ADR Awareness Centre

The European AI, Data and Robotics stakeholders operate from diverse historic backgrounds. To tap into the potentials of the diverse knowledge and resources generated in the AI, Data, and Robotics ecosystem, an all-inclusive collaboration approach between these stakeholders is necessary to make the ADR resources available and accessible to all.

For this, the ADR Awareness Centre is developed as an open repository of ADR educational resources and materials to enable collaboration and alignment among all projects within the Partnership, relevant external projects, and the public. The Awareness Centre will collect, validate, and publish educational resources and materials related to AI, Data, and Robotics.

- Who is this for? Everyone. Every project and organization in Europe including the general member of the public
- What does this Centre provide? AI, Data, and Robotics educational resources and materials produced in the EU
- When a new resource becomes available? The list of the resources will be updated when a new resource is submitted and validated
- Why should I publish a resource? Firstly, publishing your materials will promote and make them accessible to all. Secondly, it increases the transparency of your work and improves your and your organizations reputation. Last but not the least, your material will help address ADR challenges and contribute to shaping the future of ADR in Europe.
- How can I contribute and publish my resources? The Centre designed a very simple process for you to submit and publish your resources. You only need to submit your resource here and we will review and get it published and publicly accessible to all.
- What kinds of resources can I publish? The Centre only collects and publishes ADR related educational resources that can be publicly available and accessible to all. Copyrighted and licensed contents will not be published in the Centre.

Add your resource

400+

Available resource

10

Resource types

Displaying 3 resources

Video/Webinars

Webinar "Industry-driven Use Cases"

AI4REALNET project covers the perspective of AI-based solutions addressing critical systems (electricity, railway, and air traffic control), modelled by networks that can be simulated and traditionally operated by humans and where AI complements a

Category

Action and Interaction Technologies, Data for AI, Experiment and Deployment, Reasoning and decision-making Technologies, Systems, methodologies, hardware, and tools

Target audience

ADR Experts and Associations, Individual Citizens/Members of the Society, Policy Makers, Private Sector, Public Sector, Researchers and Academic

Source

Adra-e

Software resources

Software resources

100-Driver: A Large-scale, Diverse Dataset for Distracted Driver Classification

A large-scale, diverse posture-based distracted diver dataset, with more than 470K images taken by 4 cameras observing 100 drivers over 79 hours from 5 vehicles.

Category

Data sharing and Data spaces

Target audience

Individual Citizens/Members of the Society, Policy Makers, Private Sector, Public Sector, Researchers and Academic

Source

Adra-e

Video/Webinars

SAFEXPLAIN Introduction to Trustworthy AI for Safety-Critical Systems

This introductory video provides an overview of the steps taken by the SAFEXPLAIN project to ensure that the AI-based solutions used in safety-critical systems are Trustworthy, explainable and comply with the safety guidelines of diverse industria

Category

Data flow standards, Certification and Compliance, Trustworthiness

Target audience

Individual Citizens/Members of the Society, Policy Makers, Private Sector

Source

Adra-e

Want to upload your own resource?

Fill in the form