Data-Gouv-ML/pcri-informations-sur-les-projets-laureats huggingface dataset:
Modelling to Optimize Vector Elimination: Destabilising mosquito populations (MOVE)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Starting grants
Action type: ERC actions
Panel: Environmental Biology, Ecology and Evolution
Panel description: Ecology, biodiversity, environmental change, evolutionary biology, behavioural ecology, microbial ecology, marine biology, ecophysiology, theoretical developments and modelling
Countries involved: United Kingdom
Call: ERC Starting Grant (ERC-2019-STG, 2019)
Start date: 2020-02-01
End date: 2026-04-30
Duration (months): 75.0
Total project cost (EUR): 1259763.0
EU funding (EUR): 1259763.0
Participants: 1
Project status: SIGNED

Control of vector-borne diseases from Chagas to Malaria to Dengue largely relies on reducing or eliminating the arthropod vector populations. These public health initiatives routinely lead to at least initial declines in vector populations. The challenge is that as populations decline, unexpected evolutionary (such as insecticide resistance) and ecological changes (such as population fragmentation and altered density-dependence) can occur that might facilitate or undermine control efforts. However, the relative importance of these ecological intra- and inter-specific processes in regulating vector populations is almost unknown, which hinders the prediction of vector population dynamics and how different interventions might be most effectively deployed to sustainably suppress vectors. Although vector surveillance has generated extensive high-resolution time series datasets to assess the factors that underpin population persistence and regulation, the cutting-edge analytical tools required to overcome the complexity of these data have been mostly developed by ecologists and have rarely been applied in medical entomology. Filling both these knowledge and methodological gaps will require closer integration of public health science, medical entomology and ecology that I intend to deliver through this proposal. As a quantitative ecologist, I will work closely with medical entomologists and public health scientists, to develop and apply sophisticated state-space models to longitudinal vector surveillance data from five malaria endemic countries. I will determine how interventions impact vector: 1) population regulation, 2) metapopulation connectivity and persistence, and 3) community composition. This unprecedented demographic dissection of vector populations will simultaneously challenge ecological theory and explore how to harness intra- and inter-specific processes in vector populations to accelerate 'end-game' strategies that move from vector control to elimination.

Keywords: vector borne diseases,interventions,population stability,intra and inter specific competition,bayesian state space models,vector surveillance,mosquitoes
Enhance Lighting for the Internet of Things (ELIOT)

Framework: Horizon 2020 — Industrial Leadership
Programme: Information and Communication Technologies
Action type: Innovation actions
Partnership: Photonics (cPPP)
Countries involved: Germany,Germany,Germany,Spain,Spain,Netherlands,Netherlands,United Kingdom
Call: Photonics based manufacturing, access to photonics, datacom photonics and connected lighting (H2020-ICT-2018-2, 2018)
Start date: 2019-01-01
End date: 2022-06-30
Duration (months): 42.0
Total project cost (EUR): 7313322.0
EU funding (EUR): 5991026.0
Participants: 12
Project status: CLOSED

So far, the Internet of Things (IoT) is narrowband with no latency constraints. A wider range of applications is envisioned for industrial manufacturing, augmented reality and autonomous cars. It makes use of artificial intelligence, where compute functions will be offloaded from devices into the cloud. Accordingly, future IoT will need wireless links with high data rates, low latency and reliable connectivity despite the limited radio spectrum. Connected lighting is an interesting infrastructure for IoT services because it enables visible light communication (VLC), i.e. a wireless communication using unlicensed light spectrum. LED luminaires have enough modulation bandwidth for high data rates and each luminaire can be used as a wireless access point. Networked VLC-enhanced luminaires will add new features to build a wireless network for the IoT. ELIOT will start from existing prototypes and develop the support for IoT services. The project will integrate the lighting infrastructure with VLC and add positioning, multicast communications and enhanced security. ELIOT will demonstrate the new infrastructure in real environments at TRL ≥6 and mobile IoT devices at TRL ≥ 4. Main project goals are to provide an open reference architecture for the support of IoT in the lighting infrastructure, build consensus reflecting the best architectural choices, contribute to standardization of lighting and telecom infrastructures in IEC, IETF, IEEE and ITU-T and provide a roadmap for IoT until 2022 and beyond. ELIOT brings together Europe’s key players that cover the whole value chain, i.e. OSRAM, Philips Lighting and Tridonic as major component and luminaire makers, Maxlinear as chipmaker, NOKIA as a leading network vendor and integrator, BMW, Weidmüller and Thyssen Krupp working on industrial IoT, Deutsche Telekom and KPN as innovative operators, together with Fraunhofer HHI as a leading research institute and two top universities from Eindhoven and Oxford.

Keywords: visible light communication,positioning,multicasting,security,real environments,open architecture,standardization
IMPROVING THE MANAGEMENT OF ENGINEERING AND CONSTRUCTION PROJECTS THROUGH REALTIME MONITORING AND ANALYSIS OF CLOUD-BASED PROJECT DATA (Insight)

Framework: Horizon 2020 — Industrial Leadership
Programme: Innovation in SMEs
Action type: SME instrument
Countries involved: United Kingdom
Call: SME instrument (H2020-SMEInst-2018-2020-1, 2019)
Start date: 2020-01-01
End date: 2020-06-30
Duration (months): 6.0
Total project cost (EUR): 71429.0
EU funding (EUR): 50000.0
Participants: 1
Project status: CLOSED

The goal of this innovation project is to add value to digital engineering tools - inc. project management, product data management (PDM) and product lifecycle management (PLM) - by applying Net AI and providing a solution that allows companies to automatically monitor, analyse and learn from the evolving structure and content of their digital files. The product is referred to herein as Insight. Through the provision of an affordable solution that integrates market disrupting technologies of cloud computing and Artificial Intelligence combined with first-to-market capability, we aim to establish a market leading position for the monitoring and improved management of engineering and construction projects. The objectives of the overall innovation project are: 1) conduct a feasibility study focusing on technical and market knowledge acquisition supported by robust assessment of financial feasibility; 2) develop Insight - a cloud-based suite of modules built on our evolving intellectual property of Net AI; 3) bring Insight to a robust minimum viable product; 4) introduce Insight to the EU and global markets; 5) demonstrate effectiveness and cost-savings through achievement of €10M sales by 2023; and 6) leverage successful EU commercialisation to achieve €20M revenue by 2026.

Keywords: cloud computing,a i,project management,construction,manufacturing,computer aided design,product lifecycle management
Being Lean and Seen: Meeting the challenges of delivering projects successfully in the 21st century (BeingL_S)

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: Economic Sciences
Countries involved: Germany,Germany,Germany,Malaysia,United Kingdom,United Kingdom,United Kingdom
Call: Research and Innovation Staff Exchange (H2020-MSCA-RISE-2016, 2016)
Start date: 2017-01-01
End date: 2022-09-30
Duration (months): 69.0
Total project cost (EUR): 328500.0
EU funding (EUR): 328500.0
Participants: 12
Project status: CLOSED

The advancement of project management (PM) knowledge and the development of PM capability of people is crucial to the successful delivery of projects. As the overall project-related spending in the EU is assumed to be about € 3.27 trillion there are huge societal and economic challenges of reducing the massive financial and psychological costs of poor project delivery. Especially as about 6% of all projects are believed to be wholly unsuccessful, many of them tax-payer funded. Our programme is designed to put building blocks in place to enable PM to respond to the challenges it faces in delivering projects successfully in the 21st century. It does this by taking a multi-disciplinary perspective encompassing PM, lean management, psycho-social aspects, innovation and change management. The building blocks will have three broad pillars: one focused on PM efficiency (being Lean), one on PM systems that meet the psycho-social needs of project staff (being Seen) and one on making PM responsive to the need of organisations to be innovative and manage change (being Lean and Seen). The programme will cater for different contexts of project delivery in developed and developing countries, to reflect the global and interconnectedness nature of projects. A network of five academic partners, including one from a developing country and five non-academic, will deliver the holistic PM framework to guide project delivery in the future. They will investigate the role of different management practices in PM contexts and the distinctions in PM system design and delivery in different contexts. Data will be collected through a multiple method approach including in-depth reviews of the literatures, secondary data sources, cross-sectional surveys, case studies, focus groups, Delphi and interviews. Innovation will take place by bringing together the knowledge of theoretical perspectives from different disciplines, which largely reside in the academic partners, with the practical knowledge

Keywords: project management,lean management,psycho social aspects in projects,innovation and change management
Safe-Guarding Home IoT Environments with Personalised Real-time Risk Control (GHOST)

Framework: Horizon 2020 — Societal Challenges
Programme: Secure societies - protecting freedom and security of Europe and its citizens
Theme: Improve cyber security
Action type: Innovation actions
Countries involved: Spain,Germany,Germany,Spain,Switzerland,Norway,Greece,Norway,Greece,United Kingdom,United Kingdom
Call: Cyber Security for SMEs, local public administration and Individuals (H2020-DS-SC7-2016, 2016)
Start date: 2017-05-01
End date: 2020-04-30
Duration (months): 36.0
Total project cost (EUR): 4995519.25
EU funding (EUR): 3603831.75
Participants: 12
Project status: CLOSED

To effectively respond to the multitude & complexity of cybersecurity challenges in smart-homes GHOST deploys a pioneering software-enabled ‘usable security’ solution. The project brings professional level security to the European citizens and to this end it: (a) increases the automation level & effectiveness of existing security services; (b) opens up the cybersecurity ‘blackbox’ to consumers, creates understanding and builds trust through effortless decision support & advanced ‘usable transparency’; (c) enhances the system’s self-defence by safeguarding critical security-related data using blockchain technology. GHOST software will be embedded in an adequately adapted smart-home network gateway though it will be designed to be vendor-independent. A dedicated middleware layer ensures interoperability with multiple gateways & IoT devices. GHOST considers the relationship between security and usability to be an integration challenge (positive sum game) and definitely not a trade-off (zero-sum game). In this context, the project envisions to lead a paradigm shift in consumer cybersecurity by successfully coupling usable security with transparency and behavioural engineering. The envisaged user experience will systematically trigger security-friendly behaviour aiming at establishing appropriate ‘habitual behaviours’. The solution will perform network analysis & deep packet inspection for suspicious pattern recognition, will apply machine learning for malicious behaviour detection, will carry out context-aware real-time risk assessment, and widely apply analytics & visualization for effortless user comprehension & decision support. In short, GHOST will (i) increase cybersecurity resilience; (ii) boost usability & automation; and (iii) enhance the competitiveness of European ICT security industry. GHOST will be demonstrated in more than 140 real smart-homes in Spain, Norway & Romania via the Red Cross network and beta testers from the customer basis of Televes & ThingsMaze.

Keywords: blockchain
One Click LCA – transforming the construction industry through automated, affordable and scalable solution for assessing and improving the environmental impacts of construction projects and products (OneClickLCA)

Framework: Horizon 2020 — Industrial Leadership
Programme: Innovation in SMEs
Action type: SME instrument
Countries involved: Finland
Call: SME business model innovation (H2020-SMEINST-2-2015, 2015)
Start date: 2016-03-01
End date: 2018-02-28
Duration (months): 24.0
Total project cost (EUR): 1492625.0
EU funding (EUR): 1044837.5
Participants: 1
Project status: CLOSED

Construction is the world’s largest industry in terms of resource usage and waste generation, and buildings are the largest user of energy and driver for global warming. Improving resource efficiency and environmental impacts are considered the main challenges of the construction industry in EU. Life Cycle Assessment (LCA) tools assess a buildings or building products environmental performance, and are necessary to design and build in an environmentally sustainable manner. However, currently there are no fast, affordable and scalable LCA tools. LCA study usually costs €3000-15000 and takes 40-150 hours, delaying the construction process and slowing the uptake of LCA. Economies of scale have not been achieved due to heterogeneous requirements in various certifications and regulations. Bionova, the leading construction LCA software firm in Northern Europe, has developed a prototype of “One Click LCA”. With this software, LCA can be done at least 100x faster (with 1 click) and it costs 10x less (€250-1300). A core element of it is an innovative “plug-in” interface with an adaptive recognition engine. It can be easily trained by the user to adapt to their particular data, enabling automatic processing of any data sources. Unlike competing solutions, it also allows building tailor-made sustainability applications, resolving the issue of diversity in LCA-related requirements. OneClickLCA project is aimed at implementing business model innovation – preparing a wide-scale market introduction of the One Click LCA using a novel business model (value-based pricing, radically improved value proposition, cloud-based delivery, novel sales and scalability strategy) and scaling up the industrial capability of the software. LCA software market grew at 39% CAGR in 2011-2015, exceeding €250 million, with consulting services generating additional €320M. Development of One Click LCA to a global scale would increase Bionova’s revenues by €32M in 2022.

Keywords: life cycle assessment,business model innovation
Galaxy evolution in dense environments (Fornax)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Starting grants
Action type: ERC actions
Panel: Universe sciences
Panel description: Astro-physics/-chemistry/-biology; solar system; planetary systems; stellar, galactic and extragalactic astronomy; cosmology; space sciences; astronomical instrumentation and data
Countries involved: Italy
Call: ERC Starting Grant (ERC-2015-STG, 2015)
Start date: 2016-10-01
End date: 2022-09-30
Duration (months): 72.0
Total project cost (EUR): 1500000.0
EU funding (EUR): 1500000.0
Participants: 1
Project status: CLOSED

The Universe around us is populated with galaxies, each containing from millions to tens of billions of individual stars. Far from being immutable, galaxies undergo profound changes as they age. Their evolution depends on their position in the cosmic web, a network of sheets and filaments of matter that stretches across the entire Universe. The goal of FORNAX is to study the evolution of galaxies in the densest regions of the cosmic web, galaxy clusters. In these regions, a number of physical processes are thought to make galaxies lose their cold gas – the material from which new stars are born – and change their appearance dramatically. I will study these processes in action by observing the flow of cold gas in and out of galaxies living inside an important, nearby cluster of galaxies: Fornax. I will observe Fornax for 2,450 hours with MeerKAT, a new, state-of-the-art radio telescope precursor of the Square Kilometre Array. Thanks to the unprecedented combination of sensitivity, resolution and sky-coverage of my survey, I will reveal the most subtle signs of the removal of gas from galaxies, I will detect the smallest gas-bearing galaxies in the cluster, and I will hunt the elusive cold gas which, according to cosmological theories, floats in the space between galaxies along the filaments of the cosmic web.
Laser Scanning for Automatic Bridge Assessment (BridgeScan)

Framework: Horizon 2020 — Excellent Science
Programme: Marie-Sklodowska-Curie Actions
Theme: Marie Skłodowska-Curie
Destination: Individual Fellowships (IF)-Standard European Fellowships
Action type: Marie Skłodowska-Curie actions
Panel: Information Science and Engineering
Countries involved: Netherlands
Call: Individual Fellowships (H2020-MSCA-IF-2017, 2017)
Start date: 2019-01-01
End date: 2020-12-31
Duration (months): 24.0
Total project cost (EUR): 177598.8
EU funding (EUR): 177598.8
Participants: 1
Project status: CLOSED

Bridges on Europe’s transportation network are at risk due to increased freight demands, aging, environmental impact and climate change. Deficiencies of bridges must be assessed in a timely manner for planning critical maintenance, repairs and expansions. However, with bi-annual general inspections of bridges, damage may not be documented timely to prevent catastrophic collapse. Moreover, visual inspection is the predominant method that has many downsides: subjective results, slow and expensive procedures, high safety risks for inspectors and requirements of experienced inspectors, and traffic closures. Recently, although unmanned aerial vehicle (UAV)-based image has been developed for bridge inspection, results based UAV-images are of relatively low accuracy, which can be exaggerated when the images subject to shadows and noise. While several pieces of methods have been proposed to process data (both images and a point cloud), these approaches are not automatic, scalable and robust. Thus, to address those issues, the project “Laser Scanning for Automatic Bridge Assessment” called BridgeScan proposes the framework to use laser scanning integrated into UAV to acquire 3D topographic data points of bridges and to automatically process data for bridge assessment purpose. This project will involve (i) investigate a flight path and scanning parameters to scan a bridge structure by UAV with an integrated laser scanning sensor, (ii) develop automatic, robust, efficient methods to process laser scanning data to identify structural deficiencies for bridge condition rating and (iii) develop automatic methods for reconstructing a 3D bridge model for bridge assessment based on finite element analysis. Success of the BridgeScan project will be fundamental for further deploying UAV with laser scanning for monitoring and assessment of other infrastructures. Moreover, the proposed methods can be extended to reconstruct other objects for urban modelling and construction management.

Keywords: bridge inspection,bridge assessment,bridge monitoring,bridge conditional rating,lidar,laser scanning,point cloud,structural deficiency,geometric modelling
Energy Efficiency through behaviour change transition strategies (ENCHANT)

Framework: Horizon 2020 — Societal Challenges
Programme: Secure, clean and efficient energy
Theme: Reducing energy consumption and carbon foorpint by smart and sustainable use
Action type: Research and Innovation actions
Countries involved: Italy,Italy,Italy,Germany,Austria,Austria,Norway,Romania,Türkiye,Romania,Norway,Norway
Call: Socio-economic research: non-energy impacts and behavioural insights on energy efficiency interventions (H2020-LC-SC3-EE-2020-1, 2020)
Start date: 2020-10-01
End date: 2023-12-31
Duration (months): 39.0
Total project cost (EUR): 1957291.33
EU funding (EUR): 1957291.33
Participants: 18
Project status: SIGNED

The time for reaching the necessary cuts in energy use and CO2 emissions is running out quickly and increasing energy efficiency in households substantially is a prerequisite for reaching these goals in time. Behaviour science has provided deep insights into mechanisms of behaviour change in this domain in a large number of small-scale pilots. However, the urgency of the task makes it necessary to role-out such intervention programs lagre-scale and quickly. This requires knowledge on how behaviour science based intervention programs can be provided in real-life situations, on large scale, and resource efficient by real market actors. To address this knowledge gap, the ENCHANT consortium and research approach have been carefully designed to systematically evaluate existing knowledge on energy efficiency interventions, reanalyse existing data in the field, design realistic intervention packages, and implement them on 10 million households in six European countries with a large group of user partners of different types (energy providers, municipalities, NGOs) testing different communication channels. This unprecedented intervention program allows testing a large selection of intervention types addressing a large variety of psychological biases alone or in combination and evaluates their realistic saving potentials. ENCHANT evaluates the performance of intervention campaigns not only with respect to energy and CO2 saved, but also cost effectiveness, and effects on well-being of the participants (with a focus on gender specific effects), as well as effects for target groups in energy poverty. The knowledge created in ENCHANT will be implemented into an algorithm-based webtool which supports decision making of policymakers, energy providers, NGOs and municipalities in designing effective and targeted energy efficiency campaigns. In short, ENCHANT will bridge the gap from knowledge to impact.

Keywords: behavioural science,interventions,large scale,cost effect,decision making tool