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Antmicro Ltd

Country: Poland
4 Projects, page 1 of 1
  • Funder: EC Project Code: 645560
    Overall Budget: 1,224,380 EURFunder Contribution: 991,688 EUR

    AXIOM introduces the first professional, extendable, affordable and modular cinema camera platform based on Free Software, Open Design, Open Hardware, transparent development processes and extensive documentation. The project establishes an ecosystem that offers a sustainable basis for a broad spectrum of audiovisual applications and empowers enthusiasts, videographers as well as developers in the technology and creative industry sectors. AXIOM is not meant to be just one fixed product but rather an open platform stimulating the collaboration of the creative industry with a viable ecosystem for innovative (value-added) products and services. The project aims to show a best-practice example in European Open Hardware development and documentation. There is no comparable product on the market yet. AXIOM targets the demand for emerging technologies in the creative industry and imaging sectors (eg. cinema, broadcast, science or medical use): high-resolution (4K), high frame-rate (HFR), global shutter, open design (Open Hardware, FLOSS), modular system, using only open standards. AXIOM is a project of ground-breaking nature. We are expecting the project to be a best-practice-example, with very high potential to disrupt the creative industries in the imaging and video sectors. AXIOM is: -) a system between industrial and high end digital cinema camera, for a fraction of the price -) highly modular: customizable (software, hardware, FPGA) -) using open standards exclusively The proposed action includes prototyping, testing, demonstrating and piloting the AXIOM Open Integrated Modular Cinema Camera dubbed "AXIOM Gamma". AXIOM will be presented at the international M.I.T. Open Hardware Summit 2015, research data and results will be released under a free licence.

  • Funder: EC Project Code: 957197
    Overall Budget: 7,996,650 EURFunder Contribution: 7,996,650 EUR

    The ever increasing performance of computer systems in general and IoT systems, in particular, delivers the capability to solve increasingly challenging problems, pushing automation to improve the quality of our life. This triggers the need for a next-generation IoT architecture, satisfying the demand for key sectors like transportation (e.g. self-driving cars), industry (e.g. robotization or predictive maintenance), and our homes (e.g. assisted living). Such applications require building systems of enormous complexity, so that traditional approaches start to fail. The amount of data collected and processed is huge, the computational power required is very high, and the algorithms are too complex allowing for the computation of solutions within the tight time constraints. In addition, security, privacy, or robustness for such systems becomes a critical challenge. An enabler that aims at delivering the required keystone is VEDLIoT, a Very Efficient Deep Learning IoT platform. Instead of traditional algorithms, artificial intelligence (AI) and deep learning (DL) are used to handle the large complexity. Due to the distributed approach, VEDLIoT allows dividing the application into smaller and more efficient components and work together in large collaborative systems in the Internet of Things (IoT), enabling AI-based algorithms that are distributed over IoT devices from edge to cloud. In terms of hardware, VEDLIoT offers a platform, the Cognitive IoT platform, leveraging European technology, which can be easily configured to be placed at any level of the compute continuum starting from the sensor nodes and then edge to cloud. Driven by use cases in the key sectors of automotive, industrial, and smart homes, the platform is supported by cross-cutting aspects satisfying security and robustness. Overall, VEDLIoT offers a framework for the Next Generation Internet based on IoT devices required for collaboratively solving complex DL applications across a distributed system.

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  • Funder: EC Project Code: 730270
    Overall Budget: 12,064,700 EURFunder Contribution: 9,318,200 EUR

    The X-MINE project supports better resource characterization and estimation as well as more efficient ore extraction in existing mine operations, making the mining of smaller and complex deposits economically feasible and increasing potential European mineral resources (specifically in the context of critical raw materials) without generating adverse environmental impact. The project will implement large-scale demonstrators of novel sensing technologies improving the efficiency and sustainability of mining operations based on X-Ray Fluorescence (XRF), X-Ray Transmission (XRT) technologies, 3D vision and their integration with mineral sorting equipment and mine planning software systems. The project will deploy these technologies in 4 existing mining operations in Sweden, Greece, Bulgaria and Cyprus. The sites have been chosen to illustrate different sizes (from small-scale to large-scale) and different target minerals (zinc-lead-silver-gold, copper-gold, gold) including the presence of associated critical metals such as indium, gallium, germanium, platinum group metals and rare earth elements. The pilots will be evaluated in the context of scientific, technical, socio-economic, lifecycle, health and safety performances. The sensing technologies developed in the project will improve exploration and extraction efficiency, resulting in less blasting required for mining. The technologies will also enable more efficient and automated mineral-selectivity at extraction stage, improving ore pre-concentration options and resulting in lower use of energy, water, chemicals and men hours (worker exposure) during downstream processing. The consortium includes 6 industrial suppliers, 4 research/academic organizations, 4 mining companies and 1 mining association. The project has a duration of 51 months and a requested EC contribution of €9.3M.

  • Funder: EC Project Code: 101095947
    Overall Budget: 53,739,800 EURFunder Contribution: 15,430,500 EUR

    TRISTAN’S overarching aim is to expand, mature and industrialize the European RISC-V ecosystem so that it is able to compete with existing commercial alternatives. This will be achieved by leveraging the Open-Source community to gain in productivity and quality. This goal will be achieved by defining a European strategy for RISC-V based designs including the creation of a repository of industrial quality building blocks to be used for SoC designs in different application domains (e.g. automotive, industrial, etc.). The TRISTAN approach is holistic, covering both electronic design automation tools (EDA) and the full software stack. The broad consortium will expose a large number of engineers to RISC-V technology, which will further encourage adoption. This ecosystem will ensure a European sovereign alternative to existing industrial players. The 3-year project fits in the strategy of the European Commission to support the digital transformation of all economic and societal sectors, and speed up the transition towards a green, climate neutral and digital Europe. This transformation includes the development of new semiconductor components, such as processors, as these are considered of key importance in retaining technological and digital sovereignty and build on significant prior investments in knowledge generation in this domain. Development strategies leveraging public research funding that exploit Open-Source have been shown to boost productivity, increase security, increase transparency, allow better interoperability, reduce cost to companies and consumers, and avoid vendor lock-ins. The TRISTAN consortium is composed of 46 partners from industry (both large industries as well as SMEs), research organizations, universities and RISC-V related industry associations, originating from Austria, Belgium, Finland, France, Germany, Israel, Italy, the Netherlands, Poland, Romania, Turkey and Switzerland.

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