The 2D Experimental Pilot Line (2D-EPL) project will establish a European ecosystem for prototype production of Graphene and Related Materials (GRM) based electronics, photonics and sensors. The project will cover the whole value chain including tool manufacturers, chemical and material providers and pilot lines to offer prototyping services to companies, research centers and academics. The 2D-EPL targets to the adoption of GRM integration by commercial semiconductor foundries and integrated device manufacturers through technology transfer and licensing. The project is built on two pillars. In Pillar 1, the 2D-EPL will offer prototyping services for 150 and 200 mm wafers, based on the current state of the art graphene device manufacturing and integration techniques. This will ensure external users and customers are served by the 2D-EPL early in the project and guarantees the inclusion of their input in the development of the final processes by providing the specifications on required device layouts, materials and device performances. In Pillar 2, the consortium will develop a fully automated process flow on 200 and 300 mm wafers, including the growth and vacuum transfer of single crystalline graphene and TMDCs. The knowledge gained in Pillar 2 will be transferred to Pillar 1 to continuously improve the baseline process provided by the 2D-EPL. To ensure sustainability of the 2D-EPL service after the project duration, integration with EUROPRACTICE consortium will be prepared. It provides for the European actors a platform to develop smart integrated systems, from advanced prototype design to small volume production. In addition, for the efficiency of the industrial exploitation, an Industrial Advisory Board consisting mainly of leading European semiconductor manufacturers and foundries will closely track and advise the progress of the 2D-EPL. This approach will enable European players to take the lead in this emerging field of technology.

Edge computing offers many technical advantages, e.g., reduced latency, secure decentralized processing and storage, scalability at lower complexity, versatility to adapt the changes in resources and applications, and increased reliability. Edge computing can dramatically boost services and applications by supporting artificial intelligence (AI) natively, instead of relying on the cloud. Edge computing supporting AI is the only technology that will enable many of the long-awaited game changers: Industry4.0 and smart manufacturing, 5G, IoT, self-driving vehicles, remote robotics for healthcare, and machine vision among others. The BRAINE project’s overall aim is to boost the development of the Edge framework focusing on energy efficient hardware and AI empowered software, capable of processing Big Data at the Edge, supporting security, data privacy, and sovereignty. The approach is to build a seamless Edge MicroDataCenter interlinked with AI enabled network interface cards. BRAINE employs a visionary utilization method for edge resources management and network-edge workload distribution. Predicting resource availability and workload demand, identifying trends, and taking proactive actions are all aspects of these novel methods. The impact of BRAINE encompasses advances in the European video distribution ecosystem, improving data processing at the network edge, and proving integrated AI for applications. These will lead to unprecedented savings in performance and energy efficiency: 2x performance/Watt and 50% energy savings; 71% latency reduction for an acceleration centric EMDC; 80% space and maintenance reduction, 99.999% fault tolerance with level 5 autonomy (autonomous driving, robotics, mission-critical system); and significantly faster infrastructure installation and deployment. BRAINE boosts EU’s position in the intelligent edge computing field and enables growth across many sectors, e.g., manufacturing, smart healthcare, surveillance, satellite navigation.

Border authorities and Law Enforcement Agencies (LEAs) across Europe face important challenges in how they patrol and protect the borders. Their work becomes more problematic considering the heterogeneity of threats, the wideness of the surveyed area, the adverse weather conditions and the wide range of terrains. Although there are several research tools and works targeting these areas independently for border surveillance, nowadays border authorities do not have access to an intelligent holistic solution providing all aforementioned functionalities. Towards delivering such a solution, ROBORDER aims at developing and demonstrating a fully-functional autonomous border surveillance system with unmanned mobile robots including aerial, water surface, underwater and ground vehicles, capable of functioning both as standalone and in swarms, which will incorporate multimodal sensors as part of an interoperable network. The system will be equipped with adaptable sensing and robotic technologies that can operate in a wide range of operational and environmental settings. To provide a complete and detailed situational awareness picture that supports highly efficient operations, the network of sensors will include static networked sensors such as border surveillance radars, as well as mobile sensors customised and installed on board unmanned vehicles. To succeed implementing an operational solution, a number of supplementary technologies will also be applied that will enable the establishment of robust communication links between the command and control unit and the heterogeneous robots. On top of this, detection capabilities for early identification of criminal activities and hazardous incidents will be developed. This information will be forwarded to the command and control unit that will enable the integration of large volumes of heterogeneous sensor data and the provision of a quick overview of the situation at a glance to the operators, supporting them in their decisions.

ICONET will significantly extend state of the art research and development around the PI concept in pursuit of a new networked architecture for interconnected logistics hubs that combine with IoT capabilities and aiming towards commercial exploitation of results. ICONET strives to achieve the end commercial goal of allowing shipments to be routed towards final destinations automatically, by using collaborative decisions inspired by the information centric networking paradigm, and optimizing efficiency and customer service levels across the whole network. According to this vision, cargo regarded as smart physical packets will flow between hubs based on ‘content’ of the cargo influencing key commercial imperatives such as cost, optimisation, routing, efficiency and advancing EU's Green agenda. Consequently, the consortium are discernibly aimed at three (3) avenues of commercialisation and exploitation from the ICONET innovation, specifically targeted in the areas of (a) Warehousing as a service, (b) E-commerce fulfillment as a service, and (c) Synchromodality as a service. PI based logistic configurations will be simulated, prototyped and validated in the project . Modelling and analysis techniques will be combined with serious game type simulation, physical and digital prototyping, using living lab (LL) requirements scenarios and data. With analyses and simulations, optimal topologies and distribution policies for PI will be determined. The project implementation will be based on a succession of phases of modelling and design/prototyping, learning and experimentation and feedback and interaction with the wider business community, including the ALICE logistics platform as well as members of the partner Associations ESC, UIRR and ELUPEG. Through its Living Labs, the project will address under the PI paradigm both Supply Network Collaboration and Supply Network Coordination.

The overall objective of the ROAM project is to investigate and demonstrate the use of the orbital angular momentum (OAM) modes of light for communications and networking. Two are the primary objectives. The firs objective is to exploit the use of OAM modes in optical fibres as a disruptive means of increasing optical fibre transmission capacity for short-reach high data density applications. A transmission testbed utilising OAM multiplexing and wavelength division multiplexing (WDM) dimensions will be demonstrated. The target will be a 10x or more capacity increase by employing 10 or more OAM multiplexed channels over a conventional WDM system. The combination of 10x OAM states with 16 wavelength channels will provide a total of 160 multiplexed channels. Full compatibility with legacy technologies will be demonstrated. Speciality fibres will be employed to support OAM modes transmission in the range up to 2 km. The second objective is to exploit the use of OAM domain as a switching resource in conjunctions with the wavelength domain to significantly improve the scalability and the power consumption of the switches in data-centres applications. A 10x improvement of the scalability of the data-centre switches will be targeted with the study and development of an OAM-based switch compatible with the WDM layer. A switch exploiting 10 OAM modes and 16 wavelengths as switching domains will be implemented. The developed two-layer switch will enable a more than 10x reduction of power consumption/Gb/s with respect to the current commercial switches. OAM switch configuration time of 100 ns will be demonstrated, with 8x improvement with respect to commercial switches. The project goals will be enabled by integrated high performance OAM components build on silicon photonics technology. ROAM consortium is composed by three universities, two research institutes, and two large companies, with the required knowledge and infrastructures to satisfy the project objectives.