Projects

Keeping in mind the potential opportunities, risks and limitations offered by Artificial Intelligence (AI), AI4CCAM will develop an open environment for integrating trustworthy-by-design AI models of vulnerable road user behaviour anticipation in urban traffic conditions to ensure improved road safety and user acceptance.

Leveraging the Trustworthy AI...

The EERIE answers Horizon Europe call: HORIZON-CL5-2022-D1-02-02: Development of high-resolution Earth system models for global and regional climate change projections.

The project uses four European global climate models to produce new simulations of past and future climate. The representation of ocean processes will be at the cutting edge given that...

ASPECT aims to setup and demonstrate a seamless climate information (SCI) system with a time horizon up to 30yr and accompanied with underlying research and using climate information for sectoral applications ( middle-ground level 1). The project's goal is to improve existing climate prediction systems and to merge their outputs across timescales together with climate...

Precipitation directly affects societies and ecosystems, with extremely wet and dry conditions posing potential risks. Our ability to predict variations in precipitation on seasonal, inter-annual and decadal time scales is limited, and state-of-the-art prediction systems exhibit low skill in predicting precipitation despite substantial developments and improvements of the...

Compound events (CEs) can pose significant threats to societies, economies and ecosystems around the world, especially when amplified by anthropogenic climate change (ACC). There is therefore a strong need for skilled, reliable and actionable predictions of how CEs are expected to change in the next decades to help governments and stakeholders implement robust adaptation...

The high-performance demands of the functionalities required in complex critical systems is rapidly increasing. In the space domain, on-board processing algorithms for navigation and control systems are needed to increase  spacecraft autonomy; in the automotive and railway domains, advanced driving assistance systems (ADAS) and obstacle detection and avoidancesystems...

A growing number of applications rely on AI-based solutions to carry-out mission-critical tasks, many of which are of temporal nature, dealing with ever-evolving flows of information. Crucial for mitigating threats and taking advantage of opportunities in such domains, is the ability to forecast imminent situations and critical complex events ahead of time. EVENFLOW will...

Deep Learning (DL) techniques are key for most future advanced software functions in Critical Autonomous AI-based Systems (CAIS) in cars, trains and satellites. Hence, those CAIS industries depend on their ability to design, implement, qualify, and certify DL-basedsoftware products under bounded effort/cost.There is a fundamental gap between Functional Safety (FUSA)...

Cardiovascular disease (CVD) remains the leading cause of mortality worldwide, accounting for about a third of annual deaths. Refusing structured and unstructured data has the potential for significant health benefits for the population suffering from CVD. Healthcare data reuse in Europe faces privacy and fragmentation issues, high data formats and language diversity, and a...

Despite clear signs that the impacts of climate change are escalating, the global response has been inadequate. Traditional scientific efforts have fallen short of providing knowledge and tools that have been broadly applied in decision-making, and innovative approaches to knowledge translation are needed.

To catalyse climate action in Europe to protect public health,...