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 …

Tiny Machine Learning (TinyML), a rapidly evolving edge computing concept that links
embedded systems (hardware and software) and machine learning, with the purpose of …

The computing everywhere paradigm is paving the way for the pervasive diffusion of tiny
devices (such as Internet-of-Things or edge computing devices) endowed with intelligent …

The rapid growth in miniaturization of low-power embedded devices and advancement in
the optimization of machine learning (ML) algorithms have opened up a new prospect of the …

The emergence of Tiny Machine Learning (TinyML) has positively revolutionized the field of
Artificial Intelligence by promoting the joint design of resource-constrained IoT hardware …

Internet of things (IoT) enables the integration of smart and intelligent systems in our lives,
subsequently creating an AI-powered society, where the latter is a substantial ingredient in …

Abstract In recent years, Artificial Intelligence (AI) and Machine learning (ML) have gained
significant interest from both, industry and academia. Notably, conventional ML techniques …

Tiny Machine Learning (TML) is a novel research area aiming at designing and developing
Machine Learning (ML) techniques meant to be executed on Embedded Systems and …

We use 250 billion microcontrollers daily in electronic devices that are capable of running
machine learning models inside them. Unfortunately, most of these microcontrollers are …

Healthcare is the field that can benefit from the large amount of raw data generated from
portable and wearable devices. This data must be sent to the Cloud for processing due to …