Natural disasters are more and more often present in our daily life. Many are the cases where these events affect people and economies. In this context, there is the need for a technological intervention in support of first responders, with solutions capable of make decisions on the disaster areas. Indeed, considering these scenarios are time-sensitive, the intention is moving the computation units closer to those areas. In this paper, we propose a computing continuum architecture for offloading distributed intelligences over cloud, edge and deep edge layers. Exploiting the federated learning paradigm, enables mobile and stationary devices to independently train local models, contributing to the creation of the global common model.

Supporting the Natural Disaster Management Distributing Federated Intelligence over the Cloud-Edge Continuum: the TEMA Architecture

Carnevale, Lorenzo;Marino, Roberto;Ruggeri, Armando;Fazio, Maria
2023-01-01

Abstract

Natural disasters are more and more often present in our daily life. Many are the cases where these events affect people and economies. In this context, there is the need for a technological intervention in support of first responders, with solutions capable of make decisions on the disaster areas. Indeed, considering these scenarios are time-sensitive, the intention is moving the computation units closer to those areas. In this paper, we propose a computing continuum architecture for offloading distributed intelligences over cloud, edge and deep edge layers. Exploiting the federated learning paradigm, enables mobile and stationary devices to independently train local models, contributing to the creation of the global common model.
2023
979-8-4007-0473-4
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11570/3306635
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