Manufacturing, construction, and agriculture are major driving forces for the European economy and prosperity. Maintaining its competitiveness in these sectors demands highly efficient and flexible processes, and this can be achieved through digitization. Novel intelligent robotic capabilities that can be deployed side-by-side with humans and can operate and adapt to dynamic environments can accelerate this process. However, existing robotic systems cannot fit well into such settings as they are not versatile and flexible enough to automate certain tasks, cannot collaborate safely with humans in open and dynamic environments, nor are they easily and economically adaptable to process changes. The SOPRANO project coalesces multidisciplinary research and innovation in human-robot collaboration and intelligent multi-agent systems, aspiring to design the next generation of manufacturing floors, construction sites, and agri-food production, where humans and intelligent machines will seamlessly work together. It proposes to scale collaboration from the single human-agent dyad to a peer-based synergy between multiple interconnected robotic systems featuring different physical and cognitive properties, supporting various tasks in collaboration with human workers, robotics and other agents. SOPRANO will validate the technological offering in three novel and open-access use cases addressing both large-scale industries and small to medium enterprises, adding value to EU key sectors and instrumenting community building surrounding the open-source technologies in the EU industrial ecosystem. During the project, we will also enable external SMEs and start-ups to benefit from the project technologies via an open call, which will enable the building of demonstrators using SOPRANO technologies that will open new market opportunities for their products and services.

The overall goal of the SECURED project is to scale up multiparty computation, data anonymization and synthetic data generation, by increasing efficiency and improving security, with a focus on private and unbiased artificial intelligence and data analytics, health-related data and data hubs, and cross-border cooperation. The project will address the limitations that are currently preventing the widespread use of secure multiparty computation and effective anonymization, namely: the limited practical capabilities of current cryptographic schemes for secure multi-party computation protocols, and their performance; the lack of well understood and standardized data anonymization methods for health data; the absence of dynamic and on demand services for generating synthetic data; the complex and ad-hoc nature of current federation protocols for machine learning and AI-based data analytics; the lack of support for health technology providers to implement privacy enhancing technologies, in particular SMEs. SECURED will tackle these challenges by focusing on scaling up privacy technologies via algorithmic improvements and implementation efficiency (HW and SW), as well as the generalization of primitives and definitions, with the aim of speeding up and facilitating privacy preserving data-driven tools and services for wellbeing, prevention, diagnosis, treatment and follow-up care. SECURED will also analyse the current ethical and legal challenges to data sharing, and is targeted at overcoming current limited adoption of advanced multi-party computation and data anonymization technologies by providing direct support to health technology SMEs through a funding call. To ensure relevance to real-world settings, SECURED will showcase the technologies developed in four health-related use cases provided by partner hospitals and health stakeholders, namely: real-time tumor classification; telemonitoring for children; synthetic data generation for education; access to genomic data.

Current evidence from both randomized trials and real-world evidence studies suggests that older breast cancer patients derive clinical benefit from the addition of CDK 4/6-inhibitors to endocrine therapy but with higher risk for adverse events and treatment discontinuation compared to younger patients. The IMPORTANT project will design and conduct a pragmatic clinical study with a decentralised approach for older patients with advanced breast cancer aiming at high level of evidence (level I) with multi-layer results that can enable changes in current clinical practice. This study will be conducted across 6 (six) EU countries, and will include more than 500 female and male patients. The project will also perform a series of analyses over a) a wide range of clinical-relevant primary and secondary endpoints targeting to contribute to current clinical practice and b) the implementation of specific strategies aiming at more individualized treatment and follow-up approaches to a clinical trial setting that highly resembles real-world setting due to the trial's pragmatic design. The project will be developed in 60 months by a competitive consortium of 19 partners from 11 countries, which corresponds to a well-balanced structure, involving clinical sites, SMEs, universities and patient advocacy organizations. Despite the great diversity of entities within the proposal, IMPORTANT partners bring state-of-the-art complementary skills ensuring the ability of the consortium to successfully complete the proposed work.This action is part of the Cancer Mission cluster of projects on ‘Diagnosis and treatment’.

AI4Work will investigate practical methods and tools for optimal sharing of work between humans and AI/robots. AI and robotics are likely to be most powerful means for radical improvement of working conditions in diverse domains, as they can support human operators in diverse tasks starting from difficult and tedious manual labor tasks up to complex decision-making tasks. The vision of the AI4Work project is to improve communication and collaboration between humans, AI and robots, allowing for an improvement of the working conditions within different processes in organisations in several domains in terms of increased efficiency of work, reduction in stress upon employees, increased confidence in decision-making process etc. Due to the high level of uncertainty in modern organisations an appropriate balance between human and machine activities must be found. The key assumption is that to cope with the required flexibility and dynamics, Sliding Work Sharing (SWS), where this balance varies during the operation depending on the situational context, machine-based confidence levels and human interactions, is likely to be the most appropriate for modern organisations. The key challenge of the project is to develop a set of common methods and tools (methodology framework, digital twin service platform, SW building blocks for SWS) that can be applied in diverse sectors and with different AI/robotics services, allowing for an effective experience exchange. The project will make use of living digital twins of working systems as a mean to increase efficiency and trustworthiness of AI/robotics solutions. By this, the project, aiming at improved quality of jobs and creating more decent work for human operators, will contribute to the acceptance of the AI/robots support of work in diverse domains. The project will be driven by six pilots in different sectors: logistics, manufacturing industry, construction, healthcare, education and agriculture.

Cybersecurity certification as introduced by the EU Cybersecurity Act (EUCSA) will play a crucial role in increasing the trust to and security of ICT Products, ICT Services and ICT Processes. Cybersecurity certification is a complex process, posing a variety of challenges to the different interested parties. This proposal introduces the CUSTODES, a system comprised of a variety of components with the aim to provide trustworthy, cost-effective, agile and portable conformity assessment capabilities, to a variety of interested parties, covering multiple Assurance levels of Composite ICT products or ICT services. The CUSTODES system will discover and translate certification information of the Building Blocks of the composite ICT products or Services under evaluation, will provide Certification information to the interested parties and will share information on newly identified vulnerabilities related to the specific blocks or composite products as needed increasing transparency, re-usability and trust. It will also utilize a Restricted & Trusted Execution (RTE) Environment, to ensure the chain of custody of the product under assessment. CUSTODES will be validated in three pilots, a) one of two Class I composite products with digital elements, b) one of an ICT product with an embedded AI component and c) a final one of the as-a-service functionality through EIT Digital extensive digital ecosystem. The CUSTODES project is built on a collaboration of 17 organisations from 11 EU member states and third countries. The Consortium which includes 3 Conformity Assessment Organizations is composed by 10 SMEs, 3 large industry partners, 2 research organizations, and 2 public organizations/associations. The Consortium is led by RISE which has extensive experience in national and European research projects, and numerous collaborations with industrial partners.