Abstract Federated Learning (FL) enhances Artificial Intelligence (AI) applications by
enabling individual devices to collaboratively learn shared models without uploading local …

Data science projects represent a greater challenge than software engineering for
organizations pursuing their adoption. The diverse stakeholders involved emphasize the …

A revolution in advanced manufacturing has been driven by digital technology in the fourth
industrial revolution, also known as Industry 4.0, and has resulted in a substantial increase …

The integration of edge intelligence (EI) in animation design, particularly when dealing with
large models, represents a significant advancement in the field of computer graphics and …

The detection of critical situations through the adoption of multi-sensor Emergency Detection
Units (EDUs) can significantly reduce the time between the initial stages of urban …

This article comprehensively reviews the emerging concept of Internet of Intelligent Things
(IoIT), adopting an integrated perspective centred on the areas of embedded systems, edge …

Emerging technologies are continually redefining the paradigms of smart farming and
opening up avenues for more precise and informed farming practices. A tiny machine …

Food supply chains are increasingly digitised and automated through the use of
technologies such as Internet-of-Things (IoT), blockchain and Artificial Intelligence (AI). Such …

Abstract Tiny Machine Learning (TinyML) is an expanding research area based on pushing
intelligence to the edge and bringing machine learning techniques to very small devices and …

Machine learning (ML) within the edge internet of things (IoT) is instrumental in making
significant shifts in various industrial domains, including smart farming. To increase the …