Aquaticpollutants

Artificial Intelligence-powered Forecast for Harmful Algal Blooms

The eutrophication of water bodies in Europe is contributing to the increase of Harmful Algal Blooms (HABs) which poses serious risk to human health. To address this problem, the AIHABs project will develop an early warning system to forecast the occurrence, spread and fate of cyanotoxins caused by HABs in inland and coastal waters, using Artificial Intelligence (AI) and the latest innovations in mathematical modelling, nanosensors, and remote sensing. The novelty of this project lies in merging these tools with the joint purpose of providing an early warning system to decision-making authorities in terms of risk to the public. The model predictions will allow timely action to minimise the risks of consuming surface waters or using them as recreational resources when the waterbodies are prone to produce toxic cyanobacterial blooms.

A number of candidate sites with a history of HABs in the countries of the project partners will be evaluated using multi-criteria analysis in order to identify the most suitable inland and coastal water sites for use in the study. The main criteria for selecting the sites will be the availability of the required data for modelling and the strong evidence of historical HABs.

 

Keywords

Water quality, Harful Algal Blooms (HABs), Hydrodynamics, Remote sensing, Computer vision,  Artificial Intelligence (AI)

 

 

Achievements so far

Launched in September 2021, the AIHABs project aims to develop an artificial intelligence-based forecasting model for harmful algal blooms (HABs) in inland and coastal waters. The project involves a multidisciplinary team from seven European institutes and is divided into five work packages covering study site selection, water quality sampling, mathematical modelling, development of portable sensors and validation of the AI-based prediction model. Progress includes water quality sampling campaigns in Spain and the Czech Republic, with analysis showing widespread antibiotic contamination and resistance in the study sites. The project aims to characterize HABs, predict their presence using an advanced model, and mitigate risks to human health and the environment. The ultimate goal is to comply with relevant European Union directives on marine and bathing water quality.

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