Data-Gouv-ML/pcri-informations-sur-les-projets-laureats huggingface dataset:
More Efficient Wind Blades (MEWi-B)

Framework: Horizon 2020 — Societal Challenges
Programme: Secure, clean and efficient energy
Action type: SME instrument
Countries involved: Italy
Call: Stimulating the innovation potential of SMEs for a low carbon energy system (H2020-SMEINST-1-2015, 2015)
Start date: 2015-06-01
End date: 2015-11-30
Duration (months): 6.0
Total project cost (EUR): 71429.0
EU funding (EUR): 50000.0
Participants: 1
Project status: CLOSED

The objective MEWi-B is the implementation and production of universal aeroelastic wind blades, which are recyclable, highly efficient and able to operate in both high and low winds regimes. This means achieving more sustainable and efficient wind systems at a lower environmental impact than with traditional technologies. The innovation of MEWi-B product lies in passive aeroelastic deformation; in the innovative design of the aerodynamic profile, in the innovative and recyclable materials used; in the lighter blades; in the reduction of the rotors diameter at the same power produced. The new blades will allow to produce wind energy in areas where to date it is not cost effective because of low wind, but also to increase the efficiency (20%) of existing wind farms through the re-blading programme. To date, it estimated around 10.000 turbines in Europe that could benefit from re-blading. The wind energy landscape is moving towards a very difficult phase due to incentive cuts for Renewable Energy System, energy wholesale price reduction and expensive system charges. All factors are determining lower than expected returns on assets in operation. As a result, most new wind projects are now being abandoned due to unattractive returns. In this contest MEWi-B provides superior quality blades which delivers over-performance valued by customers. The potential customers are wind turbines manufacturers which will put on their market an innovative solution, owners of existing wind farms, managing company which will benefit from more efficiency and longer life-cycle by replacing the obsolete blades, and developer of new wind farms which could use also marginal sites. The feasibility evaluation of the phase1 will cover in particular: the technical/scientific and economic feasibility, the potential market for the EU and non-EU and the risks related to the project business idea. Phase2 will focus on demonstration, testing and prototyping of product/process and market replication.

Keywords: wind energy,energy efficency,wind baldes,re blading,low environmental impact,recycle,end life,low carbon technologies
Urban dynamics: learning from integrated models and big data (DYNURBAN)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Advanced grants
Action type: ERC actions
Panel: Individuals, Markets and Organisations
Panel description: Economics, finance and management
Countries involved: Spain
Call: ERC Advanced Grant (ERC-2015-AdG, 2015)
Start date: 2016-08-01
End date: 2022-07-31
Duration (months): 72.0
Total project cost (EUR): 1292586.25
EU funding (EUR): 1292586.25
Participants: 1
Project status: CLOSED

City growth is driven by a combination of systematic determinants and shocks. Random growth models predict realistic city size distributions but ignore, for instance, the strong empirical association between human capital and city growth. Models with systematic determinants predict degenerate size distributions. We will develop an integrated model that combines systematic and random determinants to explain the link between human capital, entrepreneurship and growth, while generating relevant city size distributions. We will calibrate the model to quantify the contribution of cities to aggregate growth. Urban growth also has a poorly understood spatial component. Combining gridded data of land use, population, businesses and roads for 3 decennial periods we will track the evolution of land use in the US with an unprecedented level of spatial detail. We will pay particular attention to the magnitude and causes of “slash-and-burn” development: instances when built-up land stops meeting needs in terms of use and intensity and, instead of being redeveloped, it is abandoned while previously open space is built up. Job-to-job flows across cities matter for efficiency and during the recent crisis they have plummeted. We will study them with individual social security data. Even if there have only been small changes in mismatch between unemployed workers and vacancies during the crisis, if workers shy away from moving to take a job in another city, misallocation can increase substantially. We will also study commuting flows for Spain and the UK based on anonymized cell phone location records. We will identify urban areas by iteratively aggregating municipalities if more than a given share of transit flows end in the rest of the urban area. We will also measure the extent to which people cross paths with others opening the possibility of personal interactions, and assess the extent to which this generates productivity-enhancing agglomeration economies.

Keywords: urban economics
Mission concepts for high-performance CubeSat platforms with propulsion system (SpaceEye)

Framework: Horizon 2020 — Excellent Science
Programme: Marie-Sklodowska-Curie Actions
Theme: Marie Skłodowska-Curie
Destination: Individual Fellowships (IF)-Society and Enterprise panel
Action type: Marie Skłodowska-Curie actions
Panel: Environment and Geosciences
Countries involved: Germany
Call: Individual Fellowships (H2020-MSCA-IF-2017, 2017)
Start date: 2019-05-01
End date: 2021-04-30
Duration (months): 24.0
Total project cost (EUR): 159460.8
EU funding (EUR): 159460.8
Participants: 1
Project status: CLOSED

The achievements of the space age are essential to modern society, but they come at an environmental cost. The vast majority of the more than 16000 tracked objects currently orbiting the Earth are space debris. Passive debris mitigation measures are insufficient for the stabilization of the debris environment. In this light, considerable effort is being devoted to develop active debris removal and on-orbit servicing. Dedicated high-performance CubeSat platforms with propulsion system could make on-orbit servicing missions more robust and cost efficient. High Δv propulsion systems technology was long awaited in the CubeSat community, and the proposed research project will significantly advance this field with innovative frameworks for mission design and quantification. The chosen mission concepts will enable a fast response to the changes in overall mission parameters which is rather novel for the space industry, where such parameters are typically frozen at the beginning of the project.
Digital Technologies, Advanced Robotics and increased Cyber-security for Agile Production in Future European Manufacturing Ecosystems (TRINITY)

Framework: Horizon 2020 — Industrial Leadership
Programme: Information and Communication Technologies
Action type: Innovation actions
Countries involved: Germany,Germany,Norway,Finland,Greece,Hungary,Serbia,Finland,Lithuania,Slovenia,Norway,Belgium,Belgium,Belgium,Latvia,United Kingdom
Call: Robotics - Digital Innovation Hubs (DIH) (H2020-DT-2018-1, 2018)
Start date: 2019-01-01
End date: 2023-06-30
Duration (months): 54.0
Total project cost (EUR): 16335948.75
EU funding (EUR): 15997267.25
Participants: 19
Project status: SIGNED

The main objective of TRINITY is to create a network of multidisciplinary and synergistic local digital innovation hubs (DIHs) composed of research centers, companies, and university groups that cover a wide range of topics that can contribute to agile production: advanced robotics as the driving force and digital tools, data privacy and cyber security technologies to support the introduction of advanced robotic systems in the production processes. The result will be a one-stop shop for methods and tools to achieve highly intelligent, agile and reconfigurable production, which will ensure Europe’s welfare in the future. The network will start its operation by developing demonstrators in the areas of robotics we identified as the most promising to advance agile production, e.g. collaborative robotics including sensory systems to ensure safety, effective user interfaces based on augmented reality and speech, reconfigurable robot workcells and peripheral equipment (fixtures, jigs, grippers, …), programming by demonstration, IoT, secure wireless networks, etc. These demonstrators will serve as reference implementation for two rounds of open calls for application experiments, where companies with agile production needs and sound business plans will be supported by TRINITY DIHs to advance their manufacturing processes. Besides technology-centered services, primarily laboratories with advanced robot technologies and know-how to develop innovative application experiments, TRINITY network of DIHS will also offer training and consulting services, including support for business planning and access to financing. Services of participating DIHs and dissemination of information to wider public will be provided through a digital access point that will be developed in the project. Another important activity of the project will be the preparation of a business plan to sustain the network after the end of the project funding.

Keywords: agile production,internet of things,mobile robotics,cyber security,digital technologies,open call,digital innovation hub
Digital Disruptive Technologies to Co-create, Co-produce and Co-manage Open Public Services along with Citizens (CO3)

Framework: Horizon 2020 — Societal Challenges
Programme: Europe in a changing world - inclusive, innovative and reflective societies
Theme: Innovative societies
Action type: Research and Innovation actions
Countries involved: Italy,Spain,Germany,Germany,Greece,France
Call: Transformative impact of disruptive technologies in public services (H2020-SC6-TRANSFORMATIONS-2018, 2018)
Start date: 2019-01-01
End date: 2021-12-31
Duration (months): 36.0
Total project cost (EUR): 3281712.5
EU funding (EUR): 3281712.0
Participants: 13
Project status: CLOSED

CO3 aims at assessing the benefits and risks of disruptive technologies, namely: blockchain, augmented reality, geolocated social network, liquid democracy tools and gamification, in the co-creation, co-production and co-management of public services with citizens as PAs partners. Augmented Reality becomes a single shared layer on the urban paysage and part of citizen’s public life, AR enables manipulation of financial objects built on blockchains, information sharing on a map, online deliberations and so constitutes an infrastructure for service co-production by citizens. CO3 pilots the technologies’ ecosystem of in three sites. It evaluates the outcomes of the new interaction model between PA and citizens under a set of metrics in three dimensions : 1) social and cultural: citizen engagement, change in relationship with public servants; 2) economic: value of services produced, effects on workplaces, consumptions and economic sustainability; 3) legal: legal implications for PA including privacy and data protection. CO3 will devise a business plan ensuring long term sustainability for the PAs on the basis of the metrics applied on the pilots’ data. CO3 is a participative and interdisciplinary project, the Consortium involves: University of Torino (IT)(Computer Science, Economics, Sociology and Law), ISMB private research center (IT), Fundación Universitaria Balmes (ES), Institut de Recherche et d’Innovation of Centre Pompidou (FR), and OpenLab Athens (EL), with its Laboratory of the Digital Commons. It also involves three highly innovative SMEs: Brainbot, leaders in the Ethereum Blockchain development(DE), FlexiGuided (DE), the company that created LiquidFeedback, Geomotion (ES) working on augmented reality and location-based technologies. Municipality of Torino (IT) together with the Neighbourhood Houses, Municipality of Athens (EL) via its public company DAEM and the Municipalities of the Plaine Commune in Paris (FR) will be the pilot sites.

Keywords: blockchain,urban commons,co production,e participation,augumented reality,e democracy,gamification,social networks,public engagement
CLImate INTelligence: Extreme events detection, attribution and adaptation design using machine learning (CLINT)

Framework: Horizon 2020 — Societal Challenges
Programme: Climate action, environment,  resource efficiency and raw materials
Theme: Fighting and adapting to climate change
Action type: Research and Innovation actions
Countries involved: Germany,Spain,Germany,Germany,Italy,Italy,Sweden,Belgium,Greece,France,Netherlands,Netherlands,United Kingdom
Call: Advancing climate services (H2020-LC-CLA-2020-2, 2020)
Start date: 2021-07-01
End date: 2025-06-30
Duration (months): 48.0
Total project cost (EUR): 6067719.98
EU funding (EUR): 6067719.98
Participants: 15
Project status: SIGNED

Weather and climate extremes pose challenges for adaptation and mitigation policies as well as disaster risk management, emphasizing the value of Climate Services in supporting strategic decision-making. Today Climate Services can benefit from an unprecedented availability of data, in particular from the Copernicus Climate Change Service, and from recent advances in Artificial Intelligence (AI) to exploit the full potential of these data. The main objective of CLINT is the development of an AI framework composed of Machine Learning (ML) techniques and algorithms to process big climate datasets for improving Climate Science in the detection, causation and attribution of Extreme Events, including tropical cyclones, heatwaves and warm nights, and extreme droughts, along with compound events and concurrent extremes. Specifically, the framework will support (1) the detection of spatial and temporal patterns, and evolutions of climatological fields associated with Extreme Events, (2) the validation of the physically based nature of causality discovered by ML algorithms, and (3) the attribution of past and future Extreme Events to emissions of greenhouse gases and other anthropogenic forcing. The framework will also cover the quantification of the Extreme Events impacts on a variety of socio-economic sectors under historical, forecasted and projected climate conditions by developing innovative and sectorial AI-enhanced Climate Services. These will be demonstrated across different spatial scales, from the pan European scale to support EU policies addressing the Water-Energy-Food Nexus to the local scale in three types of Climate Change Hotspots. Finally, these services will be operationalized into Web Processing Services, according to most advanced open data and software standards by Climate Services Information Systems, and into a Demonstrator to facilitate the uptake of project results by public and private entities for research and Climate Services development.

Keywords: machine learning
Domo4m: Scalable Intelligent home office automation for energy savings (Domo4mAI)

Framework: Horizon 2020 — Societal Challenges
Programme: Secure, clean and efficient energy
Action type: SME instrument
Countries involved: Spain
Call: Stimulating the innovation potential of SMEs for a low carbon and efficient energy system (H2020-SMEINST-1-2016-2017, 2017)
Start date: 2017-05-01
End date: 2017-10-31
Duration (months): 6.0
Total project cost (EUR): 71429.0
EU funding (EUR): 50000.0
Participants: 1
Project status: CLOSED

Domo4m proposes a home & office automation solution that maximizes energy savings in each household or office, and enables a higher penetration of automated homes and offices due to affordable costs, ability to retrofit existing premises, and the ease of use of the solution. To achieve this, we use Artificial Intelligence (AI) to learn, predict and react on user’s habits to maximize efficiency, and leverage the flexibility of software running on standard hardware with existing wireless protocols. Existing Home Automation systems are complex and expensive. Our solution takes an innovative approach to overcome these barriers by implementing: • Cost reduction o Leverage economies of scale using smartphone based HW, to run our SW on an automation controller deployed at customer´s households. o Use of inexpensive standard based sensors and actuators to maximize the number of controlled devices at an affordable price. o Subscription based model to lower barrier and provide new value added services • Simplify usage: o The AI algorithms included in our SW will implement a ready to use “home configuration” that will be automatically customized to our user´s behaviour and preferences with a minimum user interaction, while keeping security, confidentiality and privacy levels. o We intend to implement and end to end managed service model, were a local field force will consult, install and support most of our solution deployments. Most systems today implement siloes of functionality (heating control, lighting, entertainment, security), compromising user adoption. Our system leverages SW flexibility to implement a single control platform for all devices at home. In conclusion, our solution would accelerate home & office automation adoption to reach predicted 20% penetration. Home & Office automation can save up to 27% o energy consumption to contribute to EU target to reduce energy consumption.

Keywords: home automation,energy savings,domotics,smart home,smart office
Shared Innovation Space for Sustainable Productivity of Grasslands in Europe (Inno4Grass)

Framework: Horizon 2020 — Societal Challenges
Programme: Food security, sustainable agriculture and forestry, marine and maritime and inland water research and the bioeconomy
Theme: Sustainable and competitive agri-food sector for a safe and healthy diet
Action type: Coordination and support actions
Countries involved: Italy,Germany,Ireland,Germany,Italy,Germany,Poland,Sweden,Sweden,Belgium,Belgium,Belgium,France,France,France,France,France,France,Netherlands,Netherlands
Call: Thematic Networks compiling knowledge ready for practice (H2020-RUR-2016-1, 2016)
Start date: 2017-01-01
End date: 2019-12-31
Duration (months): 36.0
Total project cost (EUR): 1999998.75
EU funding (EUR): 1999998.75
Participants: 25
Project status: CLOSED

Grasslands are vitally important for European agriculture. The 20 partners of Inno4Grass gather farmers’ organisations, extension services, education and research in eight countries (Germany, Belgium, France, Ireland, Italy, the Netherlands, Poland & Sweden) where grasslands contribute a major share of the agricultural area. The overall objective of the project is to bridge the gap between practice and science to ensure the implementation of innovative systems on productive grasslands to achieve profitability while providing environmental services. The associated animal productions are dairy and beef cattle and sheep. Inno4Grass will set up a Facilitator Agents network, capture novelties from innovative farms scrutinized via 85 case studies, discuss and synthesize them in electronic farm networks and through cognitive mapping. It will upgrade this capital via multi-actor approaches and science dialogue, transfer innovation capital and boost collaboration and exchanges beyond the borders of regions and among Member States (MS). Dedicated dissemination approaches and events like national and European Wikimedia, decision support systems and grassland awards are designed and applied to convey innovations to practice with highest acceptance by practitioners and beyond the project term. Inno4Grass will ensure delivery and training of grassland knowledge at operational, tactical and strategic levels for farmers, advisors, and students (specific syllabus, materials for existing MOOCs) and for the value chain mobilizing key actors within the collaborating MS. At least 100 practice abstracts and 104 video clips describing innovative practices will be provided. The project strongly contributes to the implementation of the EIP and many consortium members are involved in their national contact points. This supports the establishment and cross linkage of Operational Groups on grasslands.
Development of Novel Statistical Tools for the Analysis of Astronomical Data (ASTROSTAT)

Framework: Horizon 2020 — Excellent Science
Programme: Marie-Sklodowska-Curie Actions
Theme: Marie Skłodowska-Curie
Destination: Research and innovation staff exchange
Action type: Marie Skłodowska-Curie actions
Panel: Physics
Countries involved: Switzerland,Greece,United States,United Kingdom
Call: Marie Skłodowska-Curie Research and Innovation Staff Exchange (RISE) (H2020-MSCA-RISE-2015, 2015)
Start date: 2016-01-01
End date: 2019-12-31
Duration (months): 48.0
Total project cost (EUR): 652500.0
EU funding (EUR): 526500.0
Participants: 7
Project status: CLOSED

We propose an interdisciplinary collaboration network involving leading groups in Astrophysics (Astrophysics Group in Crete, Geneva Observatory, Smithsonian Astrophysical Observatory, Ohio State University. and Nortwestern University), and Statistics (Imperial College, University. of California Davis). The goal of this project is to share expertise between the different fields and geographical areas in order to tackle key questions in observational Astrophysics, related to the nature of dark energy and dark matter, the populations of accreting binary stars in galaxies and their evolution, and the morphological and activity classification of galaxies. To address each of these questions we will use state-of-the-art observations and theoretical models, and we will develop novel, principled tools for statistical analysis in the domains of source classification, structure detection, and fitting. The methods developed under this program will have lasting value and applications beyond the field of Astrophysics.

Keywords: astrostatistics