Fog computing-based framework and solutions for intelligent systems: Enabling autonomy in vehicles

M Dhanalakshmi, K Tamilarasi… - … Intelligence for Green …, 2024 - igi-global.com
The automotive industry is increasingly focusing on autonomous vehicles, leading to a need
for intelligent systems that enable safe and efficient self-driving. Fog computing is a …

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 …

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 …

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 …

The convergence of cutting-edge technologies: leveraging AI and edge computing to transform the internet of medical things (IoMT)

R Punugoti, N Vyas, AT Siddiqui… - 2023 4th International …, 2023 - ieeexplore.ieee.org
This research used a wearable sensor to gather photoplethysmography (PPG) signals from
15 healthy subjects. The dataset includes 7,308 PPG segments, each containing 8 seconds …

Healthcare and fitness services: a comprehensive assessment of blockchain, IoT, and edge computing in smart cities

YY Liu, Y Zhang, Y Wu, M Feng - Journal of Grid Computing, 2023 - Springer
Edge computing, blockchain technology, and the Internet of Things have all been identified
as key enablers of innovative city initiatives. A comprehensive examination of the research …

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 …

Novel Transformation Deep Learning Model for Electrocardiogram Classification and Arrhythmia Detection using Edge Computing

Y Han, P Han, B Yuan, Z Zhang, L Liu… - Journal of Grid …, 2024 - Springer
The diagnosis of the cardiovascular disease relies heavily on the automated classification of
electrocardiograms (ECG) for arrhythmia monitoring, which is often performed using …

Knowledge Graph Based on Reinforcement Learning: A Survey and New Perspectives

Q Huo, H Fu, C Song, Q Sun, P Xu, K Qu, H Feng… - IEEE …, 2024 - ieeexplore.ieee.org
Knowledge graph is a form of data representation that uses graph structure to model the
connections between things. The intention of knowledge graph is to optimize the results …

A deep reinforcement learning-based two-dimensional resource allocation technique for V2I communications

H **, J Seo, J Park, SC Kim - IEEE Access, 2023 - ieeexplore.ieee.org
This paper proposes a two-dimensional resource allocation technique for vehicle-to-
infrastructure (V2I) communications. Vehicular communications requires high data rates, low …