Resumen
Next-generation industrial systems promise to deliver unprecedented excellence not only in terms of
performance, but also explainability, trustworthiness and transparency. To achieve this new
objectives, state-of-the-art concepts of artificial intelligence (Al), edge-to-cloud (E2C)
computing, blockchain, and visualisation need to be de-risked and applied. Motivated by this, TALON
aims at sculpturing the road towards the next lndustrial revolution by developing a fully-automated
Al architecture capable of bringing intelligence near the edge in a flexible, adaptable,
explainable, energy and data efficient manner. TALON architecture consists of three fundamental
pillars: a) an Al orchestrator that coordinates the network and service orchestrators in order to
optimise the edge vs cloud relationship, while boosting reusability of datasets, algorithms and
models by deciding where each one should be placed; b) a lightweight hierarchical blockchain
schemes that introduce new service models and applications under a privacy and security umbrella;
and c) new digital-twin empowered transfer learning and visualization approaches that enhance Al
trustworthiness and transparency. lt combines the benefits of Al, edge and cloud networking, as
well as blockchain and DTs, optimized by means of a) new key performance indicators that translate
the Al benefits into insightful metrics; b) novel theoretical framework for the characterisation of
the Al; c) blockchain used to deliver personalised & perpetual protection based on security,
privacy and trust mechanisms; d) Al approaches for automatically and co-optimising edge and cloud
resources as well as the Al execution nodes; e) semantic Al to reduce the learning latency and
enhance reusability; and f)
man-in-the-loop approaches. All the technological breakthroughs are
emonstrated, validated and evaluated by means of proof-of-concept simulation and four real-world
pilots.
