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.

The overarching goal of BEYOND5 is to build a completely European supply chain for Radio-Frequency Electronics enabling new RF domains for sensing, communication, 5G radio infrastructure and beyond. BEYOND5 is first and foremost a technology project gathering most significant European actors covering the entire value chain from materials, semiconductor technologies, designs and components up to the systems. BEYOND5 will drive industrial roadmaps in More than Moore (MtM) in adding connectivity features on existing CMOS Technology. The ambition is to accomplish sustainable Radio Frequency SOI platforms to cover the frequency range from 0.7GHz to more than 100GHz, and to demonstrate the technical advantage of SOI, which allows combining large scale integration, low power consumption, cost competitiveness and higher reliability; thus, resulting in high volume production of trusted components with low environmental impact in Europe. This objective will be achieved in a “Time to Market” approach using the 3 major work streams: 1. Technology enhancement in three European industrial pilot lines: • 300mm RF SOI substrates pilot line in Soitec, supported by the “Substrate Innovation Center” in CEA LETI to prepare future generations. • RF-SOI 65nm pilot line for 5G FEM in ST addressing both sub-6GHz and 28GHz domains. • 22FDX pilot line addressing Digital Signal Processing of radio module and RF reliability, in GF 2. European RF design ecosystem strengthening, based on a large fabless community using FD-SOI and RF-SOI platforms 3. Six Leading edge systems aggregating the value chain to demonstrate added-value of the technology at the user level: • NB IoT for Smart Asset Tracking, • Contactless USB for high-data rate communication, • V2X for autonomous connected trucks, • 5G Low Power Digital Beamforming Base Station for Indoor dense spaces, • Automotive MIMO Radar with embedded AI, • Car Interior Radar for passenger monitoring.

5G-MOBIX aims at executing CCAM trials along x-border and urban corridors using 5G core technological innovations to qualify the 5G infrastructure and evaluate its benefits in the CCAM context as well as defining deployment scenarios and identifying and responding to standardisation and spectrum gaps. 5G-MOBIX will first define the critical scenarios needing advanced connectivity provided by 5G, and the required features to enable those advanced CCAM use cases. The matching between the advanced CCAM use cases and the expected benefit of 5G will be tested during trials on 5G corridors in different EU countries as well as China and Korea. Those trials will allow running evaluation and impact assessments and defining also business impacts and cost/benefit analysis. As a result of these evaluations and also internation consultations with the public and industry stakeholders, 5G-MOBIX will propose views for new business opportunity for the 5G enabled CCAM and recommendations and options for the deployment. Also the 5G-MOBIX finding in term of technical requirements and operational conditions will allow to actively contribute to the standardisation and spectrum allocation activities. 5G-MOBIX will evaluate several CCAM use cases, advanced thanks to 5G next generation of Mobile Networks. Among the possible scenarios to be evaluated with the 5G technologies, 5G-MOBIX has raised the potential benefit of 5G with low reliable latency communication, enhanced mobile broadband, massive machine type communication and network slicing. Several automated mobility use cases are potential candidates to benefit and even more be enabled by the advanced features and performance of the 5G technologies, as for instance, but not limited to: cooperative overtake, highway lane merging, truck platooning, valet parking, urban environment driving, road user detection, vehicle remote control, see through, HD map update, media & entertainment.

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.

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.