Decentralized and Distributed Learning for AIoT: A Comprehensive Review, Emerging Challenges and Opportunities

H Xu, KP Seng, LM Ang, J Smith - IEEE Access, 2024 - ieeexplore.ieee.org
The advent of the Artificial Intelligent Internet of Things (AIoT) has sparked a revolution in the
deployment of intelligent systems, driving the need for innovative data processing …

Sustainable fog-assisted intelligent monitoring framework for consumer electronics in industry 5.0 applications

SS Tripathy, S Bebortta… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
The fifth era of the industry (Industry 5.0) has been marked by the reformation witnessed in
consumer electronics sector by bringing forth technology that could enhance efficiency …

FedHealthFog: A federated learning-enabled approach towards healthcare analytics over fog computing platform

SS Tripathy, S Bebortta, CL Chowdhary, T Mukherjee… - Heliyon, 2024 - cell.com
The emergence of federated learning (FL) technique in fog-enabled healthcare system has
leveraged enhanced privacy towards safeguarding sensitive patient information over …

Towards Multi-Modal Deep Learning-Assisted Task Offloading for Consumer Electronic Devices Over An IoT-Fog Architecture

SS Tripathy, S Bebortta, MI ul Haque… - IEEE Transactions …, 2024 - ieeexplore.ieee.org
Internet of Things (IoT) devices along with associated software have proliferated at an
unprecedented pace, presenting the challenge of high energy use combined with latency …

An SDN-enabled fog computing framework for wban applications in the healthcare sector

SS Tripathy, S Bebortta, MA Mohammed, J Nedoma… - Internet of Things, 2024 - Elsevier
For healthcare systems utilizing Wireless Body Area Networks (WBANs), maintaining the
network's diverse Quality of Service (QoS) metrics necessitates effective communication …

Multi-Level Split Federated Learning for Large-Scale AIoT System Based on Smart Cities

H Xu, KP Seng, J Smith, LM Ang - Future Internet, 2024 - mdpi.com
In the context of smart cities, the integration of artificial intelligence (AI) and the Internet of
Things (IoT) has led to the proliferation of AIoT systems, which handle vast amounts of data …

[HTML][HTML] Fed-RHLP: Enhancing Federated Learning with Random High-Local Performance Client Selection for Improved Convergence and Accuracy

P Sittijuk, K Tamee - Symmetry, 2024 - mdpi.com
We introduce the random high-local performance client selection strategy, termed Fed-
RHLP. This approach allows opportunities for higher-performance clients to contribute more …

Intelligent Machine Learning Framework for Classification of Vehicular Traffic in Internet of Vehicles

B Tripathy, SS Tripathy, S Bebortta… - 2024 3rd International …, 2024 - ieeexplore.ieee.org
In a world that is always changing due to population growth, it is difficult to forecast how
routes will behave in the future, especially with regard to traffic. In this work, Traci was used …

[PDF][PDF] Orchestration Framework Based on Revocable Dynamic Hash Table for Dynamic Access of Data in Multi-Cloud Environments.

ZA Adhoni, DL Narayan - International Journal of Intelligent Engineering & …, 2024 - inass.org
The primary aim of this article is to propose a novel orchestration framework based on
Revocable Dynamic Hash Table (RDHT) for dynamic and secure access of Electronic …

PriorHealth: A Priority-Aware Task Scheduling Framework for Managing Healthcare Data in Fog Computing Applications

S Bebortta, SS Tripathy… - 2024 2nd International …, 2024 - ieeexplore.ieee.org
The advent of wearable sensor technology, like oximeters, accelerometers, and gyroscope-
based monitoring devices, are being widely used to address the important problem of health …