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INNOVATION
Remote Attestation and Trusted Execution Environment for enhancing Low-Cost Device Trustworthiness.
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Market Maturity: Exploring
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Market Creation Potential
This innovation was assessed by the JRC’s Market Creation Potential indicator framework as addressing the needs of existing markets and existing customers. Learn more
Women-led innovation
A woman had a leadership role in developing this innovation in at least one of the Key Innovator organisations listed below.
Location of Key Innovators developing this innovation
Key Innovators
UN Sustainable Development Goals(SDG)
This innovation contributes to the following SDG(s)
SUSTAINABLE DEVELOPMENT GOAL 9
Build resilient infrastructure, promote inclusive and sustainable industrialization and foster innovation

The UN explains: "Investments in infrastructure – transport, irrigation, energy and information and communication technology – are crucial to achieving sustainable development and empowering communities in many countries. It has long been recognized that growth in productivity and incomes, and improvements in health and education outcomes require investment in infrastructure."

The EU-funded Research Project
This innovation was developed under the Horizon Europe project Green.Dat.AI with an end date of 31/12/2025
  • Read more about this project on CORDIS
Description of Project Green.Dat.AI
GREEN.DAT.AI aims to channel the potential of AI towards the goals of the European Green Deal, by developing novel Energy-Efficient Large-Scale Data Analytics Services, ready-to-use in industrial AI-based systems, while reducing the environmental impact of data management processes. GREEN.DAT.AI will demonstrate the efficiencies of the new analytics services in four industries (Smart Energy, Smart Agriculture/Agri-food, Smart Mobility, Smart Banking) and six different application scenarios, leveraging the use of European Data Spaces. The ambition is to exploit mature (TRL5 or higher) solutions already developed in recent H2020 projects and deliver an efficient, massively distributed, open-source, green, AI/FL - ready platform, and a validated go-to-market TRL7/8 Toolbox for AI-ready Data Spaces. The services will cover AI-enabled data enrichment, Incentive mechanisms for Data Sharing, Synthetic Data Generation, Large-scale learning at the Edge/Fog, Federated & Auto ML at the edge/fog, Explainable AI/Feature Learning with Privacy Preservation, Federated & Automatic Transfer Learning, Adaptive FL for Digital Twin Applications, Automated IoT event-based change detection/forecasting. The GREEN.DAT.AI Consortium consists of a multidisciplinary group of 17 partners from 10 different countries (and one associated party), well balanced in terms of expertise. The vast majority of partners already have key roles in a number of projects funded under the Big Data PPP (ICT-16-2017) topic, namely BigDataStack, CLASS, Track & Know, and I-BiDaaS and are serving as active members of the BDVA/DAIRO Association, FIWARE, AIOTI, and ETSI. In addition, partners come from a variety of sectors, such as banking, mobility, energy, and agriculture, constituting a representative workforce of their respective domains, which will contribute to industry adoption and stimulate uptake in other sectors as well.

Innnovation Radar's analysis of this innovation is based on data collected on 17/09/2024.
The unique id of this innovation in the European Commission's IT systems is: 128251