AI.BIG Cluster: AI and Big Data
Analysis for emergency situation and Extreme Data exploitation

Today, the world faces increasing challenges posed by natural disasters and emergencies that threaten human life and the environment. However, the advent of artificial intelligence and megadata analysis has brought a glimmer of hope to the way we approach and manage these critical events.

Accuracy, Prediction and Prevention

The predictive capabilities of AI combined with Big Data analysis have dramatically improved the accuracy of natural disaster forecasts. Sophisticated models exploiting predictive algorithms make it possible to anticipate and prevent certain events, offering an opportunity for increased preparedness and faster response. These projects aim to revolutionize the way emergency situations are managed, and equip authorities and humanitarian organizations with advanced tools to deal effectively with these crises.

The projects involved in the cluster, funded under the HORIZON-CL4-2022-DATA-01-01 call

TEMA

Trusted Extremely Precise Mapping and Prediction for Emergency Management

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CREXDATA

Critical Action Planning over Extreme-Scale Data

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ExtremeXP

EXPeriment driven and user eXPerience oriented analytics for eXtremely Precise outcomes and decisions

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Machine learning for early warning systems

These systems use data to detect early warning signals of impending disasters. This enables early warnings to be triggered, giving populations and authorities the time they need to prepare and react. These technologies will be tested in several Use Cases, such as :

The Cluster's Projects

The EU-funded ExtremeXP project will create a next-generation decision support framework that integrates novel research from big data management, machine learning, visual analytics, explainable ΑΙ, decentralized trust, and knowledge engineering. The framework aims to improve the performance of complex analytical processes, such as accuracy, responsiveness, specificity, memory, precision and resource utilization, by adapting different computational configurations to various user profiles. It promotes a human-centered approach to artificial intelligence and complex analysis, with an emphasis on experimentation. The project plans to carry out five pilot demonstrations.

The EU-funded TEMA project will improve natural disaster management (NDM) by automating precise semantic 3D mapping and disaster evolution prediction. TEMA will focus on real-time semantic extraction from various modalities and heterogeneous data sources. It will create a constantly updated 3D map of disaster areas, with semantic annotations. This map will enable response teams to visualize and evaluate various strategies using simulations to intervene effectively.

The EU-funded CREXDATA project will develop a generic platform for real-time critical situation management including flexible action planning and agile decision making over streaming data of extreme scale and complexity. The project will develop algorithms, software structures and tools to enable federated predictive analysis and forecasting under uncertainty. It will support proactive decision-making by providing accurate short- and long-term forecasts, while ensuring transparency and explanation through advanced visual analysis. In addition, it will enable the use of accurate, real-time augmented reality facilities.

The ExtremeXP project is co-funded by the European Union Horizon Program HORIZON-CL4-2022-DATA-01-01, under Grant Agreement No. 101093164
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