This paper provides an overview of recent advances in the application of artificial intelligence (AI) in industrial contexts such as datacenter and the railway industries carried out at the University of Naples Federico II node of the CINI-AIIS Lab. We discuss some challenges and opportunities associated with the adoption of AI in these industries. In data centers, AI is being used to optimizer e source utilization, reduce energy consumption, and ensure high availability of services. Despite the potential benefits of AI, the reare also challenges associate dwith its adoption, including the need for high-quality data, reliability and interpretability of AI-based systems, and ethical and legal concerns related to privacy, security, and bias. From the other hand, in the railway industry, AI is being used to optimize train schedules, reduce delays, support predictive maintenance operations and improve passenger safety by predicting and preventing accidents. In this paper, we focus on Hard Disk Drive health status assessment task and on an overview of AI techniques for railway domain in the context H2020 Shift 2 Rail project.
Advanced AI-based approaches in Industry4.0 of the University of Naples Federico II node of the CINI-AIIS Lab
Antonino Ferraro;
2023-01-01
Abstract
This paper provides an overview of recent advances in the application of artificial intelligence (AI) in industrial contexts such as datacenter and the railway industries carried out at the University of Naples Federico II node of the CINI-AIIS Lab. We discuss some challenges and opportunities associated with the adoption of AI in these industries. In data centers, AI is being used to optimizer e source utilization, reduce energy consumption, and ensure high availability of services. Despite the potential benefits of AI, the reare also challenges associate dwith its adoption, including the need for high-quality data, reliability and interpretability of AI-based systems, and ethical and legal concerns related to privacy, security, and bias. From the other hand, in the railway industry, AI is being used to optimize train schedules, reduce delays, support predictive maintenance operations and improve passenger safety by predicting and preventing accidents. In this paper, we focus on Hard Disk Drive health status assessment task and on an overview of AI techniques for railway domain in the context H2020 Shift 2 Rail project.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
