Table 2 Summary of important works related to application of FL based approaches.
From: Leveraging federated learning and edge computing for pandemic-resilient healthcare
Ref | Year | Contribution |
|---|---|---|
2020 | Due to Federated Learning’s greater concern for privacy, several sectors are urged to implement it and make sure their privacy is preserved | |
2020 | The primary driving force for the adoption of this cutting-edge technology in Florida is the constant presence of data on consumer edge devices The new foundation for working while utilizing federated learning Training algorithms have historically relied on centralized architecture | |
2020 | FL offers a fresh take on decentralizing solutions that improve efficiency and performance on big data sets. Carefully analyzing the costs and benefits is necessary if we want to convince companies to use the federated learning paradigm. | |
2020 | One of the most important advantages of FL is the elimination of privacy issues | |
2020 | Federated Learning works best in situations where managing and accessing data is a privacy problem Because of this, it is ideal for businesses and sectors where privacy is a top priority FL is utilizing a decentralized method; therefore, the training algorithm and data are not a concern The training algorithm’s job is to teach the edge devices and only transmit the necessary and pertinent data | |
2020 | Federated Learning completed its task even when the edge devices were in operation. charging, or linked via WiFi. Thus, the end user should not be concerned about data leaks or battery issues | |
2021 | Comparison between the proposed models’ loss, accuracy, and performance speed are explained here | |
2022 | Genetic clustered federated learning for COVID-19 detection is done. | |
2023 | Federated clustering and semi supervised clustering are used to detect human activity in different cases | |
2024 | Federated Learning (FL) overcomes this issue by allowing many healthcare organizations to collaborate on decentralized data without sharing it. FL’s reach in healthcare includes disease prediction, therapeutic personalization, and clinical trial research | |
2023 | Proposing a framework to integrate edge and blockchain into lung cancer detection to ensure data protection and accuracy CapsNet model is used here for benefits of rich private data exchange while maintaining privacy, Blockchain data sharing process | |
[This work] | 2024 | Adoption of a YOLOv4 and SENET attention layer on edge nodes and several DPTMs on a FL framework to develop a pandemic−compliant architecture to perform facemask detection, determine correct facemask wearing, conduct contact tracing, and figure out cyber-attacks |
