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STARdom: an architecture for trusted and secure human-centered manufacturing systems

2021-04-02 11:00:20
Jože M. Rožanec, Patrik Zajec, Klemen Kenda, Inna Novalija, Blaž Fortuna, Dunja Mladenić, Entso Veliou, Dimitrios Papamartzivanos, Thanassis Giannetsos, Sofia Anna Menesidou, Rubén Alonso, Nino Cauli, Diego Reforgiato Recupero, Dimosthenis Kyriazis, Georgios Sofianidis, Spyros Theodoropoulos, John Soldatos
arXiv_AI
     
Abstract

There is a lack of a single architecture specification that addresses the needs of trusted and secure Artificial Intelligence systems with humans in the loop, such as human-centered manufacturing systems at the core of the evolution towards Industry 5.0. To realize this, we propose an architecture that integrates forecasts, Explainable Artificial Intelligence, supports collecting users' feedback, and uses Active Learning and Simulated Reality to enhance forecasts and provide decision-making recommendations. The architecture security is addressed as a general concern. We align the proposed architecture with the Big Data Value Association Reference Architecture Model. We tailor it for the domain of demand forecasting and validate it on a real-world case study.

Abstract (translated)

URL

https://arxiv.org/abs/2104.00983

PDF

https://arxiv.org/pdf/2104.00983.pdf

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