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The Cluster

AI and Big Data Analysis for emergency situation and Extreme Data exploitation

The technologies, adopted in the Cluster projects, foresee Machine Learning for Early Warning Systems, Image and Video Processing for Damage Assessment, Predictive Analytics for Post-Disaster Recovery Planning, and others.

These technologies will be tested in several Use Cases, such as:

  • Weather Emergencies
  • Health Crisis
  • Maritime Emergencies
  • Increased Cybersecurity
  • Transportation analysis and visualization
  • Flash flood forecasting and management
  • Forest fire prediction and management
  • Social Media Analytics for Situational Awareness
  • Real-time Resource Management and Allocation

 

What is a Project Cluster?

The European Commission has been incentivising the clustering of Horizon Europe projects in order to multiply the impact financed projects seek. By forming or joining a cluster, engaged projects can better collaborate and mutually support each other through knowledge sharing and benchmarking project outcomes, hence creating synergies and facilitating the achievement of the proposed impacts.

In other words, project clustering refers to an alliance created by projects with related subjects or complementing interests, which can encompass partnerships for communication and dissemination activities, participation in meetings of common interest, joint capacity building activities and workshops, among other examples.

In response to the increasing frequency and severity of natural disasters and emergency situations globally, a cluster of innovative projects has emerged, centered around the application of Artificial Intelligence (AI) and Big Data Analysis and managing&exploitation of extreme data. The aim is to advance the boundaries of analytics, prediction, simulation, and visualization, in order to yield highly accurate, timely, and valuable results from data and knowledge. This is done to support decision-making, whether conducted by humans or automated systems, with the ultimate goal of saving lives or generating significant positive impact (economically, socially, environmentally) compared to traditional decision-making methods.These projects aim to revolutionize the way emergency situations are managed and equip authorities and relief organizations with advanced tools to tackle these crises effectively.

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

  • CREXDATA (Critical Action Planning over Extreme-Scale Data)
  • ExtremeXP (EXPeriment driven and user eXPerience oriented analytics for eXtremely Precise outcomes and decisions)
  • TEMA (Trusted Extremely Precise Mapping and Prediction for Emergency Management)

This Cluster of projects represents a groundbreaking endeavor to harness the power of AI and Big Data Analysis for emergency situations and extreme data management. Through early warning systems, damage assessment tools, social media analytics, resource management optimization, and predictive recovery planning, these projects strive to enhance preparedness, response, and recovery efforts, ultimately leading to more efficient and effective disaster management worldwide.

The Cluster’s Projects

The EU-funded project, ExtremeXP, is creating a next-generation decision support framework that integrates novel research from big data management, machine learning, visual analytics, explainable ΑΙ, decentralised trust, and knowledge engineering. The framework aims to optimize the properties of complex analytics processes (e.g., accuracy, time-to-answer, specificity, recall, precision, resource consumption) by associating different user profiles to computation variants, promoting a human-centered, experimentation-based approach to AI and complex analytics. 

The EU-funded TEMA project is improving natural disaster management (NDM) by automating precise semantic 3D mapping and disaster evolution prediction. To that end, it analyses and combines many heterogeneous extreme data sources and develops an integrated, ground-breaking NDM platform. TEMA focuses on real-time semantic extraction from multiple heterogeneous data modalities and sources and construct a semantically annotated 3D disaster area map, which will be constantly updated, allowing the personnel to visualise and evaluate different response strategies through simulation.

The AI-on-Demand platform (AIoD) is a community-driven channel designed to empower european research and innovation in Artificial Intelligence (AI), while ensuring the european seal of quality, trustworthiness and explainability.

The Research element provides a space for researchers and other interested users to learn more about verifiable AI, integrative AI, collaborative AI and physical AI, and to access research bundles and AI assets.

CREXDATA being part of the community will take advantadge and provide datasets among other contributions to the platform.

The CREXDATA project works within the greater ecosystem of HORIZON EUROPE projects  that contribute to the Digital Europe Programme. We share common objectives with the other 25 Horizon Europe projects funded under Horizon Cluster 4–2021/2022–Data–01 call: World Leading Data and Computing Technologies.