Federated Transfer Learning for IIoT Devices With Low Computing Power Based on Blockchain and Edge Computing
With the development of artificial intelligence and Internet of Things (IoT), the era of industry 4.0 has come. According to the prediction of IBM, with the continuous popularization of 5G technology, the IoT technology will be more widely used in factories. In recent years, federated learning has b...
Saved in:
| Main Authors: | Peiying Zhang, Hao Sun, Jingyi Situ, Chunxiao Jiang, Dongliang Xie |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2021-01-01
|
| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/9477440/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Blockchain Enabled Federated Learning for Detection of Malicious Internet of Things Nodes
by: Rachid Alami, et al.
Published: (2024-01-01) -
Trustworthy and efficient project scheduling in IIoT based on smart contracts and edge computing
by: Peng Liu, et al.
Published: (2025-01-01) -
Semi-supervised Federated Learning for Digital Twin 6G-enabled IIoT: A Bayesian estimated approach
by: Yuanhang Qi, et al.
Published: (2024-12-01) -
A Blockchain-Assisted Federated Learning Framework for Secure and Self-Optimizing Digital Twins in Industrial IoT
by: Innocent Boakye Ababio, et al.
Published: (2025-01-01) -
EdgeGuard: Decentralized Medical Resource Orchestration via Blockchain-Secured Federated Learning in IoMT Networks
by: Sakshi Patni, et al.
Published: (2024-12-01)