Abstract
The REDRAW project investigates the exploitation of the federated learning computing paradigm to improve the technologies adopted for the monitoring, diagnosis and treatment management of specific health conditions, developing approaches more respectful of the constraints of privacy, confidentiality and cybersecurity, which are still largely absent from the market. REDRAW proposes the study and fine-tuning of dynamic cloud-edge deployment techniques, which exploits Federated Learning (FL) models, in three real-world contexts, to improve the technological features of existing solutions, while respecting the strategic and non-functional constraints that characterize the Italian and European scenarios .
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Acknowledgements
This work has been supported by the REDRAW research project (P2022MWE3S - Prin 2022 PNRR, DR n. 1409 of 14-09-2022) funded by the Italian Ministry of Research and by the European Union.
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Aversa, R. et al. (2024). REDRAW: fedeRatED leaRning for humAn Wellbeing. In: Barolli, L. (eds) Advanced Information Networking and Applications. AINA 2024. Lecture Notes on Data Engineering and Communications Technologies, vol 203. Springer, Cham. https://doi.org/10.1007/978-3-031-57931-8_10
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DOI: https://doi.org/10.1007/978-3-031-57931-8_10
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