SHASAI targets the HW/SW security and AI-based high risk systems intersection, aiming to enhance the security, resilience, automated testing, and continuous assessment of AI systems. The rising interest in these systems makes them attractive targets for threat actors due to their complexity and valuable data. Ensuring the security of AI systems involves safeguarding AI models, datasets, dependencies, and securing the underlying HW/SW infrastructure. SHASAI takes a holistic approach of AI system security throughout their lifecycle stages. At requirement definition, SHASAI provides an enhanced risk assessment methodology for secure and safe AI. At design, SHASAI will propose secure and safe design patterns at SW and HW level to achieve trustworthy AI systems. During implementation, SHASAI provides tooling for a secure supply chain of the system by analyzing vulnerabilities in SW / HW dependencies, detecting poisoned data and backdoors in pretrained models, scanning for software vulnerabilities, hardening hardware platforms, and safeguarding intellectual property. At evaluation, SHASAI offers a virtual testing platform with automated attack and defense test suites to assess security against AI and infrastructure-specific threats. In operation, AI-enhanced security services continuously monitor the system, detect anomalies, and mitigate attacks using AI firewalls and attestation methods, ensuring availability and integrity. The feasibility of SHASAI methods and tools will be demonstrated in 3 real scenarios: 1. Agrifood industry: Cutting machines. 2. Health: Eye-tracking systems in augmentative and alternative communication. 3. Automotive: Tele-operated last mile delivery vehicle. Their heterogeneity and complementarity maximize the transferability of solutions. SHASAI will contribute to scientific, techno-economic, and societal impacts as it aligns with the CRA, EU AI Act, NIS2 and CSA, sharing and commercializing methods and tools to ensure trustworthy AI components.

MOSAIC addresses a grand challenge for European competitiveness: technological independence and filled fabs in the landscape of automated systems. By fostering innovation in Electronic Components and Systems (ECS), MOSAIC aims to propel Europe to excellence and digital autonomy, directly linked to the EU Chips Act. The project achieves this through a comprehensive strategy. It will develop next-generation ECS offering superior, cognitive system intelligence, enabling energy efficiency and robustness. These results will be tailored to the demands of automated systems, enabling rapid data processing and intuitive, AI-enabled decision- making. MOSAIC tackles the challenge of integrating diverse perception hardware configurations, ensuring that automated systems can perceive their surroundings in a non-invasive manner, avoiding a single point of failure, with unparalleled accuracy and decreased complexity. Additionally, the project emphasizes standardized communication protocols and interoperability, fostering a collaborative ecosystem across several industries, namely automotive, aerospace, maritime, industrial automation and infrastructures. By spearheading such advancements, MOSAIC empowers European ECS manufacturers to gain a competitive advantage. The project's achievements will be demonstrated in 31 cutting-edge technical showcases, indicatively global perception through 360° distributed radar, AI-enabled reasoning through magnetic field signature and resilient communications by means of non-terrestrial networks. 2 accompanying impact studies, will solidify Europe's position as a global leader in automated systems. MOSAIC leverages a pan-European consortium encompassing the entire ECS value chain, ensuring a comprehensive effort towards filling the European fabs and ensuring digital sovereignty. In essence, MOSAIC is an investment in Europe's future – a secure digital future of technological leadership, economic prosperity, and strategic independence.

While Fully electric vehicles (EV) have zero tailpipe emissions and are seen as a key solution to meeting the European Fit-for-55 target of reducing CO2 levels in 2030 and climate-neutrality by 2050, much more can be potentially achieved if the global market uptake of innovative EVs is accelerated. The ZEV-UP project aims to address this urgent need by developing modular, cost-effective, and user-centric EVs for both passenger and goods transportation. Leveraging innovative design and engineering techniques, ZEV-UP vehicles will be tailored to meet the specific needs of users in both developed and emerging markets, ensuring high levels of user acceptance and market uptake. Key innovations include a base L7e BEV model that is designed respectful of affordability and can be upgraded and adapted for various purposes and needs, including commercial applications and higher-value passenger vehicles. By optimizing vehicle components for reduced material usage and enhanced structural properties, the project will achieve lighter vehicles with increased autonomy and minimized environmental impact. ZEV-UP will also develop digital-twin models to improve vehicle development efficiency and reduce validation costs, as well as designing charging capabilities compatible with a variety of regional power systems. Novel business and usage models, such as Battery as a Service, will be explored to maximize the benefits and impact of the L7e BEV platform. User-centric design, informed by market research and field interviews in both established and developing countries, will be a central focus of the project. Additionally, ZEV-UP will develop a proliferation model to assess policy intervention scenarios and strategize for short- and long-term BEV uptake in various markets. By delivering these key results and adhering to its objectives, ZEV-UP will accelerate the transition to sustainable urban mobility and contribute to the reduction of greenhouse gas emissions in the transport sector.

The Shift2SDV project aims to revolutionize the European automotive domain by creation of an SDV ecosystem around middleware & API framework enabling collaboration across the automotive value chain. This ambitious endeavour envisions a comprehensive shift towards a modular framework that transcends the limitations of current monolithic systems, fostering agility and innovation through the development of complementary middleware services and software development solutions. Central to Shift2SDV is the development of a cutting-edge middleware framework that provides micro-services to build automotive applications upon, abstracting from underlying hardware components – supporting stepwise migration, open source and proprietary components, in-vehicle safety critical and off-vehicle cloud functionality. It is specifically designed to streamline software development and integration while ensuring compatibility and flexibility with existing and emerging technologies. Key technical objectives include the development of a modern, flexible micro-services-based architecture, middleware framework that simplifies the brand-specific application development, and establishment of a safe and secure system architecture compliant with functional safety standards. Additionally, the project aims to develop an orchestration for efficient resource management, integrate edge and cloud computing, and demonstrate the practical viability of the developed middleware through concrete use cases. To maximize impact, Shift2SDV prioritizes active communication, dissemination, and exploitation of project outcomes, fostering collaboration among stakeholders and existing projects and initiatives aligning technological advancements with market demands. Through these concerted efforts, Shift2SDV seeks to propel European leadership in Software Defined Vehicles, driving innovation and economic growth in the automotive industry.

EdgeAI-trust aims to develop a domain-independent architecture for decentralized edge AI along with HW/SW edge AI solutions and tools, which enable fully collaborative AI and learning at the edge. The edge AI technologies address key challenges faced by Europe's industrial and societal sectors such energy efficiency, system complexity and sustainability. EdgeAI-trust will enable large-scale edge AI solutions that enable interoperability, upgradeability, reliability, safety, security and societal acceptance with a focus on explainability and robustness. Toolchains will provide standardized interfaces for developing, optimizing and validating edge AI solutions in heterogeneous systems. The generic results will be instantiated for automated vehicles, production and agriculture, thus offering innovation potential not only in the generic HW/SW technologies and tools, but also in the three target domains. These technological innovations are complemented with business strategies and community building, ensuring the widespread uptake of the innovations in Europe. EdgeAI-trust will establish sustainable impact by building open edge AI platforms and ecosystems, with a focus on standardization, supply chain integrity, environmental impact, benchmarking frameworks, and support for open-source solutions. The consortium consists of major suppliers and OEMs encompassing a broad range of application domains, supported by leading research and academic organizations. By embracing the opportunity to specialize in Edge AI, Europe can maintain its position in the global context, especially as it aligns with decentralized and privacy-driven European policy. Furthermore, as AI is closely connected with the Green Deal, this project can provide proper solutions for environmental issues. Ultimately, the project will enable AI to be connected with other strong sectors and industries, improving the innovation process and decision-making in Europe.