Low-code development platforms (LCPD) are software development platforms on the Cloud, provided through a Platform-as a-Service model, which allow users to build completely operational applications by interacting through dynamic graphical user interfaces, visual diagrams and declarative languages. They address the need of non-programmers to develop personalised software, and focus on their domain expertise instead of implementation requirements. Lowcomote will train a generation of experts that will upgrade the current trend of LCPDs to a new paradigm, Low-code Engineering Platforms (LCEPs). LCEPs will be open, allowing to integrate heterogeneous engineering tools, interoperable, allowing for cross-platform engineering, scalable, supporting very large engineering models and social networks of developers, smart, simplifying the development for citizen developers by machine learning and recommendation techniques. This will be achieved by injecting in LCDPs the theoretical and technical framework defined by recent research in Model Driven Engineering (MDE), augmented with Cloud Computing and Machine Learning techniques. This is possible today thanks to recent breakthroughs in scalability of MDE performed in the EC FP7 research project MONDO, lead by Lowcomote partners. The 48-month Lowcomote project will train the first European generation of skilled professionals in LCEPs. The 15 future scientists will benefit from an original training and research programme merging competencies and knowledge from 5 highly recognised academic institutions and 9 large and small industries of several domains. Co-supervision from both sectors is a promising process to facilitate agility of our future professionals between the academic and industrial world. re

REBECCA, a heavily SME-driven project, will democratize the development of novel edge AI systems. Towards this aim, REBECCA will develop a purely European complete Hardware(HW) and Software(SW) stack around a RISC-V CPU, which will provide significantly higher levels of a) performance (e.g., inferences per second), b) energy/power efficiency (e.g., inferences per joule/watt), c) safety and d) security than the existing ones. This will be achieved by utilizing state-of-the-art technologies and by making significant scientific and technological advances in several key relevant domains, including a) processing units, b) hardware accelerators, c) reconfigurable hardware, d) tightly coupled interconnected chiplets e) HW/SW co-design and co-development tools, f) system software, g) middleware, and h) AI libraries and frameworks. REBECCA will significantly contribute to realizing business and societal opportunities by validating and demonstrating its approach on 4 real-world use cases and 2 benchmarks based on real-world applications from the Smart appliances, Energy Generation, Infrastructure Inspection, Avionics Automotive and Health domains. In terms of HW, REBECCA will develop a novel chip consisting of two tightly coupled chiplets which will incorporate: a) RISC-V multicore, b) Neuromorphic AI Accelerator, c) Programmable array AI Accelerator, d) AI Accelerator utilizing a hierarchical processing architecture, e) DNN Accelerator, f) Reconfigurable hardware, g) Near-Memory-Processing, h) Memory Encryption. In terms of SW, REBECCA will implement optimized system SW, middleware, and AI libraries that will take full advantage of the underlying novel HW. The REBECCA platform will be complemented by a novel HW/SW Design Space Exploration tool which will allow the development of highly efficient REBECCA-based systems. REBECCA will additionally provide the means for safety and security modeling and verification for the developed HW and SW from the very early design stages.

There is an ever increasing complexity of the systems we engineer in modern society, which includes facing the convergence of the embedded world and the open world. This complexity creates increasing difficulty with providing assurance for factors including safety, security and performance - particularly for safety critical systems such as the transportation, aerospace and the industrial control domains. In this project we will focus on the following: • Safety/Security/Performance to be considered together, during the overall life cycle of our products. • Flexibility across domains. • Consolidate the industrial market by reducing costs and increasing system quality and maintaining compliance with more and more exacting standards. • Improved tool features and capabilities

European industry faces stiff competition on the global arena. Electronic Components and Systems become more and more complex, thus calling for modern engineering practices to be applied in order to better tackle both productivity and quality. Model-based technologies promise significant productivity gains, which have already been proven in several studies and applications. However, these technologies still need more enhancements to scale up for real-life industrial projects and to provide more benefits in different contexts. The ultimate objective of improving productivity, while reducing costs and ensuring quality in development, integration and maintenance, can be achieved by using techniques integrating seamlessly design time and runtime aspects. Industrial scale system models, which are usually multi-disciplinary, multi-teams and serving to several product lines have to be be exploited at runtime, e.g. by advanced tracing and monitoring, thus boosting the overall quality of the final system and providing lessons-learnt for future product generations. MegaM@Rt brings model-based engineering to the next level in order to help European industry reducing development and maintenance costs while reinforcing both productivity and quality. To achieve that, MegaM@Rt will create a framework incorporating methods and tools for continuous development and runtime validation to significantly improve productivity, quality and predictability of large and complex industrial systems. MegaM@Rt addresses the scalability challenges with advanced megamodelling and traceability approaches, while runtime aspects will be tackled via so-called “models@runtime”, online testing and execution traces analysis. MegaM@Rt brings together a strong international consortium involving experts from France, Spain, Italy and Finland. The partners cover the whole value chain from research organizations to tool providers, including 9 end-users with large industrial case studies for results validation.

SafeCOP (Safe Cooperating Cyber-Physical Systems using Wireless Communication) will establish a safety assurance approach, a platform architecture, and tools for cost-efficient and practical certification of cooperating cyber-physical systems (CO-CPS). SafeCOP targets safety-related CO-CPS characterized by use of wireless communication, multiple stakeholders, dynamic system definitions, and unpredictable operating environments. In this scenario, no single stakeholder has the overall responsibility over the resulted system-of-systems; safe cooperation relies on the wireless communication; and security and privacy are important concerns. Although such CO-CPS can successfully address several societal challenges, and can lead to new applications and new markets, their certification and development is not adequately addressed by existing practices. SafeCOP will provide an approach to the safety assurance of CO-CPS, enabling thus their certification and development. The project will define a platform architecture and will develop methods and tools, which will be used to produce safety assurance evidence needed to certify cooperative functions. SafeCOP will extend current wireless technologies to ensure safe and secure cooperation. SafeCOP will also contribute to new standards and regulations, by providing certification authorities and standardization committees with the scientifically validated solutions needed to craft effective standards extended to also address cooperation and system-of-systems issues. SafeCOP brings clear benefits in terms of cross-domain certification practice and implementations of cooperating systems in all addressed areas: automotive, maritime, healthcare and robotics. The advantages include lower certification costs, increased trustworthiness of wireless communication, better management of increasing complexity, reduced effort for verification and validation, lower total system costs, shorter time to market and increased market share.