… Federated Learning (FL) has emerged as a distributed collaborative AI approach that can
enable many intelligent IoT applications, by allowing for AI training at distributed IoT devices …

… The purpose of this study is to provide an overview of the FL … Federated learning may enable
autonomous vehicles to … process, we will use the federated learning approach to train CNN (…

… survey, we introduce the basic fundamentals of FL, describing its underlying technologies,
architectures, system challenges, and privacy-preserving methods… , autonomous vehicles, IoT, …

… vehicles and the transmission overhead of these datasets to the cloud servers. Hence, FL is
a promising approach to efficiently train the learning … , we present a case study of FL, such as …

… This smartness and connected approach … federated learning (FL) model primarily depends
on the data quality, since they are supposed to make efficient decisions. Automated vehicles …

… The traditional ML uses centralized machine learning approaches. In centralized machine …
this comprehensive survey on Federated Learning for smart cities. The Federated Learning for …

… In this paper, we first conduct a brief survey of existing studies … -mitigated federated
learning approach that reduces … 1) Perception technologies for autonomous vehicles Since …

… dynamic federated proximal (DFP) algorithm. Different from the conventional FL-based methods
in … In particular, we study how the mobility of the CAVs, wireless fading channels, and the …

… federated vehicle cloud (FVC), and a preliminary study of … this is the idea of “connected
and autonomous vehicles” [2]. … FVN–Data-Parallel Approach: There are two different ways we …

… learning are summarized. Then we discuss the potential of using machine learning, deep
learning … Further we analyze and summarize the ways to handle the heterogeneous and huge …