. Perdigão1,2 and Julia Hall1,2
Rui A. P. Perdigão and Julia Hall
  • 1Meteoceanics Institute for Complex System Science, Washington, DC, USA
  • 2Synergistic Manifolds, Lisbon, Portugal

We hereby introduce our latest Information Physical Quantum Technological Intelligence (IPQuTI), further empowering next-generation innovation and service workflows from sensing to computing, communications and security across multissectorial theatres of operation.

Methodologically, we build a novel synergistic dynamic interface among the novel augmented sensing technologies in our Quantum Aerospace Systems Intelligence (QuASI), the enhanced complex system dynamic analytics and model design methodologies in our latest Information Physical Artificial Intelligence (IPAI) and Earth System Dynamic Intelligence (ESDI), and the latest computational developments in our Synergistic Nonlinear Quantum Wave Intelligence Networks (SynQ-WIN).

With multi-hazard system dynamic complexity across diverse interacting geospheres and space in mind, we leverage and further build on our Meteoceanics QITES Constellation to tackle critical intelligence and security challenges to improve crucial awareness, understanding, preparedness and resilience in the face of pressing challenges facing our environment and society.

Operationally, our technologies are developed in-house and deployed across an infrastructural ecosystem on Earth and in Space. In doing so, we produce an integrated synergistic platform to support scientific, technical, management and security forces across challenging theaters of operation. From prediction and detection of early warning signs of hazards and multi-hazards, to processing and relaying complex sensitive information in a swift, secure manner across environmental and security value chains.

The operational and societal relevance of the overall methodological and technological advances are illustrated through the simulation of individual, compound and coevolutionary disaster occurrences across a sample of synthetically generated and real-world practical examples, thereby reporting concrete outputs of this platform. Some are representative of recurrent occurrences in line with the latest state-of-the-art abilities of dynamic modelling, machine learning and artificial intelligence, whereas others leap beyond the state-of-the-art with the new capabilities brought up by our latest advances, harnessing and simulating unprecedented non-recurrent emerging features and synergies elusive to prior data records and model designs.

These simulations further guide the mathematically robust, physically consistent deployment of system dynamic intelligence to address non-recurrent and other emerging phenomena. This is of special relevance in the face of structural-functional critical transitions and emergent multi-hazard behaviours associated to the synergistic coevolution between humans and nature e.g. pertaining a changing climate and land use, along with emerging transitions, criticalities and extremes, including black swan events, i.e. those non-recurrent high-impact phenomena elusive to traditional recurrence-based system dynamic modelling and information technologies.

Our novel IPQuTI brings added synergistic integrated value from sensing to computing and decision support, further enhancing the methodological and operational capabilities of current platforms along with ongoing projects on multi-hazard risk intelligence and disaster resilience such as the platforms being developed in the scope of Horizon Europe project C2IMPRESS.

 

Acknowledgement: This contribution is developed in the scope of the Meteoceanics Flagship on Quantum Information Technologies in the Earth Sciences (QITES), and of the C2IMPRESS project supported by the Εuropean Union under the Horizon Europe grant 101074004.

 

How to cite: Perdigão, R. A. P. and Hall, J.: Information Physical Quantum Technological Intelligence (IPQuTI) for Global High-Resolution Anticipatory Multi-Hazard Sensing, Modelling and Decision Support, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5308, https://doi.org/10.5194/egusphere-egu24-5308, 2024.