Smart Inventory System for Expiry Date Tracking
Volume-7 | Issue-2

Exploiting Vulnerabilities in Weak CAPTCHA Mechanisms within DVWA
Volume-7 | Issue-2

Investigating Process Scheduling Techniques for Optimal Performance and Energy Efficiency in Operating Systems
Volume-6 | Issue-4

Gamification in Mobile Apps: Assessing the Effects on Customer Engagement and Loyalty in the Retail Industry
Volume-5 | Issue-4

AI based Identification of Students Dress Code in Schools and Universities
Volume-6 | Issue-1

Review on Sanskrit Sandhi Splitting using Deep Learning Techniques
Volume-6 | Issue-2

AI-Powered Data Interaction: A Natural Language Chatbot for CSV, Excel, and SQL Files
Volume-7 | Issue-1

A Comprehensive Study of Zero-Day Attacks
Volume-5 | Issue-3

TF-IDF Vectorization and Clustering for Extractive Text Summarization
Volume-6 | Issue-1

A Review on Cryptocurrency and its Advancements in Present World
Volume-4 | Issue-4

AUTOMATION USING IOT IN GREENHOUSE ENVIRONMENT
Volume-1 | Issue-1

Principle of 6G Wireless Networks: Vision, Challenges and Applications
Volume-3 | Issue-4

Classification of Remote Sensing Image Scenes Using Double Feature Extraction Hybrid Deep Learning Approach
Volume-3 | Issue-2

Light Weight CNN based Robust Image Watermarking Scheme for Security
Volume-3 | Issue-2

VIRTUAL REALITY GAMING TECHNOLOGY FOR MENTAL STIMULATION AND THERAPY
Volume-1 | Issue-1

Design of Digital Image Watermarking Technique with Two Stage Vector Extraction in Transform Domain
Volume-3 | Issue-3

Analysis of Natural Language Processing in the FinTech Models of Mid-21st Century
Volume-4 | Issue-3

PROGRESS AND PRECLUSION OF KNEE OSTEOARTHRITIS: A STUDY
Volume-3 | Issue-3

Image Augmentation based on GAN deep learning approach with Textual Content Descriptors
Volume-3 | Issue-3

Comparative Analysis for Personality Prediction by Digital Footprints in Social Media
Volume-3 | Issue-2

Home / Archives / Volume-7 / Issue-1 / Article-5

Volume - 7 | Issue - 1 | march 2025

Enhanced Federated Learning Framework for Edge-Enabled Green IoT Open Access
Jennifer S. Raj   177
Pages: 56-67
Full Article PDF pdf-white-icon
Cite this article
Raj, Jennifer S.. "Enhanced Federated Learning Framework for Edge-Enabled Green IoT." Journal of Information Technology and Digital World 7, no. 1 (2025): 56-67
Published
30 April, 2025
Abstract

The Internet of Things (IoT) is rapidly transforming industries by enabling seamless data collection and processing. However, the massive influx of data poses significant challenges in terms of energy consumption and privacy. Federated Learning (FL) has emerged as a promising solution, allowing distributed model training without transmitting raw data. This research proposes an Enhanced Federated Learning Framework (EFLF) for edge-enabled green IoT that optimizes energy efficiency while maintaining high model accuracy. The proposed framework integrates adaptive client selection, energy-aware aggregation, and model compression techniques. Experimental results demonstrate superior performance in terms of energy efficiency and model convergence compared to baseline FL approaches.

Keywords

Internet of Things (IoT) Federated Learning (FL) Energy Efficiency Data Collection

×

Currently, subscription is the only source of revenue. The subscription resource covers the operating expenses such as web presence, online version, pre-press preparations, and staff wages.

To access the full PDF, please complete the payment process.

Subscription Details

Category Fee
Article Access Charge
15 USD
Open Access Fee Nil
Annual Subscription Fee
200 USD
After payment,
please send an email to irojournals.contact@gmail.com / journals@iroglobal.com requesting article access.
Subscription form: click here