← Back to Research Radar
Academic Publication Academic Publication

Federated Learning for IoT: A Survey of Techniques, Challenges, and Applications

162
Citations
January 22, 2025
Published Date

Research Abstract & Technology Focus

Federated Learning (FL) has emerged as a pivotal approach for decentralized Machine Learning (ML), addressing the unique demands of the Internet of Things (IoT) environments where data privacy, bandwidth constraints, and device heterogeneity are paramount. This survey provides a comprehensive overview of FL, focusing on its integration with the IoT. We delve into the motivations behind adopting FL for IoT, the underlying techniques that facilitate this integration, the unique challenges posed by IoT environments, and the diverse range of applications where FL is making an impact. Finally, this submission also outlines future research directions and open issues, aiming to provide a detailed roadmap for advancing FL in IoT settings.
federated learning survey techniques challenges applications
Read Full Literature

Correlated Market Trend: Adaptive Learning

Bridging academia to market: The 60-day public search velocity mapping directly to the core technology of this paper. Dashed line represents 7-day moving average.

AI Semantic Synergy Context

Connecting this academic literature to real-world market discussions and products.

crossref.org › academic paper
100%
🔥

Federated Learning for IoT: A Survey of Techniques, Challenges, and Applications

Federated Learning (FL) has emerged as a pivotal approach for decentralized Machine Learning (ML), addressing the unique demands of the Internet of Things (IoT) environments where data privacy, ban...
crossref.org › academic paper
8%

Federated Learning in Smart Healthcare: A Comprehensive Review on Privacy, Security, and Predictive Analytics with IoT Integration

Federated learning (FL) is revolutionizing healthcare by enabling collaborative machine learning across institutions while preserving patient privacy and meeting regulatory standards. This review d...
crossref.org › academic paper
0%

Federated Learning for Cloud and Edge Security: A Systematic Review of Challenges and AI Opportunities

The ongoing evolution of cloud computing requires sustained attention to security, privacy, and compliance issues. The purpose of this paper is to systematically review the current literature regar...
crossref.org › academic paper
0%

Exploring privacy mechanisms and metrics in federated learning

Abstract The federated learning (FL) principle ensures multiple clients jointly develop a machine learning model without exchanging their local data. Various government enacted pr...
crossref.org › academic paper
0%

A Review on Federated Learning Architectures for Privacy-Preserving AI: Lightweight and Secure Cloud–Edge–End Collaboration

Federated learning (FL) has emerged as a promising paradigm for enabling collaborative training of machine learning models while preserving data privacy. However, the massive heterogeneity of data ...

Frequently Asked Questions (FAQ)

Curated market intelligence mapped to this research.

What is the core focus of the research titled 'Federated Learning for IoT: A Survey of Techniques, Challenges, and Applications'?

This literature focuses on: Federated Learning (FL) has emerged as a pivotal approach for decentralized Machine Learning (ML), addressing the unique demands of the Internet of Things (IoT) environments where data privacy, bandwidth constraints, and device heterogeneity are p...

Are there open-source GitHub repositories related to Federated Learning for IoT: A Survey of Techniques, Challenges, and Applications?

Yes, open-source projects like THU-MAIC/OpenMAIC (Open Multi-Agent Interactive Classroom — Get an immersive, multi-agent learning experience in just one click) are actively building upon these concepts.

Which startups are commercializing the technology behind Federated Learning for IoT: A Survey of Techniques, Challenges, and Applications?

Products like Padel Chess are bringing this to market. Their focus is: Padel tactics learning app.

What other academic literature is closely related to 'Federated Learning for IoT: A Survey of Techniques, Challenges, and Applications'?

Yes, highly correlated activity was mapped. An entry titled 'Federated Learning for IoT: A Survey of Techniques, Challenges, and Applications' discusses this: Federated Learning (FL) has emerged as a pivotal approach for decentralized Machine Learning (ML), addressing the unique demands of the Internet of...

Cite this Market Intelligence Report

Reference our AI-mapped synergy between this research and the commercial market to instantly build authority.

Commercial Realization

Startups and Open Source tools heavily associated with the concepts explored in this paper.

Associated Media Narrative