Artificial Intelligence for Sustainability
Artificial Intelligence (AI) for sustainability refers to the application of AI technologies and techniques to address environmental, social, and economic challenges with the ultimate goal of promoting sustainable development and preserving the planet’s resources for future generations. AI plays a pivotal role in analyzing vast amounts of data related to climate change, biodiversity, energy consumption, and other sustainability-related factors. It enables predictive modeling, data-driven decision-making, and optimization of resource usage, leading to more efficient and effective sustainable practices.
At DaSCI we have analyzed in depth how Artificial Intelligence can be a determining factor in the achievement of the Sustainable Development Goals (SDG). Our lema is AI-loves-SDG.
We seek to support research in AI and SDGs to advance four main goals:
- Strengthen the research line on AI for climate change by developing AI models to analyze the impact of climate change in the Sierra Nevada area, particularly for plant species identification using drone and satellite images. We participate in the LifeWatch Smart Ecomountains project.
- Reinforce the research line on AI for Renewable Energy (RE) by proposing AI models for characterizing photovoltaic systems, modeling fuel generation with biomass, and optimizing generation systems for energy consumption. Advanced AI models will be developed for combined power generation systems, circular economy aspects, and explainability in specific tasks. We participate in the MOBILETE project.
- Enhance the research line on AI for sustainability in agriculture by utilizing AI models to improve sustainable agriculture practices, including water assessment, plant disease detection, and automated yield estimation using deep learning and computer vision. DaSCI have achieve goals for in-field plant water assessment using AI and non-invasive sensors (spectroscopy and thermometry), but further research and transfer is still needed.
- Strengthen the research line on AI to prevent global deforestation by developing AI models for wood species recognition to monitor and prevent illegal timber trade, assisting customs agents and authorities in early detection of suspicious shipments. We participate in the GO IMAI project. Future research focuses on making the models robust to attacks and changes in data distribution and enhancing their explainability and generalization.
Related Researchers:
Letra: |
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| Name | Area | Cat. | ||
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Bergmeir, Christoph | bergmeir@ugr.jco_4pX4mes | Data Science and Big Data Area | PhD - Maria Zambrano |
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Gómez Romero, Juan | jgomez@uXEhC5Ldm_gr.es | DaSCI Technology Applications Area | PhD |
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Gutiérrez Salcedo, Salvador | salvagutiAj@6dCzov@decsai.ugr.es | Data Science and Big Data Area | – |
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Herrera Triguero, Francisco | herrera@decsairXl1G2_pNnJ.ugr.es | – | |
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Khaldi, Rohaifa | rohaifa.khaldi@lifehku2jFwatch.eu | – | |
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Molina Solana, Miguel | miguelmolina@uifqdNI2Vfgr.es | – | |
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Montes Soldado, Rosana | rosana@ugfconninBKHYGr.es | DaSCI Technology Applications Area, Computational Intelligence Area | PhD |
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Peregrin Rubio, Antonio | peregrin@dti.eQrz2Z6uhu.es | – | |
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Tabik, Siham | siham@u98oY_Urgr.es | Data Science and Big Data Area | PhD |