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.
An IoE-based Framework Supporting Human-Centric Industry / Arazzi, M.; Belli, A.; Cusano, C.; Esposito, M.; Facchinetti, T.; Ferretti, M.; Galimberti, G.; Sciarroni, M. M.; Napoletano, P.; Nocera, A.; Pierleoni, P.; Storti, E.; Ursino, D.. - (2025). ( 30th International Conference on Emerging Technologies and Factory Automation (ETFA) Porto, Portugal 09-12 September 2025) [10.1109/ETFA65518.2025.11205771].
An IoE-based Framework Supporting Human-Centric Industry
Belli A.;Esposito M.;Pierleoni P.;Storti E.;Ursino D.
2025-01-01
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.| File | Dimensione | Formato | |
|---|---|---|---|
|
Arazzi_An-IoE-based-Framework-Supporting_Post-print.pdf
accesso aperto
Tipologia:
Documento in post-print (versione successiva alla peer review e accettata per la pubblicazione)
Licenza d'uso:
Licenza specifica dell'editore
Dimensione
1.76 MB
Formato
Adobe PDF
|
1.76 MB | Adobe PDF | Visualizza/Apri |
|
Arazzi_IoE-based-Framework-Supporting_2025.pdf
Solo gestori archivio
Tipologia:
Versione editoriale (versione pubblicata con il layout dell'editore)
Licenza d'uso:
Tutti i diritti riservati
Dimensione
1.81 MB
Formato
Adobe PDF
|
1.81 MB | Adobe PDF | Visualizza/Apri Richiedi una copia |
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.


