In today's world, the health of our planet and its inhabitants faces significant challenges, including deforestation, pollution, and climate change. Addressing these issues requires innovative, cross-sectoral efforts; this is where the PLANET4Health EU-funded project steps in. This initiative brings together 17 partners from 12 countries, including LIBRA AI Technologies, to tackle the interconnected health of humans, animals, and ecosystems.

PLANET4Health focuses on four key areas:

  • Vector-borne diseases in the Iberian Peninsula,
  • Air pollution in South Africa,
  • Food contamination in Central Europe,
  • and the mental health impacts of environmental and climate stressors.

The consortium aims to create replicable solutions that improve predictive capability and preparedness for these challenges by leveraging research, technological innovation, and policy support.

LIBRA AI Technologies’ Role

LIBRA AI Technologies plays an important role in the PLANET4Health initiative by defining and developing a sophisticated Machine Learning (ML) framework specifically designed for time-series forecasting. This framework focuses on building advanced capabilities for predicting future trends and events by analyzing sequential data over time. It includes specialized techniques for temporal forecasting, which examines changes over time, and spatiotemporal forecasting, which integrates time and spatial dimensions to analyze patterns across different regions. These forecasting capabilities are crucial for providing accurate predictions that can inform proactive decision-making and early interventions in health and environmental contexts.

The AI toolbox developed by LIBRA AI Technologies is equipped to manage various ML tasks, streamlining essential processes such as data preparation, model selection, and unbiased model comparison. This ensures efficient data handling and facilitates the identification of the most suitable models for each task, enhancing the accuracy and reliability of outcomes. To maintain transparency and trust in the AI models, the framework incorporates Explainable AI (XAI) techniques. It offers clear interpretations of model results and provides stakeholders with insights into how specific predictions are derived and which factors influence them.

In addition, the toolbox integrates MLOps practices for effective model management. This includes tracking model versions, monitoring performance metrics over time, and ensuring continuous improvement of ML solutions. These practices enable efficient lifecycle management and reproducibility of models, ensuring their sustained performance and scalability.

The ML models and analytical capabilities generated through this framework significantly enhance key components of the PLANET4Health project, such as early warning systems and digital tools customized for various case studies. By delivering advanced forecasting and analysis capabilities, LIBRA AI Technologies ensures that the PLANET4Health project is equipped with reliable, data-driven insights that support proactive decision-making. This approach allows LIBRA AI Technologies to contribute to the project's overall success by providing cutting-edge AI solutions that are accurate, efficient, transparent, and easy to manage over time.

LIBRA AI Technologies will also manage data storytelling activities to ensure the project findings are widely accessible, relevant and engaging for various stakeholders. Additionally, as task leaders, we will coordinate the innovation and exploitation efforts, ensuring the project's outputs are scientifically sound and practically applicable.

Learn More

PLANET4Health is a 48-month European project launched in January 2024 and funded by the European Commission's Horizon Europe Research and Innovation Programme.

Visit the Planet4Health website for more details on the project's objectives and expected impact, 

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