VERGE will tackle evolution of edge computing from three perspectives: “Edge for AI”, “AI for Edge” and security, privacy and trustworthiness of AI for Edge. “Edge for AI” defines a flexible, modular and converged Edge platform that is ready to support distributed AI at the edge. This is achieved by unifying lifecycle management and closed-loop automation for cloud-native applications, MEC and network services, while fully exploiting multi-core and multi-accelerator capabilities for ultra-high computational performance. “AI for Edge” enables dynamic function placement by managing and orchestrating the underlying physical, network, and compute resources. Application-specific network and computational KPIs will be assured in an efficient and collision-free manner, taking Edge resource constraints in to account. Security, privacy and trustworthiness of AI for Edge are addressed to ensure security of the AI-based models against adversarial attacks, privacy of data and models, and transparency in training and execution by providing explanations for model decisions improving trust in models. VERGE will verify the three perspectives through delivery of 7 demonstrations across two use cases - XR-driven Edge-enabled industrial B5G applications across two separate Arçelik sites in Turkey, and Edge-assisted Autonomous Tram operation in Florence. VERGE will disseminate results to academia, industry and the wider stakeholder community through liaisons and contributions to relevant standardization bodies and open sources, a series of demonstrations showing progression through TRLs and by creating an open dataspace for enabling public access to the datasets generated by the project.

Nowadays there is a shared vision among industry, operators and academy that 5G wireless networks will have to provide wideband wireless access and ubiquitous computing anywhere and at any time. The human life of the majority of the EU citizens will be surrounded by intelligent wireless sensors, which will bring radical changes to the way we live and do things. Supporting this scenario is a challenge for network operators and wireless network infrastructures and it will demand a tremendous performance improvement of medium range wireless infrastructure. This challenge needs to be addressed by a convergence of advanced semiconductor nanotechnology and a robust wireless infrastructure based on meshed networks with seamless fiber performances. The DRAGON project, through the exploitation of the radio spectrum in D-band (130-174.8 GHz) , will overcome the constraints of current E-band wireless backhaul solutions to achieve a small-form factor and high-capacity radio solution, suitable for massive deployment, that will enable bringing the speed of optical systems to backhaul systems in a cost effective way. The DRAGON project vision and objectives rely on a power efficient and silicon based BiCMOS transceiver analog front end, operating in D-band and enabling cost efficient deployment of telecommunications networks with seamless fiber performance. A beam steering integrated antenna array using an intelligent low-cost packaging technology will be developed for the implementation of the 5G network demo trial on field, with fine beam alignment for facilitating the installation and compensating pole vibration. The DRAGON consortium has a well-balanced and complementary know-how in the relevant areas for designing and demonstrating the feasibility of a small cell cellular network architecture based on meshed D-band backhaul links. DRAGON will therefore secure Europe’s industrial leadership and pave the way towards innovative 5G telecommunications networks.

The significance of migration as a social, political and broader public concern has intensified significantly. Migration is increasingly seen as a high-priority policy issue by many governments, politicians and throughout the world. As well as migration projections and scenarios that are essential for appropriate planning and effective policymaking, a deeper understanding of the root causes and drivers of migration and of their interrelation with people’s propensity to migrate is needed. Enhancing migration data is a crucial step to advance migration governance since better data is needed in order to accomplish sustainable social and economic development and national migrant data strategies are required to inform good policies. The project’s overall objective is to improve understandings of changing nature of migration flows and the drivers of migration, to analyse patterns, motivations and new geographies. Moreover, HumMingBird aims to calculate population estimates and determine emerging trends and future trends and accordingly to identify possible future implications of today’s policy decisions. Correspondingly, migration scenarios will be developed in a more forward looking manner that takes into account both quantitative and qualitative perspectives of different migration actors that might have an impact people’s decisions to migrate and consequent trends that will have an impact on our societies. Global scenarios will base on not only a realistic understanding of the drivers and dynamics of migration but also on the effects and effectiveness of past migration policies. Projects ambitions are to identify the uncertainties and reappraise, to explore the reasons why migration predictions may not hold and to demonstrate non-traditional data sources for migration research.

Over the last years, the importance and need for broadband and high-speed connectivity has constantly increased. The Covid-19 pandemic has even accelerated this process towards a more connected society. But this holds mainly true for urban communities. In Europe a 13% lack access still persists, and mainly concerns the most rural and remote areas. Those are the most challenging to address since they are the least commercially attractive. COMMECT aims at bridging the digital divide, by providing quality, reliable, and secure access for all in rural and remote areas. The goal of extending broadband connectivity in rural and remote areas will be achieved by integrating Non-Terrestrial Networks with terrestrial cellular XG networks, and low-cost Internet of Things (IoT). Artificial Intelligence, Edge and Network Automation will reduce energy consumption both at connectivity and computing level. Participatory approach with end-users and ICT experts working together on development challenges will be the key for the digitalization of the sector. To ensure the rich exchange of best-practice and technical knowledge among the actors of the agro-forest value chain, COMMECT will set up five Living Labs across and outside Europe, where end-users pain and (connectivity) gains will be largely discussed, from different perspectives. COMMECT aims at contributing to a balanced territorial development of the EUs rural areas and their communities by making smart agriculture and forest services accessible to all. COMMECT will facilitate that, by developing a decision-making support tool able to advise on the best connectivity solution, according to technical, socio-economic, and environmental considerations. This tool, incorporating collaborative business models, will be a key enabler for jobs, business, and investment in rural areas, as well as for improving the quality of life in areas such as healthcare, education, e-government, among others.

The main objective of the storAIge project is the development and industrialization of FDSOI 28nm and next generation embedded Phase Change Memory (ePCM) world-class semiconductor technologies, allowing the prototyping of high performance, Ultra low power and secured & safety System on Chip (SoC) solutions enabling competitive Artificial Intelligence (AI) for Edge applications. The main challenge addressed by the project is on one hand to handle the complexity of sub-28nm ‘more than moore’ technologies and to bring them up at a high maturity level and on the other hand to handle the design of complex SoCs for more intelligent, secure, flexible, low power consumption and cost effective. The project is targeting chipset and solutions with very efficient memories and high computing power targeting 10 Tops per Watt. The development of the most advanced automotive microcontrollers in FDSOI 28nm ePCM will be the support technology to demonstrate the high performances path as well as the robustness of the ePCM solution. The next generation of FDSOI ePCM will be main path for general purpose advanced microcontrollers usable for large volume Edge AI application in industrial and consumer markets with the best compromise on three requirements: performances, low power and adequate security. On top of the development and industrialization of silicon process lines and SoC design, storAIge will also address new design methodologies and tools to facilitate the exploitation of these advanced technology nodes, particularly for high performance microcontrollers having AI capabilities. Activities will be performed to setup robust and adequate Security and Safety level in the final applications, defining and implementing the good ‘mixture’ and tradeoff between HW and SW solutions to speed up adoption for large volume applications.