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MICHÁLEK, J. OUJEZSKÝ, V. ŠKORPIL, V.
Original Title
An Android Federated Learning Framework for Emergency Management Applications
Type
conference paper
Language
English
Original Abstract
In this paper, we present an Android federated learning framework designed specifically for emergency management applications. Our focus is on addressing the challenges related to communication in such scenarios. To overcome the limitations of centralized server architectures, we propose a novel communication protocol that enables the framework to efficiently collaborate with multiple centralized servers. This protocol facilitates effective knowledge sharing and model training while ensuring data privacy and security. By leveraging this protocol, our framework enhances the performance and robustness of critical infrastructure systems on the Android platform, enabling real-time operational scenarios. Through this research, we contribute to the advancement of emergency management applications by providing a comprehensive solution that optimizes communication and enables seamless collaboration with multiple centralized servers.
Keywords
Android; communication protocol; federated learning; framework; machine learning
Authors
MICHÁLEK, J.; OUJEZSKÝ, V.; ŠKORPIL, V.
Released
30. 10. 2023
Publisher
IEEE
ISBN
979-8-3503-9328-6
Book
2023 15th International Congress on Ultra Modern Telecommunications and Control Systems and Workshops (ICUMT)
2157-023X
Periodical
International Congress on Ultra Modern Telecommunications and Control Systems and Workshops
State
unknown
Pages from
97
Pages to
101
Pages count
5
URL
https://ieeexplore.ieee.org/document/10333300
BibTex
@inproceedings{BUT185682, author="Jakub {Michálek} and Václav {Oujezský} and Vladislav {Škorpil}", title="An Android Federated Learning Framework for Emergency Management Applications", booktitle="2023 15th International Congress on Ultra Modern Telecommunications and Control Systems and Workshops (ICUMT)", year="2023", journal="International Congress on Ultra Modern Telecommunications and Control Systems and Workshops", pages="97--101", publisher="IEEE", doi="10.1109/ICUMT61075.2023.10333300", isbn="979-8-3503-9328-6", issn="2157-023X", url="https://ieeexplore.ieee.org/document/10333300" }