Industry 5.0 envisions manufacturing systems that are human-centric, sustainable, and resilient. In this context, the Internet of Everything (IoE) enables integration of devices, people, and processes into a unified digital ecosystem. This paper presents a modular, semantically enriched framework that supports this transition by managing heterogeneous data sources - such as IoT sensors, wearable devices, and smart objects - through a layered architecture. The platform enables real-time data stream processing, semantic interoperability, and secure, context-aware access. Anomaly detection is enabled through a privacy-preserving mechanism based on behavioral fingerprinting and federated learning. The platform supports immersive human-machine interaction via gesture recognition, empowering workers to control and interact with industrial systems. Use cases demonstrate the system's ability to support gesture-based control and intelligent monitoring, highlighting its potential to enhance adaptability, security, and worker empowerment in Industry 5.0 environments.

Arazzi, M., Belli, A., Cusano, C., Esposito, M., Facchinetti, T., Ferretti, M., et al. (2025). An IoE-based Framework Supporting Human-Centric Industry. In 2025 IEEE 30th International Conference on Emerging Technologies and Factory Automation (ETFA). Institute of Electrical and Electronics Engineers Inc. [10.1109/ETFA65518.2025.11205771].

An IoE-based Framework Supporting Human-Centric Industry

Napoletano P.;
2025

Abstract

Industry 5.0 envisions manufacturing systems that are human-centric, sustainable, and resilient. In this context, the Internet of Everything (IoE) enables integration of devices, people, and processes into a unified digital ecosystem. This paper presents a modular, semantically enriched framework that supports this transition by managing heterogeneous data sources - such as IoT sensors, wearable devices, and smart objects - through a layered architecture. The platform enables real-time data stream processing, semantic interoperability, and secure, context-aware access. Anomaly detection is enabled through a privacy-preserving mechanism based on behavioral fingerprinting and federated learning. The platform supports immersive human-machine interaction via gesture recognition, empowering workers to control and interact with industrial systems. Use cases demonstrate the system's ability to support gesture-based control and intelligent monitoring, highlighting its potential to enhance adaptability, security, and worker empowerment in Industry 5.0 environments.
paper
Anomaly detection; Big Data; Data Stream; Human-machine interaction; Industry 5.0; Internet of Everything; IoT; Knowledge graphs; Metadata;
English
30th IEEE International Conference on Emerging Technologies and Factory Automation, ETFA 2025 - 09-12 September 2025
2025
2025 IEEE 30th International Conference on Emerging Technologies and Factory Automation (ETFA)
9798331553838
2025
none
Arazzi, M., Belli, A., Cusano, C., Esposito, M., Facchinetti, T., Ferretti, M., et al. (2025). An IoE-based Framework Supporting Human-Centric Industry. In 2025 IEEE 30th International Conference on Emerging Technologies and Factory Automation (ETFA). Institute of Electrical and Electronics Engineers Inc. [10.1109/ETFA65518.2025.11205771].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/583041
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