Autonomous and Self-organized Artificial Intelligent Orchestrator for a Greener Industry 4.0
The expected diversity of services, use cases, and applications in I5.0 requires a flexible, adaptable, and programmable AI architecture that optimizes the edge vs cloud AI to maximize the performance of the overall system. In the face of this challenge, TALON introduces an AI orchestrator that envisions transforming the I5.0 into an automated intelligent platform by exploiting advances in edge networks and bringing intelligence near sensors in embedded systems with limited computational, storage, and communication resources, as well as the integration of advanced and adaptive sensors and perception.
In this direction, TALON’s AI orchestrator maximizes both global and individual users’ and systems’ capabilities without violating the design parameters of each application. In particular, the orchestrator selects AI datasets, algorithms, metrics, and models based on the application. This creates a new system architecture that makes the most by
- jointly optimizing the edge and cloud resources,
- enabling centralized, distributed, as well as hybrid intelligence and
- transforming the AI network into a low-power computer, which will be able to use underutilized (commercial and business) resources.
Likewise, by following a holistic optimization approach and leveraging the developments in blockchain, TALON aims at supporting end-to-end (e2e) personalized and perpetual security and privacy. Finally, to accommodate the particularities of the TALON architecture that are generated due to the use of novel building blocks, such as AI orchestrator, blockchain, edge networking, and DTs, a new experimentally-verified theoretical framework will be presented.
AI orchestrator for autonomous and dynamic scalability as well as greener AI networks to enhance resources coordination of infrastructures with different computational and communication resources; thus, significantly reduce the energy consumption.
Distributed blockchain for high-security, privacy and trust in a heterogeneous application environment to transform I5.0 into intelligent platforms and introduce new service models and use cases.
Flexible E2C deployment for “almost-zero latency” and high-computational capabilities near sensors, by means of personalized caching, task offloading, AI models placements and distributed as well as TL.
DTs and HIL to boost AI explainability, trust-worthiness and transparency by visualizing and involving the human into the decision-making process and decisively reduce the learning latency by combining TL approaches with DTs.
This project has received funding from the European Union’s Horizon Europe Research and Innovation programme under grant agreement No. 101070181.