AI-powered Forecast for Harmful Algal Blooms (AIHABs)

AIHABs is a multidisciplinary innovative initiative aimed at developing an integrated evaluation system to forecast the risk derived from thepresence of emerging cyanotoxins in inland and coastal ecosystems.

Ongoing project

The innovation of this project resides at merging tools as last generation Artificial Intelligence (AI), remote sensing, nanosensors, hydrodynamic modelling and massive genetic sequencing with the joint purpose of providing an early warning system to decision making authorities in terms of risk to the population. The predicting modelling effort will allow a timely action to minimize the risks of consuming surface waters or using them as recreational resources when the waterbodies are prone to produce toxic cyanobacterial blooms.

 

Project partners

  • Ahmed Nasr, Technological University Dublin, Ireland (Coordinator)
  • Jakub Brom, University of South Bohemia in České Budějovice, Czech Republic
  • Mohammadmehdi Saberioon, Helmholtz Centre Potsdam – GFZ German Research Centre for Geosciences, Germany
  • Marcos Xosé Álvarez Cid, Norwegian University of Science and Technology, Norway
  • Begoña Espiña, International Iberian Nanotechnology Laboratory – INL, Portugal
  • Antonio Quesada, Universidad Autónoma de Madrid, Spain
  • Fernando Cobo Gradín, University of Santiago de Compostela, Spain

 

Publications