EdgeAI is as a key initiative for the European digital transition towards intelligent processing solutions at the edge. EdgeAI will develop new electronic components and systems, processing architectures, connectivity, software, algorithms, and middleware through the combination of microelectronics, AI, embedded systems, and edge computing. EdgeAI will ensure that Europe has the necessary tools, skills, and technologies to enable edge AI as a viable alternative deployment option to legacy centralised solutions, unlocking the potential of ubiquitous AI deployment, with the long-term objective of Europe taking the lead of Intelligent Edge. EdgeAI will contribute to the Green Deal twin transition with a systemic, cross-sectoral approach, and will deliver enhanced AI-based electronic components and systems, edge processing platforms, AI frameworks and middleware. It will develop methodologies to ease, advance and tailor the design of edge AI technologies by co-ordinating efforts across 48 of the brightest and best R&D organizations across Europe. It will demonstrate the applicability of the developed approaches across a variety of vertical solutions, considering security, trust, and energy efficiency demands inherent in each of these use cases. EdgeAI will significantly contribute to the grand societal challenge to increase the intelligent processing capabilities at the edge.

Silicon photonics is expected to leverage-off many of the advances made in CMOS electronics. International R&D efforts in this field have so far been mainly focused on the silicon-on-insulator (SOI) photonic integrated circuit (PIC) technology platform because it is predestined for datacom, high-performance computing and telecom applications. However, SOI based integrated optical waveguides cannot be used for the VIS/NIR <1.1µm wavelength region, which is important for life sciences and health related applications and, thus, offers a huge potential for PIC technology. To this end, a novel CMOS compatible low-loss silicon nitride waveguide based PIC technology platform will be developed in OCTCHIP and directly applied to the a strong business case in the field of optical coherence tomography (OCT) for ophthalmology. OCT is a revolutionizing in-vivo 3D imaging technique for non-invasive optical biopsy addressing medical needs with early diagnosis and reduction of healthcare cost. OCT has proven its value primarily in ophthalmology and cardiology but recently also in a variety of other medical fields. However, wide adoption has not taken place due to size and cost limitations as well as non-existence of miniaturized devices. The PIC technology developed in OCTCHIP will make a new generation of OCT systems possible with step-changes in size and cost beyond state-of-the-art. The monolithic integration of silicon nitride optical waveguides, silicon photodiodes and electronics combined with the hybrid integration of a III-V laser source will enable a compact, low-cost and maintenance free solution. OCTCHIP will contribute to radically transform OCT towards widespread adoption in point-of-care diagnostics for the early diagnosis of retinal pathologies, which are leading causes for blindness. The endeavor is strongly driven by company partners with strong expertise in the fields of silicon foundry process technology, miniaturized laser sources, and OCT system integration.

STREAM is a 4-year multi-site training network that aims at career development of Early Stage Researchers (ESRs) on scientific design, construction manufacturing and of advanced radiation instrumentation. STREAM targets the development of innovative radiation-hard, smart CMOS sensor technologies for scientific and industrial applications. The platform technology developed within the project will be tested in the demanding conditions posed by the CERN LHC detectors’ environment as well as European industry leaders in field of CMOS imaging, electron microscopy and radiation sensors. This leveraging factor will allow to fine-tune the technology to meet the requirements of industrial application cases on demand such as electron microscopy and medical X-ray imaging, as well as pathway towards novel application fields such as satellite environments, industrial X-ray systems and near-infrared imaging. The project will train a new generation of creative, entrepreneurial and innovative early-stage researchers and widen their academic career and employment opportunities. The STREAM consortium is composed of 10 research organisations and 5 industrial partners; the network will provide training to 17 ESRs. STREAM structures the research and training in four scientific work-packages which span the whole value-chain from research to application: CMOS Technologies Assessment, Smart Sensor Design and Layout, Validation and Qualification, Technology Integration, and Valorization.