A Contemporary Survey of Recent Advances in Federated Learning: Taxonomies, Applications, and Challenges

MH Alsharif, R Kannadasan, W Wei, KS Nisar… - Internet of Things, 2024 - Elsevier
Abstract The Internet of Things (IoT) has embedded itself in our daily lives, offering smart
services and AI-driven applications. However, traditional AI methods face challenges due to …

Enhancing Healthcare Efficacy Through IoT-Edge Fusion: A Novel Approach for Smart Health Monitoring and Diagnosis

M Izhar, SAA Naqvi, A Ahmed, S Abdullah… - IEEE …, 2023 - ieeexplore.ieee.org
This paper presents an innovative framework that leverages cutting-edge technologies to
revolutionize healthcare systems, focusing on data security, privacy, and efficient medical …

IRS-Aided Federated Learning with Dynamic Differential Privacy for UAVs in Emergency Response

KT Pauu, Q Pan, J Wu, AK Bashir… - IEEE Internet of Things …, 2024 - ieeexplore.ieee.org
The unforeseen events of natural disasters often devastate critical infrastructure and disrupt
communication. The use of unmanned aerial vehicles (UAVs) in emergency response …

UAV-Assisted Digital Twin Synchronization With Tiny Machine Learning-Based Semantic Communications

J Tang, J Nie, J Bai, J Xu, S Li… - IEEE Internet of Things …, 2024 - ieeexplore.ieee.org
Semantic communication is an emerging paradigm for digital twin (DT) synchronization in
unmanned aerial vehicle (UAV)-assisted edge computing environments, where machine …

SoftWind: Software-defined trajectory correction modelling of gust wind effects on internet of drone things using glowworm swarm optimization

A Hazra, D De - Ad Hoc Networks, 2024 - Elsevier
The dynamic nature of the atmosphere, especially wind gust, poses a crucial challenge to
efficient and real-time drone operations. This article presents a novel MQTT based software …

Online Optimization in UAV-Enabled MEC System: Minimizing Long-Term Energy Consumption Under Adapting to Heterogeneous Demands

Y Zeng, S Chen, J Li, Y Cui, J Du - IEEE Internet of Things …, 2024 - ieeexplore.ieee.org
Unmanned aerial vehicle (UAV) can work as a flying computing platform to supply
computation services to users when the terrestrial infrastructure is insufficient or damaged …

[HTML][HTML] 6G edge-networks and multi-UAV knowledge fusion for urban autonomous vehicles

MW Nawaz, W Zhang, D Flynn, L Zhang, R Swash… - Physical …, 2024 - Elsevier
The advent of 6G wireless networks has the potential to unlock diverse applications of
scalable autonomy. By advantageously coupling the individual and aggregated attributes of …

[HTML][HTML] 无人机空地网络研究综述

鞠宏浩, 程楷钧, 邓彩连, 颜雪镇, 尹宝林… - 西南交通大学 …, 2024 - xnjdxb.swjtu.edu.cn
无人机具有快速部署, 成本低廉等优势. 无人机空地网络通过将基站设备部署至升空无人机平台,
能从空中快速构建对地覆盖网络, 因而在应急救灾, 偏远覆盖, 智能交通, 智慧城市等方面具有 …

FLAG: Federated Learning for Sustainable Irrigation in Agriculture 5.0

S Bera, T Dey, A Mukherjee… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
This paper proposes a federated learning-based decision making framework for sustainable
irrigation using IoT and dew-edge-cloud paradigm. The federated learning is used to …

UAV-assisted Unbiased Hierarchical Federated Learning: Performance and Convergence Analysis

R Zhagypar, N Kouzayha, H ElSawy, H Dahrouj… - arXiv preprint arXiv …, 2024 - arxiv.org
The development of the sixth generation (6G) of wireless networks is bound to streamline
the transition of computation and learning towards the edge of the network. Hierarchical …