2021
Conference article  Restricted

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

Bacco M., Carlini E., Cassarà P., Coppola M., Dazzi P., Gotta A.

Distributed neural networks  Human-centred artificial intelligence  Cyber-physical systems  Ubiquitous and pervasive computing  Edge artificial intelligence 

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.

Source: IEEE COINS 2021: IEEE International Conference on Omni-layer Intelligent systems, Online conference, 23-26/08/2021



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Projects (via OpenAIRE)

TEACHING
A computing toolkit for building efficient autonomous applications leveraging humanistic intelligence


OpenAIRE
BibTeX entry
@inproceedings{oai:it.cnr:prodotti:455251,
	title = {TEACHING - Trustworthy autonomous cyber-physical applications through human-centred intelligence},
	author = {Bacco M. and Carlini E. and Cassarà P. and Coppola M. and Dazzi P. and Gotta A.},
	booktitle = {IEEE COINS 2021: IEEE International Conference on Omni-layer Intelligent systems, Online conference, 23-26/08/2021},
	year = {2021}
}