CLEVER proposes a series of innovations in the area of hardware accelerators, design stack, and middleware software that revolutionize the ability of edge computing platforms to operate federatedly, leveraging sparse resources that are coordinated to create a powerful swarm of resources. CLEVER technologies will support the deep edge computing paradigm, moving computing services closer to the end user or the source of the data to reduce power consumption, reduce capacity requirements, and latency for mission critical applications. Furthermore, CLEVER will overcome traditional limitations of edge computing in terms of limited resource availability by providing an effective framework for seamless use of federated resources in the edge-cloud continuum. CLEVER will demonstrate processing solutions for AI at the edge through four use cases: (1) digital twin for in-factory optimization, (2) smart agriculture for high yield eco-farms, (3) fully automated material deployment, and (4) augmented reality for shopping sites. Through the achievement of its goals, the CLEVER project will help to position Europe at the forefront of the intelligent edge computing field, enabling growth across many sectors (manufacturing, agriculture, smart environments, augmented reality, and others). By lowering the barriers for utilising edge computing for artificial intelligence applications, CLEVER will open the door for European Industries and SMEs to leverage state of the art technologies, driving their development and growth as leaders in their sectors.

The Internet of Things (IoT) brings opportunities for creating new services and products, reducing costs for societies, increasing the service level for the citizens in a number of areas, and changing how services are sold and consumed. Despite these opportunities, current information system architectures create obstacles that must be addressed for leveraging the full potential of IoT. One of the most critical obstacles are the ‘vertical silos’ that shape today’s IoT because they constitute a serious impediment to the creation of cross-domain, cross-platform and cross-organisational applications and services. Those silos also hamper developers from producing new added value across multiple platforms due to the lack of interoperability and openness. bIoTope provides the necessary Standardized Open APIs for enabling horizontal interoperability between silos. Such horizontal interoperability makes it possible to develop Systems of Systems where cross-domain information from platforms, devices and other information sources can be accessed when and as needed. bIoTope-enabled Systems can seamlessly exploit all available information, which makes them smart in the sense that they can take or propose the most appropriate actions depending on the current User’s or Object’s Context/Situation, and even learn from experience. bIoTope capabilities lay the foundation for open innovation ecosystems where companies can innovate both by the creation of new software components for IoT ecosystems, as well as create new Platforms for Connected Smart Objects with minimal investment. Large-scale pilots implemented in smart cities will provide both social, technical and business proofs-of-concept for such IoT ecosystems. This is feasible because the bIoTope consortium combines unique IoT experience, commercial solution providers and end-users, thus ensuring the high quality and efficiency of the results and implementations.

Edge computing offers many technical advantages, e.g., reduced latency, secure decentralized processing and storage, scalability at lower complexity, versatility to adapt the changes in resources and applications, and increased reliability. Edge computing can dramatically boost services and applications by supporting artificial intelligence (AI) natively, instead of relying on the cloud. Edge computing supporting AI is the only technology that will enable many of the long-awaited game changers: Industry4.0 and smart manufacturing, 5G, IoT, self-driving vehicles, remote robotics for healthcare, and machine vision among others. The BRAINE project’s overall aim is to boost the development of the Edge framework focusing on energy efficient hardware and AI empowered software, capable of processing Big Data at the Edge, supporting security, data privacy, and sovereignty. The approach is to build a seamless Edge MicroDataCenter interlinked with AI enabled network interface cards. BRAINE employs a visionary utilization method for edge resources management and network-edge workload distribution. Predicting resource availability and workload demand, identifying trends, and taking proactive actions are all aspects of these novel methods. The impact of BRAINE encompasses advances in the European video distribution ecosystem, improving data processing at the network edge, and proving integrated AI for applications. These will lead to unprecedented savings in performance and energy efficiency: 2x performance/Watt and 50% energy savings; 71% latency reduction for an acceleration centric EMDC; 80% space and maintenance reduction, 99.999% fault tolerance with level 5 autonomy (autonomous driving, robotics, mission-critical system); and significantly faster infrastructure installation and deployment. BRAINE boosts EU’s position in the intelligent edge computing field and enables growth across many sectors, e.g., manufacturing, smart healthcare, surveillance, satellite navigation.

The main objective of the iDev40 project proposal is to achieve a disruptive or “breakthrough change” step toward speedup in time to market by digitalising the European industry, closely interlinking development processes, logistics and manufacturing. Ultimately, the project aims at suitable digital technology advancements to strengthen the electronic components and systems industry in Europe. It addresses various industrial domains with one and the same approach of digitalisation towards competitive and innovative solutions. The new concept of introducing seamlessly integrated development together with automation and network solutions as well as enhancing the transparency of data, their consistence, flexibility and overall efficiency will lead to a significant speedup in the time to market (T2M) race. iDev40’s unique approach addresses: • AI learning, Data Life Cycle Management and IP Protection • Embedding Digital Development in Digital Production (the digital twin) • Close the Knowledge loop in product life cycle management along the supply chain • Collaboration 4.0 and Development of highly skilled R&D and Manufacturing Teams • Prove the innovated technologies on selected use cases in real productive environment Progress in mastering these challenges will significantly impact the productivity of future design processes embedded in an Industrial Internet environment. The global state-of-art technologies already offer tremendous diagnostics algorithms, machine controls, simulators, optimizers, etc., but only an extensive framework like iDev40 can combine them into effective integration into the development process enabling such powerful simulations like “digital twins” that ever more govern the hardware, manufacturing service and business functions. To cope with the exceptional complexity it becomes even more crucial to be competitive leaders in developing virtual representations of real physical implementation.