The Internet of Things (IoT) is penetrating many facets of our daily life with the proliferation of
intelligent services and applications empowered by artificial intelligence (AI). Traditionally …

Federated learning (FL) is a distributed machine learning strategy that generates a global
model by learning from multiple decentralized edge clients. FL enables on-device training …

Bassey, Juliet, & Stephen, P. No. 2082-2099 Page 2083 accuracy. Key findings demonstrate
that AI-enhanced LCA models significantly improve the precision and depth of …

The advancements in machine learning (ML) opened a new opportunity to bring intelligence
to the low-end Internet-of-Things (IoT) nodes, such as microcontrollers. Conventional ML …

Green hydrogen, produced through the electrolysis of water using renewable energy
sources, is heralded as a cornerstone of the future sustainable energy landscape. Unlike …

Bassey, P. No. 571-588 Page 572 predictive capability allows for better planning and
optimization of energy storage solutions, ensuring that surplus energy generated during …

This paper presents a simple yet effective approach that improves continual test-time
adaptation (TTA) in a memory-efficient manner. TTA may primarily be conducted on edge …

Abstract Online Social Networks are perpetually evolving and used in plenteous
applications such as content sharing, chatting, making friends/followers, customer …

Federated machine unlearning (FMU) aims to remove the influence of a specified subset of
training data upon request from a trained federated learning model. Despite achieving …

Unmanned aerial vehicles (UAVs) are considered as one of the promising technologies for
the next-generation wireless communication networks. Their mobility and their ability to …