Madrid, Spain

The Technical University of Madrid or sometimes called Polytechnic University of Madrid is a Spanish University, located in Madrid. It was founded in 1971 as the result of merging different Technical Schools of Engineering and Architecture, originated mainly in the 18th century. Over 35,000 students attend classes during the year.According to the annual university ranking conducted by El Mundo, the Technical University of Madrid ranks as the top technical university in Spain, and second overall. The majority of its Engineering Schools are consistently ranked as leading academic institutions in Spain in their fields, and among the very best in Europe.The UPM is part of the TIME network, which groups fifty engineering schools throughout Europe. Wikipedia.


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Grant
Agency: Cordis | Branch: H2020 | Program: ECSEL-IA | Phase: ECSEL-17-2015 | Award Amount: 64.82M | Year: 2016

ENABLE-S3 will pave the way for accelerated application of highly automated and autonomous systems in the mobility domains automotive, aerospace, rail and maritime as well as in the health care domain. Virtual testing, verification and coverage-oriented test selection methods will enable validation with reasonable efforts. The resulting validation framework will ensure Europeans Industry competitiveness in the global race of automated systems with an expected market potential of 60B in 2025. Project results will be used to propose standardized validation procedures for highly automated systems (ACPS). The technical objectives addressed are: 1. Provision of a test and validation framework that proves the functionality, safety and security of ACPS with at least 50% less test effort than required in classical testing. 2. Promotion of a new technique for testing of automated systems with physical sensor signal stimuli generators, which will be demonstrated for at least 3 physical stimuli generators. 3. Raising significantly the level of dependability of automated systems due to provision of a holistic test and validation platform and systematic coverage measures, which will reduce the probability of malfunction behavior of automated systems to 10E-9/h. 4. Provision of a validation environment for rapid re-qualification, which will allow reuse of validation scenarios in at least 3 development stages. 5. Establish open standards to speed up the adoption of the new validation tools and methods for ACPS. 6. Enabling safe, secure and functional ACPS across domains. 7. Creation of an eco-system for the validation and verification of automated systems in the European industry. ENABLE-S3 is strongly industry-driven. Realistic and relevant industrial use-cases from smart mobility and smart health will define the requirements to be addressed and assess the benefits of the technological progress.


Grant
Agency: Cordis | Branch: H2020 | Program: SGA-RIA | Phase: FETFLAGSHIP | Award Amount: 89.00M | Year: 2016

Understanding the human brain is one of the greatest scientific challenges of our time. Such an understanding can provide profound insights into our humanity, leading to fundamentally new computing technologies, and transforming the diagnosis and treatment of brain disorders. Modern ICT brings this prospect within reach. The HBP Flagship Initiative (HBP) thus proposes a unique strategy that uses ICT to integrate neuroscience data from around the world, to develop a unified multi-level understanding of the brain and diseases, and ultimately to emulate its computational capabilities. The goal is to catalyze a global collaborative effort. During the HBPs first Specific Grant Agreement (SGA1), the HBP Core Project will outline the basis for building and operating a tightly integrated Research Infrastructure, providing HBP researchers and the scientific Community with unique resources and capabilities. Partnering Projects will enable independent research groups to expand the capabilities of the HBP Platforms, in order to use them to address otherwise intractable problems in neuroscience, computing and medicine in the future. In addition, collaborations with other national, European and international initiatives will create synergies, maximizing returns on research investment. SGA1 covers the detailed steps that will be taken to move the HBP closer to achieving its ambitious Flagship Objectives.


Grant
Agency: Cordis | Branch: H2020 | Program: RIA | Phase: FETPROACT-01-2016 | Award Amount: 4.24M | Year: 2017

Planning and mental simulation of actions and outcomes are a major cognitive trait of humans. We predict action consequences and perform goal-directed actions in proactive, forward-looking ways. By contrast, systems that lack predictive planning are reactive and dominated by reflex-like, cumbersome behaviors. Most currently existing brain-machine-interfaces (BMI) fall into this category. Plan4Act sets out to go beyond this by inferring actions from action-predicting neural activity of complex action sequences. Neurophysiology in non-human primates recently revealed that such encoding is far more widespread than previously thought. The goal of the Plan4Act project is to record and understand predictive neural activity and use it to proactively control devices in a smart house. The far-future vision behind this is to endow motor-impaired patients with the ability to plan a daily-life goal like making coffee and achieve it without having to invoke one by one every single individual action to reach this goal. To approach this complex problem, we record multi-unit action predicting activity in macaques (WP1), model this by adaptive neural networks (WP2), design therefrom an embedded (FPGA-based) controller (WP3), and interface it with a smart house (WP4) to control action sequences with a clear look-ahead property. The main outcome of this project is a system that integrates the above components at TRL4 for which we quantify improved reaction speed and robustness of this type of proactive BMI control. The understanding and use of predictive neural signals for machine control is novel and methods, algorithms, and hardware developed to translate predictive planning from neural activity to technology create the major general impact of this project. Potential translational and commercial interests will be assessed by our industrial partner, where specifically the embedded controller and its smart house interface are expected to create near-future commercial impact, too.


Grant
Agency: Cordis | Branch: H2020 | Program: IA | Phase: IoT-01-2016 | Award Amount: 25.77M | Year: 2017

ACTIVAGE is a European Multi Centric Large Scale Pilot on Smart Living Environments. The main objective is to build the first European IoT ecosystem across 9 Deployment Sites (DS) in seven European countries, reusing and scaling up underlying open and proprietary IoT platforms, technologies and standards, and integrating new interfaces needed to provide interoperability across these heterogeneous platforms, that will enable the deployment and operation at large scale of Active & Healthy Ageing IoT based solutions and services, supporting and extending the independent living of older adults in their living environments, and responding to real needs of caregivers, service providers and public authorities. The project will deliver the ACTIVAGE IoT Ecosystem Suite (AIOTES), a set of Techniques, Tools and Methodologies for interoperability at different layers between heterogeneous IoT Platforms and an Open Framework for providing Semantic Interoperability of IoT Platforms for AHA, addressing trustworthiness, privacy, data protection and security. User-demand driven interoperable IoT-enabled Active & Healthy Ageing solutions will be deployed on top of the AIOTES in every DS, enhancing and scaling up existing services, for the promotion of independent living, the mitigation of frailty, and preservation of quality of life and autonomy. ACTIVAGE will assess the socio-economic impact, the benefits of IoT-based smart living environments in the quality of life and autonomy, and in the sustainability of the health and social care systems, demonstrating the seamless capacity of integration and interoperability of the IoT ecosystem, and validating new business, financial and organizational models for care delivery, ensuring the sustainability after the project end, and disseminating these results to a worldwide audience. The consortium comprises industries, research centres, SMEs, service providers, public authorities encompassing the whole value chain in every Deployment Site.


Grant
Agency: Cordis | Branch: H2020 | Program: IA | Phase: ICT-15-2016-2017 | Award Amount: 18.70M | Year: 2017

Big Data will have a profound economic and societal impact in the mobility and logistics sector, which is one of the most-used industries in the world contributing to approximately 15% of GDP. Big Data is expected to lead to 500 billion USD in value worldwide in the form of time and fuel savings, and savings of 380 megatons CO2 in mobility and logistics. With freight transport activities projected to increase by 40% in 2030, transforming the current mobility and logistics processes to become significantly more efficient, will have a profound impact. A 10% efficiency improvement may lead to EU cost savings of 100 BEUR. Despite these promises, interestingly only 19 % of EU mobility and logistics companies employ Big Data solutions as part of value creation and business processes. The TransformingTransport project will demonstrate, in a realistic, measurable, and replicable way the transformations that Big Data will bring to the mobility and logistics market. To this end, TransformingTransport, validates the technical and economic viability of Big Data to reshape transport processes and services to significantly increase operational efficiency, deliver improved customer experience, and foster new business models. TransformingTransport will address seven pilot domains of major importance for the mobility and logistics sector in Europe: (1) Smart High-ways, (2) Sustainable Vehicle Fleets, (3) Proactive Rail Infrastructures, (4) Ports as Intelligent Logistics Hubs, (5) Efficient Air Transport, (6) Multi-modal Urban Mobility, (7) Dynamic Supply Chains. The TransformingTransport consortium combines knowledge and solutions of major European ICT and Big Data technology providers together with the competence and experience of key European industry players in the mobility and logistics domain.


Grant
Agency: Cordis | Branch: H2020 | Program: CSA | Phase: ICT-17-2016-2017 | Award Amount: 4.94M | Year: 2017

The mission of BDVe is to support the Big Data Value PPP in realizing a vibrant data-driven EU economy or said in other words, BDVe will support the implementation of the PPP to be a SUCCESS. Behind that mission, there are multiple goals to achieve, which should be taken into full consideration when defining the directions of the PPP. Some of the most challenging ones are: (1) achieving a more competitive landscape of European Big Data providers, leading to bigger market share; (2) creating the context for a more competitive EU industry (transport, manufacturing, public sector, agrifood, media, energy) in the advent of a data-driven revolution where many traditional players will have to transform their processes and re-think their business if they want to remain completive or in some cases, just to survive-; (3) ensuring the sustainability of the investments and actions triggered by the PPP. BDVe has broken down those high-level goals into 7 major priorities for the project: Being accurately informed about most important facts in Big Data so that we have a solid basis to support the decision-making process in the PPP Supporting the implementation of the Big Data PPP from an operational point of view Developing a vibrant community around the PPP Supporting the development of a European network of infrastructures and centers of excellence around Big Data Setting-up a professional Communications strategy Setting up a framework that supports the acceleration of data-driven businesses, and Ensuring the sustainability of the investments and actions triggered by the PPP. The BDVe consortium includes a set of partners that have shown commitment and dedication to the success of the PPP for several years. They have already invested and they have committed to invest along the coming years. We believe that this CSA cannot be a neutral action that offers operational support without further commitment.


Grant
Agency: Cordis | Branch: H2020 | Program: RIA | Phase: ICT-01-2016 | Award Amount: 5.38M | Year: 2017

ICT is embedded and pervasive into our daily lives. The notion of Cyber Physical Systems (CPS) has emerged: embedded computational collaborating devices, capable of controlling physical elements and responding to humans. The Cross-layer modEl-based fRamework for multi-oBjective dEsign of Reconfigurable systems in unceRtain hybRid envirOnments (CERBERO) project aims at developing a design environment for CPS based of two pillars: a cross-layer model based approach to describe, optimize, and analyze the system and all its different views concurrently; an advanced adaptivity support based on a multi-layer autonomous engine. To overcome the limit of current tools, CERBERO provides: libraries of generic Key Performance Indicators for reconfigurable CPSs in hybrid/uncertain environments; novel formal and simulation-based methods; a continuous design environment guaranteeing early-stage analysis and optimization of functional and non-functional requirements, including energy, reliability and security. CERBERO effectiveness will be assessed in challenging and diverse scenarios, brought by industrial leaders: an embedded CPS with self-healing capabilities for planetary explorations (TASE-S&T), an ocean monitoring CPSoS (AS), and a Smart Travelling CPSoS for Electric Vehicle (TNO-CRF-S&T). CERBERO will automate multi-objective decisions to meet requirements and correct/optimizedbyconstruction designs. Interoperable components (i.e. DynAA by TNO, AOW by IBM, PREESM by INSA, PAPI-ARTICo3 by UPM, MDC by UniCA-UniSS) will be enhanced with additional features (as security, USI), mostly released as open-source to foster open innovation and a real path to standardisation, and integrated (IBM- AI) into a unique framework. Design speed up (one order of magnitude), increased performance (30% less energy) and reduced costs of deployment (by rapid prototyping and system in the loop incremental design) and maintenance (by runtime verification and adaptivity) of CPSoS are expected.

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