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TEACHING - Trustworthy autonomous cyber-physical applications through human-centred intelligence

Contributo in Atti di convegno
Data di Pubblicazione:
2021
Abstract:
This paper discusses the perspective of the H2020 TEACHING project on the next generation of autonomous applications running in a distributed and highly heterogeneous environment comprising both virtual and physical resources spanning the edge-cloud continuum. TEACHING puts forward a human-centred vision leveraging the physiological, emotional, and cognitive state of the users as a driver for the adaptation and optimization of the autonomous applications. It does so by building a distributed, embedded and federated learning system complemented by methods and tools to enforce its dependability, security and privacy preservation. The paper discusses the main concepts of the TEACHING approach and singles out the main AI-related research challenges associated with it. Further, we provide a discussion of the design choices for the TEACHING system to tackle the aforementioned challenges.
Tipologia CRIS:
04.01 Contributo in Atti di convegno
Keywords:
Distributed neural networks; Human-centred artificial intelligence; Cyber-physical systems; Ubiquitous and pervasive computing; Edge artificial intelligence
Elenco autori:
Coppola, Massimo; Dazzi, Patrizio; Gotta, Alberto; Cassara', Pietro; Bacco, FELICE MANLIO; Carlini, Emanuele
Autori di Ateneo:
BACCO FELICE MANLIO
CARLINI EMANUELE
CASSARA' PIETRO
COPPOLA MASSIMO
GOTTA ALBERTO
Link alla scheda completa:
https://iris.cnr.it/handle/20.500.14243/401331
Link al Full Text:
https://iris.cnr.it//retrieve/handle/20.500.14243/401331/177957/prod_455251-doc_175848.pdf
Titolo del libro:
2021 IEEE International Conference on Omni-layer Intelligent Systems (COINS)
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URL

https://ieeexplore.ieee.org/document/9524099
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