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

Technology solutions must effectively balance economic growth, social equity, and
environmental integrity to achieve a sustainable society. Notably, although the Internet of …

Model-predictive control (MPC) is a powerful tool for controlling highly dynamic robotic
systems subject to complex constraints. However, MPC is computationally demanding, and …

In the rapidly evolving landscape of electronics, Artificial Intelligence Circuits and Systems
(AICAS) stand out as a groundbreaking frontier. This review provides an exhaustive …

Is TinyML Sustainable? Page 1 THE CONTINUED GROWTH of carbon emissions and global
waste presents a great concern for our environment, increasing calls for a more sustainable …

Federated learning (FL) has emerged as a promising approach to collaboratively train
machine learning models across multiple edge devices while preserving privacy. The …

Robot vacuum cleaners have gained widespread popularity as household appliances. One
significant challenge in enhancing their functionality is to identify and classify small indoor …

While numerous methods achieving remarkable performance exist in the Object Detection
literature, addressing data distribution shifts remains challenging. Continual Learning (CL) …

The adoption of autonomous swarms, consisting of a multitude of unmanned aerial vehicles
(UAVs), operating in a collaborative manner, has become prevalent in mainstream …

In the Machine Learning (ML) era, faced with challenges, including exponential multi-sensor
data, an increasing number of actuators, and data-intensive algorithms, the development of …