Imagine having a super-powered crystal ball that looks at massive amounts of live data to predict disasters before they happen. It doesn't just give a warning; it shows you exactly what might happen using 3D visuals and augmented reality. This helps leaders make fast, smart choices when every second counts, like during a storm or a health crisis.
Decision makers in critical situations often struggle with massive, complex data streams that are hard to interpret in real-time. This leads to slow reactions and inaccurate forecasting during disasters or health crises.
A Prediction-as-a-Service (PaaS) system featuring a forecasting engine, simulation tools, and an augmented reality interface for visualizing future scenarios.
If you are a Shipping and Port Authority dealing with hazardous sea conditions — this project developed a prediction system that forecasts dangerous situations to impose safer navigational routes.
If you are a Civil Protection Agency dealing with natural disasters — this project developed a forecasting tool that allows first responders to act proactively to reduce the impact of weather emergencies.
If you are a Public Health Organization dealing with pandemic outbreaks — this project developed a predictive analytics system to limit the spread and find non-pharmaceutical treatment methods.
Based on available project data, no specific pricing or cost details are provided as it is an EU-funded research project.
Yes, the system is designed for 'extreme-scale' streaming data and uses federated learning to handle compute resource federations across different locations.
Based on available project data, the project identifies 10 exploitable assets, but specific licensing terms are not listed in the summary.
The system allows action planners to register multimodal data stream sources and graphically design workflows for data ingestion and fusion.
The project period runs from 2023-01-01 to 2025-12-31, suggesting the final results will be available by the end of 2025.
The consortium is composed of 16 partners from 6 countries, showing a strong European research base. With 7 research organizations and 4 universities, the project is heavily academic, but it maintains a 19% industry ratio with 3 SMEs, ensuring that the 10 exploitable assets are developed with a view toward commercial application.
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