AMAZING-6G proposes a novel set of 14 use cases in the domains of Healthcare, Public Safety, Energy and Transport (including Rail) which will be showcased in large-scale trials and pilots across Europe. Innovative technology enablers are planned to be developed and tested in the areas of Communications, Compute-as-a-Service, Applications and AI, IoT and localization. Security aspects will be taken into consideration in the development of solutions. Framed in this context, the significance of large-scale trials in B5G/6G networks lies not only in their ability to validate the technical capabilities of the technology but also in their capacity to unveil new use cases and applications that were previously inconceivable. As we move towards a world where the Internet of Things (IoT), augmented reality, and artificial intelligence play central roles in our daily lives, these trials provide a unique opportunity to explore the potential of B5G/6G in fostering innovative solutions across various sectors, from healthcare and transportation to utilities and public/environment safety. Through large-scale trials, stakeholders can gain valuable insights into the transformative power of B5G/6G networks and strategically position themselves to harness the full spectrum of opportunities that this cutting-edge technology offers.

The integration of edge computing, advanced 5G connectivity, and decentralized processing drives the widespread deployment of private edge ecosystems capable to reshape numerous industry sectors. However, unlocking the full potentials of edge-level intelligent management requires concerted efforts in platform development and cross-sector collaboration. COP-PILOT, develops a Collaborative Open Platform framework geared towards orchestrating end-to-end services across diverse industry domains. In crafting an open platform, COP-PILOT provides a flexible solution designed to effectively manage various industry sectors while ensuring robust security, automation, and intelligence features. Regarding interoperability, the framework seamlessly integrates with underlying technologies, ranging from IoT platforms to core infrastructure, facilitating collaboration across the compute continuum. Furthermore, COP-PILOT empowers the development of advanced cross-sector applications by offering support for cutting-edge network services, thereby enabling heightened security, resource management, and automation capabilities. The implementation strategy revolves around two primary directions: enabling platform implementation and real environment integration. For the former, COP-PILOT adopts a modular orchestration approach, simplifying the onboarding of complex applications through a user-friendly generative AI interface. This approach includes integration with multi-tiered data processing, policy-driven optimization, and dynamic reasoning capabilities, ensuring alignment with prevailing industry standards. In terms of real environment integration, the platform is deployed across four large piloting clusters, addressing a diverse array of edge paradigms. These use cases span across energy, smart city, agriculture, and industrial manufacturing sectors, fostering the development of cross-sector applications in mobility, logistics, and resource management.

One of the key enablers of 6G is undoubtedly the Native support of AI/ML at all the system levels, components, and mechanisms, from the orchestration and management levels to the low-level optimization of the infrastructure resources, including Cloud, Edge, RAN, Core Network, as well as a transport network. Despite the opportunities, there are several gaps that hinder the adoption of AI/ML in 6G, such as the lack of extensive and high-quality datasets that are required to train the models. On the other hand, AI model testing and performance evaluation in a representative staging environment (by emulation or real deployment) is also challenging without access to an end-to-end 6G testbed or representative Digital Twin environment. To this end, 6G-DALI aims to deliver an end-to-end AI framework for 6G, structured in two interdependent pillars, (1) AI experimentation as a service via MLOps and (2) Data and analytics collection and storage via DataOps. The 6G-DALI DataOps pillar provides the mechanisms for preparing clean and processed data that are stored within a 6G Dataspace and are made available for training and validating machine learning models as a service, a part of the MLOps Pillar. The end-to-end framework also delivers continuous monitoring, drift detection and retraining of models. Finally, 6G-DALI will deliver open datasets, a 6G Dataspace for dataset storage and secure sharing, and a Digital Twin testbed for data generation on demand.

Technological advances in Information communication Technologies (ICT) as well as the digital transformation of complex systems have led to the development of novel networks, platforms and systems, which have, in turn, kick-started the realisation process for multi-faceted technological collaborations and data-driven workflows on a scale never seen before. Consequently, an integration process among the different layers of complex systems and services has been unfolding raising significant issues and challenges in its wake. Hence, the digital data and collaboration spaces are all predicated upon the realisation of what is known as the computing continuum, which is based on the integration of cloud, edge and Internet of Things (IoT). Nevertheless, this has given rise to significant security and privacy risks especially since it is about systems that involve a high number of entities and devices with different profiles, processing a vast amount of potentially sensitive info MEDIATE’s vision is to produce a robust technology, which will address the security and privacy attributes of the computing continuum. For this, it will put forth a complex architecture that is based on the concept of zero-trust and will assume a federated learning approach in order to perform security-based scrutinisation at all continuum levels. i.e. IoT, edge and cloud, using security models that can be updated, redistributed and reconfigured across it. The actual features of the MEDIATE framework will support major topic outcomes such as cybersecurity resilience through reconfiguration, vulnerabilities mitigation through cyber threat analysis, secure integration at the IoT level through software and hardware-based security sensors and trust and security for massive ecosystems through the use of federated learning-based orchestration. Moreover, it will feature AI-based tools for cyber threat intelligence that assist a decision support system and privacy policies for data and identity protection.

We live in an era of information overload that impairs objective decision making, especially in time-sensitive contexts. Information Visualization (InfoVis) systems have been used to mitigate information overload, yet they have not yet unlocked their potential in critical decision-making scenarios. From emergency rooms and autonomous cars to operational command centres, a clear understanding and rapid assessment based on the available data can make the difference between life and death. SYMBIOTIK envisions an effortless interaction dialogue between human and InfoVis systems to support decision making processes, inspired by known biological principles and guided by artificial intelligence (AI). Critically, this dialogue requires AI solutions with context awareness, emotion sensing, and expressing capabilities. We propose a novel framework where both the human and the machine cooperate towards a common goal and evolve together. Awareness principles will allow us to engineer complex systems, making them more resilient and more human-centric. We will define an integrative approach for awareness engineering and propose a specific open source implementation. Finally, we will demonstrate and validate the role and added-value of such an awareness framework in two scenarios: supporting novice-to-expert transitions and critical decision making. The awareness principles to be developed in this project can support learning, adaptation, and self-development of intelligent systems over long periods of time, not only in the InfoVis domain. Therefore, SYMBIOTIK has potential to achieve the real breakthroughs needed to bring awareness and emotional intelligence for decision-making tasks in computing systems. The results of the project will benefit a range of stakeholders, from human vision and brain researchers, computer scientists, citizens, as well as research funding bodies and policy makers.