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

Conference Paper
Publication Date:
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.
Iris type:
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
List of contributors:
Coppola, Massimo; Dazzi, Patrizio; Gotta, Alberto; Cassara', Pietro; Bacco, FELICE MANLIO; Carlini, Emanuele
Authors of the University:
BACCO FELICE MANLIO
CARLINI EMANUELE
CASSARA' PIETRO
COPPOLA MASSIMO
GOTTA ALBERTO
Handle:
https://iris.cnr.it/handle/20.500.14243/401331
Full Text:
https://iris.cnr.it//retrieve/handle/20.500.14243/401331/177957/prod_455251-doc_175848.pdf
Book title:
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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