The DeepFlow project (DEEP learning for FLOWing water quality monitoring) will develop an autonomous and intelligent continuous monitoring system for the visual detection of contaminants in water, such as hydrocarbons, in both natural and industrial environments.
The solution is based on computer vision and deep learning technologies for the visual detection of contaminants using cameras placed in strategic locations in channels, rivers, and treatment ponds. These images are processed with Artificial Intelligence (AI)-based algorithms to recognize visual patterns of contamination. In the case of hydrocarbons, the models are trained to identify the formation of multicolored iridescence or shiny films caused by thin layers of oil on the surface. Finally, this integrated system will generate automatic alerts in the event of anomalies.
With this technology, DeepFlow aims to overcome the limitations of traditional detection systems, which are subjective, have limited coverage, and often rely on precise sensors that are expensive.
Project coordinated by Cetaqua.
DeepFlow project has been funded by the European Union – NextGenerationEU through the Recovery, Transformation and Resilience Plan, implemented by the Department of Business and Labour of the Government of Catalonia.
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