Towards the forthcoming transition to a fully connected world (e.g., Internet of Senses, digital twins), support of connected intelligence requires service advertisement, discovery, negotiation and management that goes beyond the complexity and scalability that existing technologies and subscription-driven MNO processes can handle. In Beyond 5G (B5G) networks, cyber-physical assets and intelligent end points will be capable of translating current service requirements to comprehensive technical specifications dynamically (e.g., QoS/QoE management per service chunk) as well as request for full customization of their service terms in line with current availability of tenants/resources and their application requirements. Distributed ledger technologies (DLTs) hold the key for natively disintermediated, cost-efficient, and anonymous B5G communications, enabling transparency and trust to be established across the integrated DLT, radio access and core network continuum. The SOVEREIGN research programme aims to fuel artificial intelligence (AI) with DLT-backed data in order to innovate the B5G service chain and the B5G protocol stack towards the support of fully decentralized, instantaneous, and anonymous resource trading across the B5G network ecosystem (end terminals, infrastructure, OTT service providers, etc.). SOVEREIGN aims to empower intelligent end points in B5G networks, to gain full control of their identities, connectivity, sessions, service terms, and shared data upon accessing B5G spectrum, antennas, network slices and services. To this end, SOVEREIGN will conceptualize and develop a modular end-to-end service architecture integrating DLT-empowered service provisioning, fully decentralized AAA operations, forward-thinking protocols for self-sovereign identity management and anonymity/data privacy preservation as well as user-driven AI-enabled mobility management and traffic steering over joint DLT/B5G system infrastructures.

Urban water management becomes progressively more challenging in the view of population growth and increasing complexity of water management infrastructure. In this line, there is an ever increase demand from the water providers’ and public authorities’ perspective to critically evaluate the existing water ecosystems at city level in respect to the water supply, waste water treatment, reuse potential and the effect the growing population has on the water ecosystem and endangered species. To enable effective decision making at the entire city level, both surface water and groundwater should be viewed as part of the overall urban water ecosystem with its spatio-temporal availability, quantity and quality and competing uses being taken into account. The Water4Cities project will rely on sensor technologies, data and visual analytics to enable localization, visualization and analysis of urban water (both surface water and groundwater) at a holistic urban setting providing services to multiple water stakeholders. More specifically, the Water4Cities project aims to develop the necessary models and associated platform that will enable water providers and relevant stakeholders to a) monitor in real-time the urban water resources; b) support their decisions for optimal urban water management causing minimal environmental impact and c) involve policy makers, corporations and the public to provide the support for sound and balanced decision-making. Beyond the scientific results, Water4Cities will target the exchange of knowledge among project partners. The Water4Cities project requires the collaboration of researchers in different research areas, i.e., water management, urban infrastructure management, sensor networks, data mining, data visualization, system integration, urban planning. Due to the multi-disciplinary nature of the project, staff exchanges will allow partners working closely together to deliver high quality results.

As the world moves from the 5G towards the 6G era, the mobile communications fabric needs to be architected differently to accommodate the emerging stringent requirements of innovative extreme future-looking applications that cannot be served by existing 5G mobile networks. Heading towards the next decade, when 6G is expected to be widely deployed, 5G application types will be redefined by morphing the classical service classes of URLLC, eMBB, and mMTC and introducing new services. ADROIT6G is an SNS JU project supporting the EC’s 6G policy by implementing the first phase of the 6G SNS roadmap towards the evolution of a 6G architecture. ADROIT6G proposes disruptive innovations in the architecture of emerging 6G mobile networks that will make fundamental changes to the way networks are designed, implemented, operated, and maintained. Such innovations include: (i) AI/ML-powered optimizations across the entire network, for high performance and automation; (ii) Transforming to a fully cloud-native network software, which can be implemented across a variety of edge-cloud platforms, including Non-Terrestrial Networks, with security built integrally into the network user plane; (iii) Software driven, zero-touch operations and ultimately automation of every aspect of the network and the services it delivers. ADROIT6G innovations, functionalities and performance will be validated through 3 representative extreme 6G use cases (i.e., holographic telepresence, Industrial IoT, collaborative robots/drones) in corresponding PoCs over five well-established 5G testbeds, which will be upgraded to support ADROIT6G innovations and architectural elements. Our 13-partner consortium is driven by industry heavyweights from EU telecom and ICT industries and renowned research organisations, with a vast expertise and experience in 5G and beyond technologies. Most of ADROIT6G’s consortium partners have participated in 44 previously funded 5G-PPP projects and in several 5G-PPP Working Groups.

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.

5G adv. and 6G aim to expand the set of supported verticals and provide enhanced capabilities beyond connectivity. 5G CAM vertical services are a broad range of services in and around vehicles, including both safety-related and other services enabled or supported by 5G. 5GS has been built as a modular architecture to support any vertical running on top in a vertical-agnostic manner. However, it is realized that certain verticals (like CAM) have specific and strict requirements. Although significant progress has been made in supporting verticals, the corresponding necessary configuration of the network and end-devices is a time-consuming manual process that requires tight coordination at technical and business levels across the verticals, the vendors, the network operator, and even the end-users. This hinders not only the greater adoption of 5GS but also the uptake of novel CAM UCs and the modernization of existing ones that require a tighter integration with the underlying network. The main objective of ENVELOPE is to advance and open up the reference 5G adv. architecture, and also to transform it into a vertical-oriented with the necessary interfaces tailored to the CAM UCs that i) expose network capabilities to verticals, ii) provide vertical-information to the network; iii) enable verticals to dynamically request and modify certain network aspects in an open, transparent and easy to use, semi-automated way. ENVELOPE aims to deliver 3 large-scale B5G trial sites in Italy, Netherlands and Greece for CAM services and beyond, implementing functionalities tailored to the CAM services and advanced exposure capabilities. Although focused on the CAM vertical, the resulting developments will be reusable by any vertical. The ENVELOPE architecture will serve as an envelope that can cover, accommodate and support any type of vertical services. The applicability of ENVELOPE capabilities will be demonstrated via the project CAM UCs and via at least 9 open call projects.