SmartCHANGE's goal is to develop trustworthy, AI-based decision-support tools that will help health professionals and citizens reduce long-term risk of NCDs by accurately assessing the risk of children and teens and promoting optimised risk-lowering strategies.

Artificial intelligence powers a growing number of systems today. This is why it’s important to make sure the AI algorithms work correctly. In this context, the EU-funded AutoFair project will focus on the issue of fairness. Specifically, it will deal with the design of explainable and transparent AI algorithms.

The artificial intelligence (AI) needed for complex autonomous tasks like self-driving cars depends on deep learning techniques. However, safety requirements mean that such techniques must also be explainable and traceable. The EU-funded SAFEXPLAIN project plans to solve this issue by creating new explainable deep learning solutions with end-to-end traceability that comply with functional safety requirements for critical autonomous AI-based systems while preserving high performance.

The goal of the AUTOASSESS project is to employ a robot and remove human surveyors out of harm’s way, while at the same time obtaining an accurate, repeatable, and quick vessel inspection. 

The PERKS project supports the holistic governance of industrial PK in its entire life cycle, from elicitation to management and from access to exploitation. PERKS bases its solutions on leading-edge AI (both symbolic and subsymbolic) and data technologies, by advancing and integrating existing methodologies and tools in terms of readiness, flexibility and user acceptance. 

dAIry 4.0 integrates AI, Data, and Robotics to optimize AVMS, reducing environmental impact. It focuses on individual cow health via AVMS and introduces a laser sensor for real-time milk quality analysis. 

DATAMITE delivers a modular, open-source and multi-domain Framework to improve data monetising, interoperability, trading and exchange in the form of software modules, training and business materials for European companies, empowering them to become new relevant players in the data economy.

UPCAST Project provides a set of universal, trustworthy, transparent, and user-friendly data market plugins for the automation of data sharing and processing agreements between businesses, public administrations and citizens.

EMERALDS is a Horizon Europe project developing a Mobility Analytics as a Service (MAaaS) toolset which will set itself apart by moving more than 30% of the analytics and 50% of sensitive data analytics to edge computing (processing the data on the same devices that collect the data or nearby devices to improve response times and privacy of sensitive data). The technology can improve decision-making by public authorities and individuals, leading to more efficient mobility, saving time, money and reducing environmental impact.

The REXASI-PRO project aims to release a novel engineering framework to develop greener and Trustworthy Artificial Intelligence solutions. The project will develop in parallel the design of novel trustworthy-by-construction solutions for social navigations and a methodology to certify the robustness of AI-based autonomous vehicles for people with reduced mobility.

CEDAR will create an inclusive, federated, and privacy-preserving Data Commons space, to establish a secure and reliable space for sharing information among stakeholders across multiple domains. CEDAR will ensure that more data becomes available in the economy and society while keeping companies and individuals who generate the data in full control in a trusted, secure, and transparent manner.

The FAITH project will develop and validate a human-centric, trustworthiness optimization ecosystem, which enables measuring, optimizing and counteracting the risks associated with AI adoption and trustworthiness in critical domains, namely robotics, education, media, transport, healthcare, active ageing, and industrial processes through seven international Large Scale Pilots.