UniCas for Industry
Authors: CEUR-WS, Alessio Miele, Hamza Mustafa, Michele Vitelli, Alessandro Bria, Claudio De Stefano, Francesco Fontanella, Claudio Marrocco, Mario Molinara, Alessandra Scotto di Freca, Miele A., Mustafa H., Vitelli M., Bria A., De Stefano C., Fontanella F., Marrocco C., Molinaria M., di Freca A.S., corda_____he::de1cc9242568d954beba138f12d7aec1
Abstract
Artificial Intelligence (AI) is transforming industries, particularly through Industry 4.0, by integrating technologies such as the Internet of Things (IoT) to optimize production processes and resource management. It addresses challenges such as reducing environmental impact while fulfilling consumer demands. Innovative sensors enable real-time data collection for environmental monitoring. Adopting advanced technologies such as energy cells, particularly lithium-ion batteries, is crucial for sustainable mobility and reducing environmental impact in the automotive industry. It is vital to understand the key parameters of energy cells, including range, energy density, and durability, and implement them while embracing the principles of Second Life effectively. For example, machine learning (ML) algorithms are utilized in industrial contexts to identify air and water pollutants and estimate the State of Charge (SoC) for automotive applications. These methodologies improve efficiency, sustainability, and innovation in various industrial sectors.
BibTeX
@misc{ceurws2024unicas,
title={UniCas for Industry},
author={CEUR-WS and Alessio Miele and Hamza Mustafa and Michele Vitelli and Alessandro Bria and Claudio De Stefano and Francesco Fontanella and Claudio Marrocco and Mario Molinara and Alessandra Scotto di Freca and Miele A. and Mustafa H. and Vitelli M. and Bria A. and De Stefano C. and Fontanella F. and Marrocco C. and Molinaria M. and di Freca A.S. and corda_____he::de1cc9242568d954beba138f12d7aec1},
year={2024}
}