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

• URL: http://arxiv.org/abs/2104.00983v1
• Date: Fri, 2 Apr 2021 11:00:20 GMT
• Title: STARdom: an architecture for trusted and secure human-centered manufacturing systems
• Authors: Jo\v{z}e M. Ro\v{z}anec, Patrik Zajec, Klemen Kenda, Inna Novalija, Bla\v{z} Fortuna, Dunja Mladeni\'c, Entso Veliou, Dimitrios Papamartzivanos, Thanassis Giannetsos, Sofia Anna Menesidou, Rub\'en Alonso, Nino Cauli, Diego Reforgiato Recupero, Dimosthenis Kyriazis, Georgios Sofianidis, Spyros Theodoropoulos and John Soldatos
• Abstract summary: We propose an architecture that integrates forecasts, Explainable Artificial Intelligence, supports collecting users' feedback, and uses Active Learning and Simulated Reality to enhance forecasts. We tailor it for the domain of demand forecasting and validate it on a real-world case study.
• Score: 4.093985503448998
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• 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.

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